Since 1914, AI has helped power commercial airplanes’ autopilot functionality. Today, spam filters, mobile check deposits, and facial-recognition technology all use AI to make consumers’ lives easier.

And in e-commerce, AI is used to improve website search functionality and make better recommendations based on recent browsing activity. The technology also helps power retargeting ads and chatbots.

Now, leading brands and retailers are tapping this technology to improve the shopping experience for customers in innovative new ways. Thanks to the growth of AI in e-commerce, shopping from home, in the park, or literally anywhere you have an internet connection, just got a whole lot more exciting.

Chapters:

1. Awesome ways AI is impacting e-commerce
2. AI in e-commerce examples
3. How to optimize your AI in e-commerce strategy

Awesome ways AI is impacting e-commerce

We’ve been watching the AI trend closely over the past year. Here are some of the most exciting AI in e-commerce use cases to date.

Though it would be fun to list all of the capabilities, approaches, and uses AI provides for e-commerce businesses, we’d be here for a while. Rather than forcing you to take a few personal days to get through it all, we thought we’d narrow it down to our favorite ways AI is changing the world of e-commerce.

1. Endless personalization

Oh, personalization. The hot topic that’ss taken consumer demands to another metaverse while forcing retailers to ask themselves, “Do I really know my customers as well as they want me to?”

Personalized shopper journeys are more of an expectation than an add-on these days. Luckily, AI algorithms can analyze colossal amounts of data, providing valuable insights into things like customer behavior, preferences, and trends. This information helps e-commerce businesses make data-driven decisions, optimize marketing strategies, and customize their offerings to each shopper’s needs. 

The result? A bucket load of customer satisfaction, increased engagement, and higher revenue. Personalization has also been proven to strengthen brand loyalty — 70% of consumers say that how well a company understands their individual needs impacts their loyalty. Give them what they want (personalized, relevant experiences), and watch their support grow.   

Personalized product recommendations 

You can’t talk about e-commerce personalization without mentioning its compatriot, AI-generated product recommendations. These subtle suggestions can create quite the shopper stir when delivered at the right time and in the right way.

First, AI algorithms analyze customer data, like browsing behavior and purchase history to identify shopping patterns. Then, that information is used to recommend products that might interest the shopper. And boom: more sales.

Intuitive cross-selling + upselling

Remember that important customer data we previously mentioned? AI systems can use it to identify relevant cross-selling and upselling opportunities. Even better, AI has a large capacity to learn and adapt, which means that over time you’ll be able to maximize your supplementary sales, propelling and improving your customer lifetime value.

2. It enhances the customer experience

One of the most meaningful ways AI is evolving e-commerce is by providing marvelously-engaging customer shopping experiences. From the very first search to the final post-purchase adieu, AI enables your digital store to function in a way that makes each shopper feel like it was created just for them.

Smarter site search

While it might seem somewhat unassuming, an e-commerce site’s ‘search’ can tell a huge story. And when powered by machine learning technology, its narrative includes advanced algorithms that are enhancing product discovery for online shoppers.

AI uses advanced natural language processing (NLP), making a user’s shopping experience faster, easier, and more intuitive. By understanding consumer language and combining keyword search and vector search into a single query, results are more accurate, and relevant. This means shoppers have a higher chance of finding exactly what they’re looking for, through two key ways:

1. Voice search. This well-known speech recognition technology allows shoppers to search phrases quickly without using a mobile device’s keyboard. Thanks to emerging AI, voice commerce has seen some impressive upgrades. For starters, speech analysis and contextual reasoning have led to more accurate voice recognition. It also saves customers time by reducing the effort (and chance for errors) of manual typing — handy for lengthy product names like, “Organic Queen Size Memory Foam Lavender Scented Pillow”
2. Visual search. Sometimes, a shopper wants to find a product but doesn’t know its name, type, or the category it falls under. Usually, it’s right about here that their search journey ends. But with visual search, potential customers can look for products using images and nothing else. If an online visitor doesn’t know the details of an item they’re interested in, all they need to do is use a picture to find what they’re searching for. Not only does this increase product exposure, but it elevates the customer experience by alleviating the friction between curiosity and acquisition

Interactive augmented and virtual reality

Both augmented reality (AR) and virtual reality (VR) enhance the e-commerce experience by providing immersive and responsive features that minimize the gap between online and physical (phygital) shopping.

Maybe it’s because AR integrates simulated elements with the real world, enabling shoppers to engage with products in their own surroundings. Or maybe it’s because AR can seamlessly work with existing devices, so shoppers can experience a product from their iPhone or tablet. Either way, the global AR market is expected to reach $300 billion this year.

Shoppers can try on virtual products, see how items will look and fit in their space, and participate in interactive demonstrations. Another cool AI-driven feature: online retailers can incorporate tailored recommendations and offers for an additional layer of personalization. 

Chatbots and virtual assistants 

One of the most significant ways AI is transforming e-commerce is through improved customer service. Most e-commerce businesses don’t have time to compose a personalized response to every incoming inquiry. This is where artificial intelligence can really serve a purpose.

Chatbots enable online retailers to provide 24/7 support to their customers. And because they never take breaks or get heated, chatbots can provide a level of service humans can’t match up to. Did we mention they don’t get paid either? 

Chatbots use NLP to understand customer queries. This allows them to provide immediate and accurate responses, help shoppers make smart purchasing decisions, and assist with order tracking and returns. These virtual assistants have already been a lifesaver for many digital stores and consumers.

Streamlined checkout process

Did you know that the average cart abandonment rate is around 70%? The good news is that AI can help to decrease the number of lost customers during the checkout process. 

AI algorithms optimize the checkout flow by assessing customer behavior and preferences to determine if any recommendations or messaging is needed for that final purchasing persuasion. 

Machine learning can also save shoppers time by inputting customer information, and offering advanced support by providing effortless payment processing. Together, this creates a more streamlined shopping experience that can minimize cart abandonment and maximize conversion rates.

3. It improves business operations

There’s a lot that goes on beyond what a shopper sees on their device’s screen. AI makes managing the back-end of e-commerce easier by providing tools that boost efficiency, save on costs, and help online retailers know exactly who to market to.

Increasing productivity

The use of AI in e-commerce empowers businesses to automate several procedures that are usually performed manually. By utilizing this innovative technology, online retailers can diminish their time spent on repetitive and arduous tasks, such as packaging items, restocking shelves, and troubleshooting issues.

The best part? The more AI software is introduced, the more its capabilities improve, resulting in a revolving loop of productivity.

It’s important to note that automation doesn’t mean extinguishing all redundancies or replacing people with technology. Rather, AI and machine learning streamline repetitive tasks, limiting the chance of operational errors. This frees your team from monotonous jobs, allowing them to channel their efforts toward more complex and creative responsibilities that have a greater impact on your bottom line.

Predictive analytics tools

AI-driven, predictive analytics tools can examine enormous volumes of customer data to forecast market trends, potential risks, and future opportunities. These insights enable you to make informed decisions and customize your sales and marketing strategies to better align with shopper preferences. 

Predictive analytics tools also play a crucial role in helping e-commerce businesses with supply chain management – but more on that in a minute. 

Customer segmentation

Thanks to AI technology, hyper-segmenting audiences based on data like browsing history, life stages, and even major hurdles, has become easier than ever. This information helps online retailers gain knowledge about everything from a customer’s preferences and behaviors, to their sentiments about products and services.

As a result, e-commerce businesses can tailor marketing campaigns and sales offers toward select shoppers. Plus it allows online merchants to get incredibly specific about targeting, messaging, and timing, which increases the chance of a better return on investment (ROI).

4. Superior supply chain management 

AI is modernizing the e-commerce industry by providing greater automation in supply chain management. Predictive analytics can help optimize stock levels, streamline delivery routes, and forecast potential disruptions. Here’s a quick breakdown for you.

Demand forecasting

Many online retailers rely on artificial intelligence for sales predictions to make demand forecasts more precise. Instead of using historical data, AI software makes sales and demand predictions using real-time data like weather, demographics, and online reviews, to name just a few. This allows you to adjust inventory levels and enhance operational adeptness.

Inventory management 

Good inventory management focuses on monitoring stock levels to ensure the right supply is always available to meet customer demand.

AI helps e-commerce stores maintain adequate inventory levels by utilizing data such as sales trends from previous years, projected changes in product demands, and impending supply-related issues that could affect stock availability.

And unlike pesky humans, AI robots can be used 24/7 to dispatch items immediately following an order, fetch inventory, or stockpile merchandise.

Optimized pricing strategies

AI-powered dynamic pricing lets e-commerce businesses adjust their pricing based on supply and demand.

Using data analytics and more machine learning methods, AI algorithms evaluate market trends, customer behavior, and competitor pricing to determine the best price for any product. 

Dynamic pricing algorithms can then adjust prices in real-time to enable digital retailers to boost revenue and maintain a competitive edge.

AI in e-commerce brand examples

AI is already well underway and brands are taking note. Here’s some of our favourite brand examples of AI in e-commerce.

Playing makeup at home

One of the best arguments for using AI in e-commerce is trying on items — virtually. NARS Cosmetics’ virtual try-on uses a shopper’s camera to instantly detect the contours of the face. As shoppers click on shades of lipstick, bronzer, and eyeshadow, the makeup is superimposed on their lips, cheeks, and eyes.

Occasionally a set of bright red lips appear in the middle of the screen, but the experience is surprisingly smooth and accurate. The technology also automatically evens out shoppers’ skin tone, making the makeup extra flattering.

Home sweet (virtual) home

Target’s See It in Your Space tool uses AR to allow shoppers to literally see how furniture and decorations will look in their home. Shoppers can either upload a photo of a room or use the Target app to access their device’s camera. Then, they select furniture to overlay on the image.

The tool helps them see if items will fit in the space, coordinate with other items, and decide which finish or color works best. 

Taking ‘see it for yourself’ to another level

Eyewear brand Warby Parker was an early adopter of AR. Its app allows shoppers to see how each frame will fit their face.

The brand’s Virtual Try-On feature also won a Webby Award. Shoppers can click through different styles and colors to see which best complements their face shape. Once they’ve picked their favorites, Warby Parkers allows shoppers to select 5 frames to try on at home for free.  

H&M’s personal stylist

H&M use an AI chatbot as their own personal shopping assistant. The bot learns each shopper’s style preferences through a series of questions, then presents options to the shopper to choose from.

Based on continual feedback from the shopper, the chatbot continues to offer up new suggestions, advice, and products for them to purchase.

3D luxury

Consumers looking for a new designer handbag or wallet can now view 3D images of their favorite Burberry products online. The items are scaled to size and then superimposed on the shopper’s camera screen.

Consumers can then see what a purse looks like on their shoulder or countertop and see how it complements their favorite outfits.

How to optimize your AI in e-commerce strategy

AI is clearly here to stay. Whether it’s transforming e-commerce by delivering endless personalization, enhancing the overall customer experience, or improving company operations, the AI revolution is changing the way we do business. But don’t forget: AI is here to enhance, not replace.

Ready to unlock the power of AI for e-commerce? Bazaarvoice Insights and Reports tools seamlessly integrate AI to boost efficiency and optimize your marketing strategy. Whether for boosting sales, improving products, or competitor analysis, our tools have you covered. 

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Masterclass: How to use AI strategically and responsibly

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E-commerce and brand managers will soon have to rely on first-party data — the data you collect directly from customers yourself.

Not just to stay compliant with privacy regulations such as the GDPR and CCPA, but because a first-party data strategy can enhance your revenue, provide value internally for your business, give you better customer data, and ultimately help you build a relationship with your customers. 

Chapters:

1. What is first-party data?
2. How to use first-party data
3. How to collect first-party data
4. First-party data e-commerce strategies
5. Examples of first-party data strategy in action
6. Maximize your first-party data

What is first-party data?

First-party data is customer information and data that you collect yourself — directly from your audience. Nobody else owns this data except you. It cannot legally be sold or shared, it doesn’t follow users outside of your website, and it’s made up of two different “types” of data.

1. Declarative data

Declarative data is the data that your audience self-reports, such as their name, email address, location, and more. It doesn’t just have to be rote demographic data, however. It can also be data such as their income level, the number of pets they have, and more. It’s especially useful for understanding consumer behavior and finding out what triggers buying behaviors.

Example: A customer informs you that they have pets: two cats. This information comes directly from the customer.

2. Behavioral data

Behavioral data is data based on the activities of a site visitor. This type of data is often collected via the use of a first-party cookie or tracking pixel. This cookie is unique to your site and your site only, and never follows the user across the web. Tools like Google Analytics are commonly used in conjunction with behavioral data to analyze site performance and user behavior, giving marketers and managers granular details about what parts of their website are performing and what parts need improvement.

Example: A customer likes several cat pictures and pages on Instagram but does not explicitly tell a business they have any cats. It’s up to the business to make that inference.

How to use first-party data

Before you start on your first-party data strategy, there’s some housekeeping and tactics that will need looking at first.

Align with stakeholders on what first-party data you’ll collect

First, you need to align with stakeholders on what first-party data you’ll collect. This way, you have buy-in from everyone on your team, and everyone’s needs are equally represented. Because this first-party data will become your only data source, it needs to be as robust as possible, while still keeping within regulations.

Aligning with stakeholders requires some prep on your end. Before meeting with the different stakeholders in your organization (managers, executives, legal, IT), come up with a list of metrics you’d like to track. Some common ones include sales interactions, emails, phone numbers, site behavior, purchase history, and common demographic information, such as age and location.

Next, you’re going to want to run this list of possible data points by your stakeholders, justifying why you want to collect each data type and how you’re going to do it, so there isn’t any friction between departments over what data is collected and how it’s being used.

Update to the latest Google Analytics data model

Google Analytics version 4 includes new ways to segment and track users, is GDPR and CCPA compliant, and is built to take on first-party data by utilizing AI to fill in data gaps that third-party data would ordinarily have filled.

The ever-popular analytics tool specifically addresses issues with the retirement of third-party data and inconsistencies in cookie consent options by using AI to fill in missing customer information, meaning you can still collect and analyze user data even if you don’t have a complete user profile.

Additionally, Google Analytics 4 helps you easily find and delete user data upon request, which means you can stay compliant with “the right to be forgotten.”

Looking to get started with a site implementation? Google has some valuable resources and a step-by-step guide to implementing Google Analytics 4 properties on your website’s analytics property.

Build new personas and segment your audiences based on first-party data

Because you’ll be using first-party data moving forward, you need your personas to be as accurate as possible; working with inaccurate or baseless buyer personas is a huge waste of time and resources. But you can’t keep relying on third-party data to build your buyer personas. Ask any marketer how accurate their third-party data is, and you’ll probably get back a “not very.” Survey data collected by Deloitte unearthed some startling facts about first-party data’s ugly cousin:

• Over 66% of respondents said that the third-party data about them was zero to 50% accurate as a whole
• Around 71% of all third-party data was deemed inaccurate after a review by survey respondents

As part of a first-party data strategy, personas based on first-party data are crucial to providing a personalized e-commerce marketing and advertising experience. Buyer personas based on first-party data have a number of benefits, including a 10–20% reduction in marketing and sales costs, a 20% higher customer satisfaction rate, a 10–15% increase in sales conversion rates, and a 20–30% increase in employee engagement.

Start by leveraging all the first-party data you can to build your personas. This might include data like location, age, purchase history, audience research, CRM data, or user account information, all of which can be consensually collected without the use of third-party data or cookies.

How you divide your customer base is entirely up to you. But some common shopper segmentations include: 

• Shared characteristics and behaviors
• Common interests
• Demographics
• Region
• Purchase or browser history
• Frequent shoppers or buyers
• New customers
• Recent cart abandoners
• Browsing or buying habits
• Engagement levels
• Average AOV (e.g. big spenders, sales hunters, etc.)

Build a data governance strategy that keeps you compliant

Data governance is the process of ingesting data and managing that data’s lifecycle from creation to storage to deletion.

Both the GDPR and CCPA have clauses that allow users to request their data be deleted — “the right to be forgotten” and “right to erasure.” Data governance strategies play a huge role in both of these clauses — you can’t comply with a data deletion request if you can’t easily find and manage that data in the first place.

Failure to govern your first-party and third-party data in accordance with regulations could put you in regulatory hot water. The GDPR imposes stiff fines for companies who fail to comply. Amazon was hit with a massive $887 million fine for not complying with the GDPR.

Failure to govern your first-party and third-party data in accordance with regulations could put you in regulatory hot water.

Building a data governance strategy requires you to consult with two teams: legal and IT. Legal will be able to tell you what needs to happen to the data you have from a governance standpoint. IT will be able to help you find a solution to managing your data.

Start collecting first-party cookies in place of third-party cookies

You may have seen those popups on some websites asking to place cookies on your browsers while also offering you the chance to opt in or out of data collection. That’s how first-party cookies are placed in a way that’s compliant with regulations — and it’s a crucial aspect of your first-party data strategy. There’s a few key ideas at work here:

• Customer information gathered from first-party cookies is gathered consensually
• This data is being used on this site and only on this site and will not follow the user across the web

Ordinarily, companies use third-party cookies — cookies that have been placed on users’ browsers by third-party sites — to gather customer data. These cookies are placed without the consent of the user, directly violating the GDPR and CCPA, which prohibit the non-consensual placement of third-party cookies. How do you start collecting first-party cookies?

You can do this manually by consulting the different teams in your org about how you’re going to implement a first-party cookie strategy. Design the language and copy, then take your plan to legal, and finally to IT, who can implement a first-party cookie solution. 

If you’re a small or medium-sized business, services like Cookiebot can help you set up collection popups. Larger organizations can rely on tools like OneTrust to do this at scale.

Value exchange

Value exchange is a tactic used to entice customers into exchanging their personal information for high-value content or services (you might recognize this as giving your email in exchange for an e-book or a discount from a company). Value exchange is consensual data collection that’s compliant with the GDPR and CCPA, and it’s mutually beneficial to your business and the customer. It’s a win-win that provides some great, long-term benefits.

Common value exchange tactics are to offer discounts, which help you gather emails, and loyalty programs, which can improve your bottom line and your brand’s relationship with your customers. You get their data and earn their trust, and the customer gets a valuable piece of content, item, or service.

Additionally, it represents your commitment to user privacy and data transparency. You’re being upfront about what you’re collecting, why, and what the customer is getting in exchange for their data. This type of approach is great for building goodwill with your customers and helps you stay compliant with regulations.

How to collect first-party data

Collecting first-party data starts with building users’ trust, gaining their consent, engaging the customers in ways that prompt them to volunteer information, and having the right tech to gather first-party data in place. Here are some tried-and-true methods of collecting first-party data:

Be transparent about the data you do collect. Customer trust is built on transparency, but one in five consumers still believe businesses don’t care about privacy. Separate your business from the pack by explaining how you’re going to use the data you do collect and how it’s being collected in your cookie consent popup.

Ask for reviews from customers. Asking for customers to review products in your e-commerce store is not only a great way to improve your sales performance but also gain access to customer data consensually.

Offer quizzes to your customers in exchange for personalized recommendations. Customers like personalized product or content recommendations — 35% of Amazon purchases come from product recommendations, and 75% of Netflix watches come from recommendations based on customer data. Learning a buyer’s likes, dislikes, and interests is a great way to improve the customer experience, your ROI, and consensually gather first-party data.

Let customers make accounts in your e-commerce store. Accounts are a veritable treasure trove of first-party data. By letting customers volunteer information via user-created profiles, you give them an incentive to return to your e-commerce store and can also mine their accounts for useful bits of data.

Reward repeat customers with a loyalty program. Building a successful customer loyalty program provides you with a dynamic source of customer data — a data source that is constantly evolving and is updated by the customer — as well as better sales numbers and increasing your brand loyalty. It’s a win-win for everyone.

Ask users to participate in surveys. Customer satisfaction surveys are an excellent way of improving your products and services. Surveys can also function as a source of first-party data, giving you the ability to tie interactions back to specific customers so you can identify points of friction within your e-commerce store or customer journey.

First-party data e-commerce strategies

Follow these best-practices for using first-party data to drive e-commerce growth.

Retarget hesitant shoppers

Retargeting is a super effective way to use first-party data to reach customers who have shown interest in your products but haven’t completed a purchase. Use data from website visits to create targeted ads that remind them about their viewed or wishlisted products or items left in their carts.

This subtle-yet-not-so-subtle nudge brings reluctant customers back to your site and also nudges them to complete their purchases.

Generate personalized product recommendations and promotions

With 91% of consumers more likely to shop with brands that provide relevant offers and recommendations, implementing this strategy into your e-commerce marketing plan is a no-brainer. Utilize purchase and browsing history to tailor offers and product recommendations that are most likely to appeal to each customer.

These can be displayed on product pages, in email campaigns, and even during the checkout process, and should include related or complementary items that encourage upsells and cross-sells to increase average order value.

Enhance the shopper journey

Strengthening customer relationships is paramount for any e-commerce business’s growth. The stronger the relationship, the greater the trust. And the greater the trust, the deeper the loyalty — which just so happens to convert to higher online revenue. 

Analyze your first-party data to identify any pain points and areas for improvement. This will allow you to optimize the customer experience by reducing any friction throughout the conversion funnel. For example, your first-party data might highlight that many of your customers make their exit during checkout after they see limited payment options.

So then you could add more payment methods, such as buy now, pay later.

Strengthen your loyalty program

A recent study found that 79% of consumers are more likely to do business with a brand because of its loyalty program, which translates to increased customer retention and revenue. Your best approach for making your loyalty program a reason that shoppers seek out your business?

Begin by using your first-party data, such as shopper preferences and previous purchases, to tailor your rewards to each customer. 

And with third-party data going away, loyalty programs are going to be more important than ever when it comes to customers actively sharing their information. With a well-executed, personalized loyalty program, you can increase your customers’ lifetime value, drive repeat purchases, and create champions for your brand.

Target shopping cart ditchers

Customers often leave your site and abandon their full shopping basket with no intention of ever returning to complete a purchase. While this might seem like a waste of time, it’s actually a great opportunity to build connections with online consumers you might never have heard from again.

First-party data can identify those who have recently abandoned shopping carts, and you can then send targeted email reminders or offers to encourage them to complete the purchase. This strategy is proven to work well, especially when an incentive like a limited-time offer is included. 

Looking to catch cart abandoners before they leave your site? Machine learning tech (like Bazaarvoice) can use first party data to identify when a shopper is likely to abandon, and intercept before they’ve made their exit.

Implement dynamic pricing

Dynamic pricing can help you maximize revenue by charging different prices to different customers at different times, optimizing based on each consumer’s willingness to pay. Determine whether this hyper-personalization strategy could benefit you by looking at first-party data like customer preferences, buying behavior, and historical purchases.

You’ll also want to take a look at competitor pricing to ensure you’re not over (or under) reaching. From here, you can adjust prices based on your customer segment and offer discounts to customer groups who would benefit from them most to encourage purchases.

Create personalized campaigns

A large part of your marketing budget is likely going toward advertising. Take your wealth of first-party data, including purchase history, browsing behavior, and demographics, and use it to create highly targeted campaigns that spark interest in your segmented groups.

For instance, a furniture retailer may target a group that has all purchased the same sectional with ads featuring a matching chair or ottoman, along with a limited-time discount if they buy it within a set time frame.

Don’t forget to test your strategies

Testing different strategies and messages based on first-party data is paramount to determining what resonates best with your audience.

Make sure to continuously refine your marketing and personalization strategies using A/B testing, and experimenting with different messaging, offers, and channels.

You can then use first-party data to measure the impact of these changes on key metrics like conversion rates, click-through rates, bounce rates, and average order value.

Examples of first-party data strategy in action

First-party data is used like any dataset to improve your products, services, revenue numbers, or processes. In the following examples, you’ll notice a common thread throughout: a strong first-party data strategy is in place, and best-practice data collection techniques are used to do a lot more than just target customers for ads or remarketing.

B2C — The slipper store

An e-commerce store selling fun and stylized slippers severed its ties with its data vendor in order to build a first-party data strategy. Upon visiting its website, users are greeted with a prompt asking for their email and phone number in exchange for a 20% off coupon. The user fills in the form and collects their discount.

During checkout, the user is then prompted to create an account to speed along the transaction and manage future purchases. The customer creates an account, enters their shipping and billing information, and completes the transaction. The e-commerce store now has some data points it can use to help improve its products or services.

But that’s not all: first-party data can be used to retarget and nurture leads during the sales process.

B2B — Applicant tracking software vendor

An applicant tracking software (ATS) has a new website and a blog it’s using to capture organic leads. Employees notice that while the blog itself is attracting a fair number of leads for the company, once users navigate to the rest of the website, they bounce within seconds, most never completing an action beyond clicking through a few pages.

The company’s first-party data strategy helps uncover the problem. Using a first-party data cookie and Google Analytics 4, the vendor can see the users coming in via the blog, attempting to schedule a demo with the CTA link on the homepage, and then bouncing. Upon analysis, the vendor realizes that the form isn’t opening when users click the “schedule a demo” CTA. They re-work the form but have another problem on their hands: the vendor has no way of remarketing to leads who didn’t convert.

They turn to first-party data to help. The vendor creates high-quality e-books and assets and then gates them at the bottom of their highest-performing blogs, asking for some basic customer information, such as their email and phone number. Now the vendor can send personalized email content to their leads, educating them on the benefits of ATS in their business and qualifying them for a sales conversation.

Maximize your first-party data with Bazaarvoice

E-commerce managers and brand managers who don’t embrace first-party data are living on borrowed time. Regulations such as the GDPR and CCPA, in conjunction with unanimous motions to quash third-party data and cookies, have put additional pressure on businesses, that often don’t have the time or resources to prepare for third-party data’s retirement.

An easy solution is insights and reports tools from Bazaarvoice. Rather than waste time hiring third parties, the tools help you analyze customer behavior and sentiment, build your brand, and source more reviews to diversify the voices in your first-party data strategy.

Using this insight, Lindt began giving its followers more of what they wanted. And the move paid off: The chocolate company’s website visits increased by 130%, and its clickthrough rate climbed by 178%.

As a social media manager, you’re well-acquainted with the frustration of decoding what actually resonates with your audience amidst the ongoing changes to Instagram Insights. But whatever your brand’s goal for Instagram — whether it’s to grow followers or increase sales — it’s essential to not only keep an eye on analytics but also to truly understand them.

Knowing what data to look for and how to examine it can help you reach your target audience better, post more engaging content, and develop a more effective social strategy to help you reach your goals and ROI.

This comprehensive guide will take you step by step through Instagram analytics and explain what each metric means and the significance of tracking it, so you can develop a winning Instagram strategy.

Chapters:

1. Why you should use Instagram analytics
2. How to access Instagram analytics
3. Instagram insights you can view
4. Individual post analytics
5. Instagram Stories analytics
6. Instagram product tags analytics
7. Making sense of Instagram analytics

Why you should use Instagram analytics

Instagram analytics helps marketers understand three important things:

1. People: Who’s engaging with your content?
2. Content: What content is engaging?
3. Products: Which products within that content are getting the most engagement?

When you consider these collectively — who’s viewing your posts, how your content is performing, and what value your content is driving — you’ll be able to curate your feed in a smarter way and improve your overall content strategy.

Plus, if you’re not looking at the numbers regularly, you may miss key insights and opportunities. For example, you could be posting too frequently or not enough, targeting the wrong audience, or even overlooking comments or mentions that could lead to future partnerships.

How to access Instagram analytics

Instagram analytics, which is known as Instagram Insights, is available to business profiles only. You can access analytics from your account profile in one of two ways. First you can access Insights directly from your profile by clicking “Professional dashboard.”

This brings you to a dashboard where you can access insights, tools, and other resources for your business account. To access Instagram Insights from this dashboard, click on the individual metrics at the top of the page to see more information about it. For example, if you want to look at your reach, click “Accounts reached.” 

You can also access Instagram analytics by clicking on the three horizontal lines on the top-right corner of the screen and then selecting “Insights” from the list of options. 

If you don’t have a business profile yet, follow these instructions to make the switch. If you only recently transitioned to a business profile, you may not have data available yet on Instagram Insights. Also, keep in mind that Instagram can only provide you with analytics information about posts and Stories that you published after you switched to a business profile.

Up until 2023, you could only see data from the past week. Now, you have the option to look at insights from the past seven days, 14 days, 30 days, three months, six months, 12 months, or two years.

Instagram insights you can view

When you access Instagram Insights, you’ll see three different data groups: reach, engagement, and followers. Within each group, you can dive deeper into even more data.

Accounts reached 

Under “Accounts reached,” you’ll see the total number of accounts reached and impressions made. 

• Reach: How many Instagram accounts your posts reached
• Impressions: Number of times your posts were viewed

At the top, your reach is broken down by followers and non-followers, so you can find out whether you’re effectively reaching your followers. Below that, you can also see an overview of the demographics of the audiences you’ve reached, including their city, country, age range, and gender. (You’ll be able to see a more in-depth breakdown of this information in the “Total followers” section.) 

Under the demographics, you’ll see a “Profile Activity” section. Within this section, you can see how many profile visits and external link taps were made during a specific time period. If you have email, phone number, and/or text options set up from your profile, you can also see how many times those were clicked. 

• Profile visits: Number of profile views for the week
• External link taps: Number of times someone clicked on the link in your Instagram profile
• Call button taps: Number of times your phone number or “Call Now” button was clicked
• Email button taps: Number of times users clicked the “email” button on your profile page
• Text button taps: Number of times your text button was clicked

This data in the “Profile Activity” section provides you with an overview of how your audience interacts with your brand each week. For example, if you find that profile visits and website clicks are growing, it’s clear that your audience is active and engaged with your brand. However, if these numbers remain low or even decrease, you’ll want to adjust your strategy and find new ways to get your audience involved. 

Why the “Accounts reached” tab matters

These numbers provide a good overview of how your content is performing in terms of how many people it’s reaching and how many views it’s receiving. 

You can use this data to try to discern what may have prompted a change in impressions. Perhaps you launched a new product that week, or maybe you hosted a giveaway that enticed users to share a post to increase their odds of winning.

Identifying what’s working — or not working — for your audience empowers you to improve your strategy.

Accounts engaged

When you view “Accounts engaged,” you’ll see the total number of people who have interacted with your content over a specific time period compared to the previous time period. Instagram breaks this number down by followers and non-followers.

Next, you’ll see a section for “Content interactions,” where you can see the total interactions made with your content. Under the total, your interactions are broken down by the type of interaction that people made with your posts, Stories, and Reels. 

For each post and Reel, you can see the likes, comments, saves, and shares. For Stories, you can see the replies, likes, and shares. If you hosted live videos during that time period, you can also see the comments and shares for those videos.

Why the “Accounts engaged” tab matters

Engagement with posts is important because it reveals what type of content is getting your audience’s attention, which allows you to tweak your strategy. For example, if you notice that photos that have a certain style or use a specific filter perform exceptionally well, you may use that tactic more frequently in the future.

Engagement is important for e-commerce brands to track because users who are engaging with your brand are more likely to make a purchase. So, if you have a post that has high engagement, it’s clearly resonating in some way. But can that engagement be translated to conversions? In other words, is there actual engagement with your products?

Total followers

Next is the followers tab. Under this section, you’ll find a more in-depth breakdown of your followers and their demographics. 

You can see your overall growth, including the number of people who followed and unfollowed you in a specific period of time, then compare it to the previous period. 

If you keep scrolling, you’ll find more specific demographics on your audience. You can look at the top locations of your followers by either city or country to find out where the majority of your followers are located. Then you can see the overall age range of your followers or break it down by gender. 

Lastly, you can see which times your followers are most active. Instagram breaks this down by both hours and days so you can pinpoint the best times to post your content. For example, if a majority of your followers are active on Fridays at 4:00 p.m., that’s a good time to post in your story and on your feed. 

Why the “Total followers” tab matters

This data can inform you if you’re reaching your target audience or perhaps if there’s an audience for your content or product that you weren’t previously aware of. For example, if you find your audience is in a younger age range, you may want to post to Instagram or Instagram Stories more frequently because younger demographics tend to be active on Instagram.

Once you understand more about your overall audience, you can look at individual posts to see how your content resonates.

Understanding the data

When interpreting data from Instagram analytics, it’s important to have goals in mind so you can determine if your content is accomplishing them:

• If your goal with Instagram is to build brand awareness, you’ll want to pay particular attention to metrics like your follower count, impressions, reach, and the number of likes and comments your posts receive
• If you’re trying to drive traffic to your website and you have high engagement but no profile clicks, you may want to consider ways to use your posts to entice followers to visit your profile and click

Now that you can compare Instagram data from the previous month and quarter, you can track and monitor more closely whether you’re making progress toward your goals in the long term. 

Questions to consider

Is your follower count growing, shrinking, or remaining stagnant? While some fluctuation in numbers is normal, if you see a sudden increase in followers, it’s worthwhile determining what led to it. Did an influential user tag you in a post? Has the type of content you’re posting changed?

Which posts receive the most impressions or have the greatest reach? Do your posts about products get a lot of attention, or do posts by micro-influencers perform better? Are users engaging with your branded content, or do one-off posts outperform them? If it’s the latter, how can you optimize branded content for engagement?

Are you reaching your target audience? Look at your audience data to determine whether you’re reaching key demographics. If not, what adjustments should you make? What audience are you already reaching, and how might this affect your brand?

How often should you post? Experiment with posting just once a day, and then try posting more often. Compare the amount of engagement that you get at different posting frequencies because different audiences will have different appetites for content.

Individual post analytics

If you want to take a look at how a particular post has performed, you can easily do this by selecting the post and clicking “View insights,” as illustrated below.

Here, in addition to viewing how many likes, comments, shares, and saves a post has received, you’ll be able to delve even deeper into the post’s performance.

Once you’re in the “Post insights” dashboard, you’ll see an overview of the post’s performance. Below the overview, you’ll see headings for “Reach,” “Engagement,” and “Profile activity.” Within these sections, you’ll see how many unique Instagram accounts you reached, how many users followed you from that post, and where the post garnered impressions.

Understanding the data

Drilling down into how a specific post performed can reveal a great deal of information:

• If certain types of posts, such as product photos, lifestyle photos, or graphics, are receiving more engagement, you’ll want to post more of these and see if you can recreate that success
• If your Instagram is shoppable, you may find that close-up photos of your products get more clicks than images featuring lots of different products in a “shop this look” format

Questions to consider

Which posts are generating the most interactions? Which ones are garnering the most profile visits, website clicks, or emails? Which ones are getting the most reach and attracting new followers?

How are users finding your posts? Are they coming to your profile and viewing content from there? Or are they discovering your content through hashtags?

Instagram Stories analytics

There’s a couple of ways you can see how your Stories are performing, depending on whether you want to view data on current Stories or see historical data from Stories after a 24-hour period.

To see historical information about Stories, simply access Instagram Insights the same way: by visiting your account profile, clicking on the three horizontal lines in the top-right corner of the screen, and selecting “Insights.” Then, click on “Content you shared.”

Under the “Content you shared” section, you can narrow the insights down to just story posts and see the number of impressions your Stories received during a certain time period. For story posts, you can choose from six different time periods: the last seven days, 30 days, three months, six months, 12 months, or two years. To see how an individual story has performed, simply select it and then swipe up to reveal more in-depth data.

To access information about an active story, simply tap on the story you’re interested in and either swipe up or tap “Activity” in the lower left-hand corner. From here, you’ll be able to view a variety of data, which is outlined in the following section.

Instagram Stories metrics 

Instagram provides a lot of information about who’s watching your Instagram Stories and how those viewers are interacting with them.

Viewers and Reach

To see who viewed an individual story on your account, click the eye icon (eyecon?). This will display a complete list of every Instagram user who saw the story.

Reach shows you how many total accounts you reached with a particular story post. Under Reach, you’ll also find data for Impressions — or the number of views your story received. This is again broken down by followers and non-followers. 

Engagement 

Beneath Reach, you’ll find a section of data called Engagement, which details the number of accounts reached with an individual story. Here, you’ll find the following metrics:

• Story interactions: How many users: replied to your story, shared your story, liked your story
• Navigation: How many users: tapped back, tapped forward, tapped on your next story, exited your story (tapped the x icon, swiped to another account’s story, returned to their own feed, or closed the Instagram app)
• Product button clicks: The number of times someone visited a product page from your story and then tapped the button on the product page
• Link clicks: The number of times people clicked on a link in your story
• Sticker taps: The number of times people clicked on a hashtag, location, mention, or product sticker in your story 

Profile activity

At the bottom of your story insights dashboard, you’ll find data on your profile activity. This includes the following metrics:

• Follows: Number of users who followed your account from the story
• Profile visits: The number of times someone visited your profile from a story post

Understanding the data

The data you gather from Stories will show you how engaging these posts are for your audience.

For example, if you find that users watch your Story posts when you post behind-the-scenes updates but exit quickly when you promote products, you may determine that users want to engage with your brand but are put off by your sales tactics.

Or if you discover that certain Stories get substantially more clicks back, meaning people are watching the story again, consider what about that content is appealing to users so you can recreate it in future Story posts. When considering your Instagram Stories analytics, again, consider your goals for the platform:

• If your goal with Instagram Stories is to engage with users in a more personal way, pay attention to how many users are sharing or replying to your story posts
• If you’re using Stories to drive traffic to your website, you’ll want to see how many people are swiping up to visit the URLs you’re linking to within your posts

While Instagram now gives businesses access to Stories data from up to two years ago, it’s helpful to be able to see data for as long as you’ve been on Instagram. Having access to all of your data allows you to compare more effectively so you can pinpoint patterns and trends you see over long periods of time and adjust your content according to what resonates most with your audience. 

For what it’s worth, Bazaarvoice offers a solution to Instagram’s limited capabilities:

• Bazaarvoice’s dashboard provides unlimited access to Instagram Stories analytics — the data will never disappear
• You can schedule Instagram Stories in advance based on AI feedback to optimize views

Questions to consider

What kinds of Stories are holding your audience’s interest? Identify which of your posts get the most engagement and look into the reason those are performing so well. Do the posts with the most engagement have stickers? Do they have faces? What is it about the engaging posts that your non-engaging posts don’t have? You can also experiment with a variety of story stickers — videos, polls, Q&As, and more — to determine what works best for your brand.

At what point are users exiting your story? This information can help you develop a strategy for your story posts. For example, if you’re uploading numerous photos or videos to tell a more lengthy or complex story overall, when do viewers lose interest? Would you benefit from keeping your Stories more succinct?

What posts are enticing users to click? When you include links in your Stories, are there certain types of posts that lead to more clicks? If you’re promoting a product, are people clicking to learn more? If you’re teasing a blog post, are people swiping up to read the full post?

Instagram product tags analytics

Product tags on Instagram allow businesses to tag items for sale in both posts and Stories, making them easily shoppable. Users simply tap on the product’s picture to learn more about the item and make a purchase. This has three key benefits:

1. Allows businesses to showcase products
2. Enables businesses to drive sales directly from Instagram
3. Empowers the buyer to quickly and easily make purchases

Product tag metrics

The metrics available for product tags are essentially the same for Instagram posts or Stories, meaning you can see the engagement and reach. However, you can also see how many clicks your product has received. Here are some additional product metrics you can access via Instagram Insights:

• Product page views: The number of times your product detail pages were viewed via product tags in your feed or story post
• Product sticker taps: A metric only available in Stories — it tells you how many times people clicked on your product sticker
• Merchant tagged: Tells you when someone tags your brand in their feed or story post
• Product tagged: Tells you when someone tags your product in their feed or story post

Product launches 

Instagram also helps businesses and creators promote new products by setting up a product launch. Once you initiate a product launch, you can share an alert so people can save reminders for the launch date. You can also allow your audience to preview products ahead of the launch to drum up excitement. You can view all the insights from your product launch in Commerce Manager. 

Understanding the data

This feature provides an additional way to evaluate how your business performs on Instagram by allowing you to see which product posts generate the most interest. However, while Instagram’s native shopping feature enables you to make your account shoppable, Bazaarvoice’s shop tags feature enables you to truly maximize the value of your content by distributing it among various outlets.

Questions to consider

Which products are getting the most clicks? You may find that some of your products simply get more engagement than others. Perhaps expensive items receive fewer clicks than more affordable ones because your audience is more likely to make an impulse buy on a less costly item. Or maybe your top-selling item isn’t getting as many clicks on Instagram as a less popular item, and you need to determine why.

Which types of posts are getting the most clicks? Do your product tags perform better in posts or in Stories? Is there something specific about the post that’s getting your audience’s attention? For example, is the product photo or video appealing for a certain aesthetic reason, or is the product teased or promoted in an intriguing way?

Making sense of Instagram analytics

Clearly, there’s a great deal of analytics information available to Instagram users, and it can be challenging to know where to start when you’re first looking at all of the data and trying to make sense of it.

To help make your Instagram analytics experience easier, first consider getting verified on Instagram. Next, consider what your goals are for the platform. If you’re mostly interested in growing your audience and expanding your brand’s reach, you’ll want to focus on followers. Pay close attention to your number of followers, track how that number changes over time, and consider how your content plays a role in the increase, decrease, or stagnation of that number.

However, if you’re using Instagram for e-commerce, you’ll want to focus on other aspects of analytics and consider how you can increase sales, such as by making your Instagram easily shoppable.

Instagram Insights can only provide so much data, though. So, if you’re serious about delving into your Instagram analytics and genuinely understanding what your numbers mean, Bazaarvoice can provide you with the tools to do just that.

FEATURED RESOURCE

A practical guide for social media professionals to drive engagement and commerce

Read here

That all sounds great, but how can you possibly know what each of your current or potential customers thinks and wants? The short answer is you just need to listen to them in the spaces where you coexist — your social media channels. Social listening is the launchpad to providing value for your customers, and how you respond will determine your success.

Learn how to listen, what to listen for, the best social listening tools, and what to do with the insights from those customer conversations in our social listening guide.

Chapters:

1. What is social listening?
2. Why is social listening important?
3. What to listen for and how to respond
4. How to set up a social listening strategy
5. Social listening examples in action
6. Manage and streamline social listening with Insights and Reports

What is social listening?

Social listening is all about actively tracking and analyzing the online conversations that matter most to your brand. Whether it’s your customers, competitors, or industry buzz, social listening tunes into these discussions across social media platforms. The goal? To glean insights into customer sentiment, preferences, and emerging trends, and to pinpoint any pain points or problems that need addressing. 

Social listening goes beyond keeping your digital ear to the ground. It’s about diving deep into the data you collect from social media conversations and analyzing it to understand public perception. This involves interpreting the data to uncover patterns, sentiments, and trends. By doing so, you can anticipate market shifts, innovate in response to customer feedback, and develop targeted digital marketing campaigns. 

Take, for instance, a beauty brand that uses social listening to track discussions around skincare routines.

They notice a growing trend in conversations about natural ingredients and eco-friendly packaging. By aligning their product development and marketing strategies with these insights, the brand successfully launches a new line of eco-friendly skincare products. The result is a product line that resonates well with their target audience, leading to increased brand loyalty and sales. 

Social listening vs. social monitoring

Social monitoring is another marketing tactic related to social listening, but the two are not the same. On the one side, social media monitoring is more targeted, with the goal of directly and immediately responding to a specific occurrence, like a brand mention or customer service question or issue. Whereas social listening is more comprehensive and aims to extract insights from social discussions to inform and shape your overall brand strategy.

Employing both social listening and brand monitoring allows brands to be reactive in customer engagement and proactive in strategic planning. Let’s run with the beauty brand example. While they used social listening to uncover an emerging trend and reshape their broader brand strategy, they might simultaneously use social monitoring to quickly address a customer’s complaint about a delayed shipment, and enhance customer satisfaction. 

Why is social listening important?

Social listening allows you to understand the key factors that affect your company’s success. It helps you become an invaluable presence in your customers’ lives and a force to be reckoned with in the eyes of competitors.

Understand customer preferences

Understanding the preferences of your customers is crucial for delivering products and services that attract and retain them. Through social listening, you can discover what particular features or qualities they love about individual products, your brand presence, and services like customer support, sustainability, and delivery. 

Customer preferences can be about your brand specifically, product categories, or your industry as a whole. By actively listening to and analyzing social media conversations, you gain the ability to pinpoint specific likes and dislikes. This process enables you to fine-tune your offerings, ensuring they hit the mark with your target audience. 

Address customer dissatisfaction

Customers might not always have a great experience with your brand or products, and that’s okay — addressing customer dissatisfaction is always an opportunity for growth and improvement. As we mentioned above, from a monitoring standpoint, social media can be a customer service tool to promptly address specific concerns and complaints before they escalate. 

At the listening level, you can use these instances to uncover the underlying causes of customer dissatisfaction and gain valuable insights into common issues within your industry. 

A clothing brand might discover through social listening that a significant number of consumers are frustrated with the lack of diverse sizing options in online shopping. This insight can prompt them to reevaluate and potentially revamp their sizing options, addressing a widespread customer need, boosting the brand’s reputation, and tapping into a new customer segment. Win-win-win!

Stay ahead of emerging trends

For your brand to stay relevant, it has to be ahead of trends. Social listening essentially serves as a radar for detecting the latest fads and preferences directly from the consumers, whether it’s must-have styles, music, products, or memes. 

Tracking trending topics and hashtags allows you to keep a finger on the pulse of shifts in consumer interests and preferences, so you can adapt your social media marketing, product, and customer service strategies in real-time.

Glean valuable competitor insights

Competition is fierce out there, especially in the world of e-commerce. While the focus should be on your brand, you also need to keep an eye on your competitors, their moves, and customer perceptions about their products, marketing, and customer service. 

Social listening helps you understand the competitive landscape, identifying both the strengths and weaknesses of your rivals, so you can uncover opportunities to outperform in areas where they fall short. It’s essentially an opportunity to capitalize on their missteps by enhancing your own products or messaging in ways that directly address the gaps left by your competitors. 

Find unique collaboration opportunities

Social listening is instrumental in finding potential influencers, UGC creators, complementary brands, and industry or subject matter experts to partner with. 

These individuals and companies are often at the forefront of trends and discussions, making them ideal partners for collaborative campaigns. When reviewing the mentions, hashtags, and keywords you track, you can find active and trusted voices contributing to those conversations.

Teaming up with them on campaigns introduces your brand to new audiences in a way that feels organic. It also aligns your brand with a voice that your target audience already knows and respects. Partnerships with the right creators and brands can cut through the noise, offering the kind of authentic content that builds trust with consumers. 

Enhance brand reputation and crisis management

For all the benefits social media has, it also puts businesses in a vulnerable position. A single misinterpreted tweet can go viral and break a brand’s reputation in a split second. Keeping tabs on what’s being said helps you safeguard the brand’s image and address any potential issues that could evolve into a full-blown crisis — in such cases, a rapid response can be the difference between a minor hiccup and a major PR disaster.

Social listening serves as an early warning system, allowing you to detect and respond to negative publicity or emerging issues promptly, and remain in tune with your audience’s perceptions and expectations. 

Improve your content strategy and marketing campaigns

Social listening takes the guesswork out of what your audience is talking about, feeling, and expecting. Using these insights, you can draw inspiration to craft content that not only aligns with but also anticipates current audience interests, leading to more effective marketing efforts. 

When your content is relevant to the audience, it naturally leads to higher engagement and conversion rates, turning those casual browsers into paying customers. 

Consider a travel agency that uses social listening to gauge the mood and preferences of its audience. They notice a growing interest in domestic travel and seize the opportunity to tailor their Google ads campaigns to focus on local tourism.

This strategic pivot results in a campaign that resonates with the audience’s current desires, leading to increased bookings and a chunkier bottom line. 

What to listen for and how to respond

There’s numerous conversations about your brand, products, industry, and competitors happening on social media, so focusing on everything isn’t feasible or efficient. These key areas of discussion are a good place to start if you want to reap the benefits of social listening.

Topics of interest

Monitor trending hashtags and popular content to align your marketing with your audience’s current interests. Pay attention to current events, big cultural moments, or trending hobbies that can shape your social media presence and interactions.

How to respond: Actively participate in conversations related to the major interests of your audience. Respond to their content or create your own that repurposes relevant content you already have, shares your brand’s perspective, and connects your products to popular use cases.

which side are you on? pic.twitter.com/Q71DeZLoOj

— Swiggy (@Swiggy) July 21, 2023

Invite your audience to share their thoughts — this not only positions your brand as a thought leader but also fosters community engagement.

Personal challenges and goals

Social media is a space where people often share personal challenges and aspirations. Social listening allows businesses to tap into these conversations, gaining insights into the real-life experiences of their audience. Access to these details enables you to offer solutions, support, and products that genuinely help customers.

How to respond: Craft campaigns and messaging that highlight how your products or services can address your customers’ needs or make progress toward their goals. 

Common issues and questions about products and services

Customers frequently turn to social media to seek information and voice their questions about products and services. Identify these common questions that come up when customers tag your brand or use your branded hashtags. This allows you to not only resolve issues quickly but also create permanent solutions and resources to improve the customer experience.

How to respond: Compile and maintain a list of the common questions that arise and use those to create online resources. For example, you can include them in a Questions and Answers section on your product pages, optimize product details with pertinent info, create a Frequently Asked Questions (FAQs) website section, and create social media content that addresses FAQs. 

Need a hand? We’re here to help! @/
-Check out the official Help Center https://t.co/R0nr73NoV4

-Visit our Community Forums page for more discussions https://t.co/f8Ncnj9Hsk

-For our Server Status & more → https://t.co/ILcKyJd79n

— Adobe Care (@AdobeCare) December 9, 2022

This is also valuable information to share with your customer service team and integrate into your live chat technology to prepare answers for these common questions.

Discussions about competitors

Social listening is a nifty tool for competitor research. Follow conversations that mention or tag your main competitors to find out what customers love or dislike about them. 

For example, you might discover sales and promotions, packaging, product details, subscription services, or something else that either works well or isn’t doing the trick. Then, you can use that information to do it better or step up your game in areas where they’re beating you out. 

How to respond: Share the insights you’ve collected about your competitors with the broader marketing, sales, and product teams. Make improvements to products, services, and marketing where needed, and highlight areas where you outshine competitors in your marketing and social media content.

Brand advocates and network partners

Pay attention to the customers who rave about your products and share content about your brand. These brand advocates are the customers who showcase your products in their everyday lives. You can also keep track of other like-minded businesses with products that would interest your audience.

How to respond: Develop relationships with creators and brands that might make good partners in the future. When someone posts quality content about your brand or industry, share it on your own social networks. Initiate deeper partnerships by reaching out to customers or influencers directly to be brand ambassadors.

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A post shared by Sarah Wolak (@sarah_wolak)

Likewise, reach out to other brands to co-host a giveaway or collaborate on product packages. 

Product mentions

Track conversations that call out your specific products and categorize them based on positive and negative feedback. 

How to respond: Evaluate the feedback about your products and identify any patterns that come up. For example, you might discover multiple complaints about certain products but rave reviews about others. Share this information with your product team so they can identify how to improve products or build upon successful ones.

How to set up a social listening strategy

Social listening is like a mind-reading superpower. While monitoring certain areas of interest ad hoc is helpful, executing an intentional social listening strategy can yield far more impactful results for your brand.

1. Define your social listening goals

Start by pinpointing what you want to achieve through social listening, be it understanding customer preferences, identifying pain points, or keeping a pulse on brand awareness. 

Make sure these objectives are specific, measurable, and, most importantly, align with your broader business goals. The latter ensures that every piece of data collected and every insight gleaned serves a larger purpose and drives the brand forward. 

Establish key performance indicators (KPIs) related to your social listening goals. These could include metrics like engagement rate, sentiment analysis results, the volume of brand mentions, or specific hashtag performance. Regularly tracking these KPIs will provide you with quantifiable data to evaluate the success of your social listening efforts.

2. Choose the right social media listening tools

From sentiment analysis and trend tracking to influencer identification, social listening tools are designed to cater to different business sizes and needs. The key is to find a tool that not only aligns with your specific social listening goals but also integrates with your existing marketing strategies. 

For small e-commerce businesses, the focus might be on cost-effective tools that offer essential listening features. These tools should be user-friendly and capable of providing insights into brand mentions, customer sentiment, and emerging trends. 

On the other hand, larger businesses might require robust platforms that offer advanced analytics, CRM integration, and data analysis capabilities. These social listening tools can handle larger volumes of data and provide deeper insights, which are key for big businesses with a wider audience reach. 

3. Identify keywords and topics

This step is crucial, as it determines the scope and relevance of the insights you’ll gather. First, identify the core aspects of your brand and industry (these can range from specific product names to broader industry terms). Include variations and common misspellings to ensure comprehensive coverage. 

Depending on your goal, you might expand your keyword list to include competitor brand names and key products. Don’t forget to add buzzwords, industry trends you’re already aware of, and seasonal topics that are likely to generate conversation. For example, if you’re a home decor brand, you might track keywords related to home improvement trends, seasonal decorations, and DIY projects.

To make your tracking more actionable, categorize your keywords into different themes or topics. This categorization can help you segment the data and analyze it more effectively. You might have categories for product feedback, customer service inquiries, and general industry discussion. 

Remember, social media is dynamic, and so should your keywords and topics be. Regularly review and update your lists to reflect new products, campaigns, or shifts in industry jargon. 

4. Determine your social media listening methods

There are various approaches to social listening and different techniques for finding meaningful conversations. Each method will unveil unique insights, and your choice will depend on the goals you originally set.

Track mentions and hashtags

Use a social media management tool to track mentions of your brand and your competitors, as well as the hashtags you designate. This way, you can access conversations on your different channels in one place. 

This is a holistic way to quickly gauge public reaction to new product launches, marketing campaigns, or company news so you can adjust strategies on the fly and ensure that your brand’s messaging aligns with audience expectations and sentiments. 

Sentiment analysis

Sentiment analysis measures customers’ perception of your brand and products based on positive and negative feedback and particular opinions expressed. And Sentiment analysis AI tools leverage machine learning that includes natural language processing (NLP) to interpret conversations and determine how people feel about your brand.

This method is particularly effective in identifying areas of customer satisfaction and dissatisfaction, which are crucial for guiding strategic improvements and maintaining a positive brand image.

Trend tracking

Use your social media management tool or the specific channel’s analytics to reveal trending content and topics. For example, the TikTok Creative Center provides robust insights on trending hashtags, creators, songs, and videos over different time periods. Analytics features included in other channels like X (formerly Twitter) reveal high-volume keywords that inform what’s trending as well. 

Proactive listening

Initiate the conversation by asking your audience for questions and feedback on your social channels. Leverage engagement features like the Questions Sticker for Instagram Stories or ask your followers to respond to your posts as a comment or a video response on TikTok.

5. Analyze and interpret social listening data

This stage is where the raw data transforms into actionable insights.

Start with quantitative analysis, which involves measuring the volume of mentions, the reach of your hashtags, and the frequency of keywords. Social media analytics platforms use automation to provide you with metrics such as engagement rates, sentiment scores, and trend graphs. 

However, quantitative data only tells part of the story. Qualitative analysis is equally important. This involves reading through posts, comments, and conversations to understand the context behind the numbers. Look for recurring themes or sentiments in the discussions about your brand. Are customers consistently praising a particular aspect of your product? Are there recurring complaints or suggestions for improvement? This level of detail can provide deeper insights into customer attitudes and perceptions. 

6. Review and adapt your social listening strategy

Social media is constantly changing, so what works today might not be as effective tomorrow. Plus, your business priorities also change and your social listening needs along with them. Regularly assessing the performance of your social listening strategy keeps it relevant and effective. 

Incorporating feedback loops is also beneficial. Use the insights gained from social listening to make changes in your business, and then monitor social media to see how these changes are received. This approach ensures that your strategy is not just reactive but also proactive in shaping your brand’s presence and offerings.

Social listening examples in action

Social listening isn’t an exact science. It’s a practice that continues to evolve with many different purposes and applications. To better understand how to use the information that’s accessible to you, take a look at these social listening examples for how other professionals have done it with impactful results.

Petco’s branding and services evolution

Petco considers social media and search the “largest focus groups on the planet” and relies on signals and feedback from social to evolve their offerings. For example, during the early days of the COVID-19 pandemic, they expedited a curbside delivery program based on listening to their audience’s preferences on social. 

In addition to offering new services informed by social listening, Petco shifted their focus to be a pet health and wellness company based on the priorities of their audience. Another way Petco leverages feedback and data is by answering customer questions on their website with Questions and Answers.

This feature provides a helpful resource on relevant product pages for customers who want to learn how specific products meet the unique needs of their pets.

Nestlé Canada’s product improvements

By listening to and acting on their customers’ feedback, Nestlé Canada saved a struggling product and returned it to its former glory. The major food brand ruffled some feathers when they modified the recipe for a favorite iced tea product. Within a month of releasing the new version, customers made their complaints known on Nestle’s marketing channels and in product reviews. As a result, their sales and review ratings dropped.

These insights led to action, and Nestlé responded to the negative sentiment by reinstating the original recipe. By finding and implementing customer feedback, they restored high customer satisfaction and raised their average customer rating for the product from 1.7 to 4 stars.

Taylor Swift’s “All Too Well” (10-minute version) 

Taylor Swift is not only one of the biggest pop stars of our time but also something of a marketing genius. Social listening is definitely part of her strategy to win over fans time and time again. One example is how the 10-minute version of the fan-favorite song “All Too Well” from her album Red came about. 

After hearing reports of a 10-minute version of the song, fans took to social media to call for its release. Taylor heard these messages and ultimately decided to record and release the complete version on “Red (Taylor’s Version)” along with a music video, which won a Grammy for Best Music Video. This is a great example of Taylor listening to her audience’s requests and responding with a new product release or, in this case, a song. 

Manage and streamline social listening with analytics

Social media teams can only do so much when it comes to conducting social listening. Small teams, multiple channels to review for social conversations, and manual processes limit what’s possible. That’s why automated tools are invaluable for managing and synthesizing large amounts of data.

Bazaarvoice’s Social Analytics tools measure your performance for social media efforts, influencer marketing, and revenue reporting all in a single dashboard. Check out the full capabilities here. Or get in touch below to learn more.

Chapters:

1. What is multi-touch attribution?
2. How to collect the right data for multi-touch attribution
3. Multi-touch attribution and the customer journey
4. Types of multi-touch attribution model
5. Multi-touch attribution tools for a privacy-first world
6. Data won’t tell you everything

In a privacy-first world, legacy approaches to multi-touch attribution are neither accurate nor reliable. Ad services like Meta and Google continue to remove user-level tracking capabilities from their reports in response to regulations, and marketers who rely on third-party cookies to quantify the mid-funnel are doomed.

User-level data is less reliable than ever and low accuracy isn’t a winning start to data-driven decision-making.

So, what are data-driven marketers to do — go back to the siloed, single-touch attribution models of Web 2.0? In an omnichannel landscape where consumers interact with brands across channels prior to a conversion, single-touch attribution doesn’t make sense. An effective marketing strategy requires a cohesive set of tactics that build on each other’s efforts to create and maintain momentum in a focused direction. 

Single-touch attribution only allows marketers to look at one tactic at a time, usually in the discovery or conversion stages. Marketers who rely on single-touch attribution to understand multi-channel strategies risk myopic decision-making by ignoring critical mid-funnel tactics. Brands need a fuller picture of what’s contributing to success to make informed multi-channel decisions. 

What is multi-touch attribution?

Multi-touch attribution is a marketing model that measures every touchpoint on the customer journey by assigning a numerical value to each channel so that marketers can see the impact each touchpoint has on conversions.

The mid-funnel is hard to measure, but investing resources in quantifying the mid-funnel pays off. Mid-funnel marketing makes a brand’s acquisition efforts more successful by lifting conversion rates across multiple channels. It also smooths the path to retention by building advocacy early, improving LTV, and taking pressure off of customer acquisition. 

Multi-touch attribution — assigning value to every stage of the customer journey — is still an important framework, but today’s version is a far cry from the third-party cookie-based approach marketers used to love. 

How to collect the right data

Third-party data collected through pixels and cookies used to be the primary source of multi-touch attribution. If a marketer wanted to track user behavior across channels, devices, and platforms, they just had to add a snippet of code to their website. Traffic would get tagged with a Facebook or Google cookie automatically without the user’s consent. That cookie would follow the user around the web to watch what they did and retarget them with relevant ads. Marketers would aggregate data from third-party cookies into multi-touch attribution reports to understand user behavior and optimize customer journeys. 

Today, that same user-level data is harder to access. GDPR and CCPA prompted Google, Facebook, and other platforms to phase out third-party cookies, a move that forced marketers to abandon tried-and-true methods of multi-touch attribution. 

Data-driven marketers have started to adapt to the new analytics landscape, leveraging first-party data and zero-party data to quantify performance across the marketing funnel.

The distinction between zero-party data and first-party data is relatively new. Until recently, all data that a brand collected was considered “first-party.”

Today, first-party data refers to quantitative behaviors that a brand tracks through their interactions with customers. First-party cookies, tags, and urchin tracking modules (UTM) are the common methods consumer brands use to collect first-party data. Omnichannel retailers might also track brick-and-mortar store visits in tandem with e-commerce customers’ behavior, like cart abandonment and email clicks. GDPR-compliant cookies can replace some of the metrics marketers used to track using third-party cookies.

Using them properly requires a privacy-first strategy that asks for consent and allows users to request that their personal data be deleted.

Zero-party data refers to qualitative information a customer tells a brand voluntarily. Customer support conversations, product reviews, survey responses, and social media comments all fall under the umbrella of zero-party data. Qualitative customer data can be invaluable to a brand if leveraged properly, but finding meaningful insights in text can be challenging to marketers used to relying solely on quantitative reports.

In an era of increased regulations and phased-out tracking systems, the best consumer marketers rely on Bazaarvoice’s zero-party qualitative insights to illuminate buyer journeys and find opportunities for growth.

Multi-touch attribution and the customer journey

Using multi-touch attribution in multi-channel marketing uncovers tactics to increase conversion rate, reduce average time to purchase, and improve average order value (AOV). 

Marketing tactics don’t exist in a vacuum — they exist in a multi-channel ecosystem. Giving full credit to any one tactic through single-touch attribution, no matter where it lies in the customer journey, ignores everything else that plays a role in customer acquisition. A brand’s relationship with prospective customers in the mid-funnel is crucial to earning more business and increasing revenue.

In a multi-channel marketing landscape, multi-touch attribution is the key to understanding what’s working and why. Consider this fictional six-step purchasing journey for a $500 Dyson vacuum cleaner. 

Using first-touch attribution, a marketing team might conclude that paid search was a clear winner. But paid search isn’t the full story. Dyson might not drive as many conversions without social proof from UGC and affiliates, which first-touch attribution can’t illuminate. 

If Dyson relied only on last-touch attribution, the team might decide to build their marketing strategy on discounting — a tricky move for a premium market player. Dyson’s products are unapologetically expensive, a pricing strategy that works because of Dyson’s proprietary technology and strong brand. Heavy discounting would counteract Dyson’s brand superpowers instead of complementing them, creating a race to the bottom that nobody can win.

Multi-touch attribution gives Dyson a better understanding of their paths to conversion, which presents more options for experimentation. Since UGC is known to improve conversion rate and plays a role in their (fictional) customer journey, Dyson might decide to experiment with more UGC ads the following quarter to increase revenue.

Types of multi-touch attribution model

Consumer marketers use linear, J-shaped, inverse J-shaped, and U-shaped models to attribute performance across the customer journey.

Linear attribution gives equal weight to every stage along the customer journey and gives marketers a balanced view of the path to conversion. It gives more credit to mid-funnel tactics than other models, which can be useful when focusing on the mid-funnel for the first time. 

It’s a good starting point, but it might inflate the value of unimportant interactions and undervalue crucial tactics. Linear attribution modeling can therefore help marketers challenge their own assumptions about what works but is rarely accurate enough in the long term to work for every scenario.

A traditional J-shaped model assigns more credit to the last stages of the customer journey, while an inverse J-shaped model puts more weight on the beginning stages of a customer journey.

U-shaped models, also called position-based models, assign equal weight to first and last touch with a smaller percentage attributed to everything in between.

Let’s look at how each type of multi-touch attribution would assign value to our fictional $500 vacuum buyer’s journey.

The attribution model a brand chooses depends on their scenario, priorities, and philosophies. Teams that are focused on building discovery might use an inverse j-shaped model to understand the beginning stages of their customer journey, while teams that are focused on the mid-funnel might apply a linear model to generate insights. 

Leveraging a multi-touch attribution model in multi-channel marketing

Here’s a scenario: a children’s apparel brand wants to find growth opportunities for their e-commerce channel. 

Using first-touch attribution, the team concludes that unbranded paid search traffic has a higher average order value (AOV) than customers acquired through paid social but generates less revenue overall.

If they stopped there, the apparel brand might conclude that despite the lower volume, paid search is a better use of their time and money. That could make sense but would increase end-of-month (EOM) revenue by a relatively small margin.

Baseline EOM Revenue: $212,350

Pairing a multi-touch attribution model with a first-touch report gives the team more options. 

When they run a buyer’s journey report in Segment, the team discovers that higher-AOV buyers from paid search traffic tend to visit a testimonial page on the store in the days preceding a purchase. The page highlights reviews from happy customers and is linked on product pages. 

Since the brand is looking at performance from an acquisition standpoint, they decide to use an inverse J-shaped model to understand the path to conversion from paid search, a high-AOV customer journey. 

After comparing the relative value of each interaction to those from lower-AOV buyers’ journeys, the team decides to direct paid social traffic to the testimonial page through a retargeting campaign, which might increase AOV from that channel.

Enter Scenario B: Leverage UGC, in this case ratings and reviews, to improve AOV and get more revenue from paid social. The team hypothesizes that AOV from paid social will increase to $99 as a result of the experiment. If it works, the experiment would increase revenue by a greater increment than Scenario A. 

Baseline EOM Revenue: $212,350

Multi-touch attribution puts complementary tactics in context, giving a team what it needs to make nuanced decisions with the constraints of their market and the strengths of their organization. 

Multi-touch attribution tools for a privacy-first world

Bazaarvoice’s suite of omnichannel commerce tools is the best way to collect zero-party data. 

Hardys Wines, the UK’s #1 wine brand, uses Bazaarvoice to collect zero-party data through ratings and reviews, two of the most important contributors to a purchasing decision. After syndicating reviews across retailers through Bazaarvoice’s platform, Hardys increased their review volume by 2,300% and improved their average star rating from 4.32 to 4.59.

Since many online shoppers filter results to show products rated 4.5 stars or higher, Hardys was able to get in front of more potential customers, building revenue across multiple channels with one mid-funnel tactic. Insights & Reports inside Bazaarvoice helps brands like Hardys maximize the value of zero-party data.

Pair Bazaarvoice’s tools with an owned marketing platform like Klaviyo to collect behavioral data that complements zero-party qualitative insights. Klaviyo’s customer profiles allow brands to map buyer journeys at the user level and then deliver a personalized experience through their suite of email and marketing tools. 

Leverage aggregation tools like Segment to quantify the customer journey across channels and uncover purchasing patterns at scale. Segment integrates first-party data flows from multiple sources, connecting insights to help consumer brands understand common buyers’ journeys and attribute performance across the entire purchasing journey.

With Segment’s Linked Profiles, consumer brands can segment customers based on affinity, buying patterns, and sentiment, getting more specific with multi-touch attribution to drive engagement and loyalty.

Data won’t tell you everything

Attribution models are just that — models. Every model has flaws, vulnerabilities, and blind spots. Brands that take quantitative data at face value without leaving room for nuance, insight, and intuition incur more risk, not more safety, in their overreliance on data. 

Multi-touch attribution is not perfect — even in the days prior to GDPR, multi-touch attribution models were never an unbiased picture of reality nor a foolproof blueprint for success. Every business uses a slightly different approach to marketing attribution — none are “wrong,” but all of them reflect different priorities and intrinsic biases.

Approaching multi-touch attribution like a model rather than a prescription is key to opening the door to strategic conversations and meaningful insights.

For a well-rounded view of customer behavior, pair quantitative attribution models with qualitative user data from Bazaarvoice. Ratings, reviews, and user-generated content are a goldmine of insights that consumer brands can leverage to understand their audience.

Bazaarvoice’s Insights & Reports tools equip brands with sentiment data, social analytics, and customer feedback trends to optimize the mid-funnel and improve conversion across channels.

Chapters:

1. What is agile marketing?
2. Benefits of agile marketing
3. Best practices for adopting agile marketing processes
4. Examples of agile marketing
5. Work with collaborative tools and vendors that support agility 

E-commerce marketers and leaders are taking cues from product teams to adopt leaner, more agile techniques for their marketing campaigns. In one report, 41% of marketers said they currently use agile tactics. 51% of marketers who don’t use agile tactics plan to start doing so, and most plan to adopt them in the next year.

If your team is looking to cut back on excess resources, be faster and more responsive, and cater your product and offerings to your target market, agile marketing is your answer. Let’s explore how agile techniques will change your marketing impact.

What is agile marketing?

Agile marketing is a dynamic approach that thrives on flexibility, adaptability, and iterative progress. Unlike traditional linear marketing tactics, agile marketing breaks down complex strategies into manageable, bite-sized tasks that are executed in short cycles.

This method values collaboration, open communication, and quick decision-making, ensuring your e-commerce team swiftly responds to changing market dynamics, customer feedback, and emerging trends. 

E-commerce leaders are leaning toward agile marketing tactics because they make it easier to streamline processes in a fast-paced market. Agile marketing fosters a culture of experimentation and continuous improvement that allows teams to refine their strategies based on real-time insights from their marketing campaigns. 

How agile marketing works

The agile marketing approach enables e-commerce teams to navigate competitive digital marketing landscapes with responsiveness and efficiency. There’s several components and characteristics of agile marketing that make this happen. 

• Task breakdown: Marketing strategies are divided into smaller tasks that can be completed within short timeframes, often referred to as sprints. These tasks are prioritized based on their importance and potential impact

• Sprints: These are short work cycles where teams focus on completing specific tasks and fostering collaboration and adaptability. Each sprint is a focused cycle, typically lasting one to four weeks. During a sprint, the team concentrates on completing just one specific project or task, aiming to deliver tangible results by the end of the cycle 

• Regular check-ins: Regular check-in meetings keep your team aligned. Each member provides updates on their progress, highlights any roadblocks, and discusses their immediate goals. Regular meetings ensure team alignment, quick adjustments, and open communication

• Iterative approach: Agile marketing encourages iterative processes. After each sprint, the team reviews the completed tasks and gathers insights from the data and feedback. Teams learn from their successes and failures, which helps inform planning for the next sprint and allows your teams to adjust their approach based on actual results

• Data-driven insights: Agile marketing relies heavily on the constant collection and analysis of data, feedback, and trends to guide decision-making. Performance metrics, customer feedback, and market trends are monitored closely to guide decision-making and optimize strategies throughout the process 

• Responsive to change: Agile marketing embraces change as a natural part of the process. It empowers teams to be proactive in addressing shifts in the market, customer behavior, and internal priorities

By embracing the components of agile marketing, e-commerce teams give themselves more opportunities to improve their products and campaigns. The iterative nature of agile marketing tactics leads to campaigns and projects that are constantly being refined, resulting in more effectiveness and better results over time.

The ability to respond promptly to market shifts ensures that e-commerce teams remain at the forefront of their industry, delivering impactful campaigns and driving business success. 92% of fully agile marketing departments say their team effectively contributes to the success of their business. This number decreases to 76% for teams that are partially agile. 

Benefits of agile marketing

Agile marketing isn’t just a buzzword — it’s a game changer. By embracing agile marketing tactics, your teams will reap several benefits that will help you make a bigger impact with your campaigns.

Adaptability to market demands

Customer demands are constantly changing, and sometimes, it feels impossible to keep up. This is where agile marketing helps. Agile marketing’s core strength lies in its adaptability. If unforeseen challenges arise, your team can quickly adjust their strategies during the next sprint rather than waiting for a major planning overhaul. 

Agile marketing creates adaptability by breaking down marketing strategies into manageable tasks that can be adjusted during sprints. When teams can adjust as needed, they’ll be able to quickly pivot their efforts in response to changing market dynamics, customer behaviors, or competitive pressures.

Plus, with your daily check-ins and regular evaluations, you ensure team members stay aligned and informed about shifts in trends or consumer preferences.

Faster delivery of marketing campaigns

Getting marketing campaigns out to the public quickly is important when demand is constantly changing and competition is high. When you can quickly launch campaigns, your e-commerce teams can seize timely opportunities and respond to current trends, capturing consumer interest when it matters most.

Agile marketing achieves faster time-to-market by emphasizing the delivery of campaigns during short sprints. E-commerce teams prioritize executing and launching core elements of a marketing campaign quickly.

This approach allows teams to gather real-time feedback and insights from initial releases, leading to refinements and enhancements in all subsequent iterations.

Increased competitive advantage

Because agile marketing promotes adaptability and speed, it helps teams adjust their campaigns accordingly to resonate better with customers. Teams that engage with their audiences and incorporate feedback into their strategies create offerings that align precisely with customer needs.

This customer-centric approach boosts customer satisfaction and loyalty, helping the business stand out from all the competition. 

Best practices for adopting agile marketing practices

Agile marketing is flexible — you can start small, and you don’t have to overhaul all your marketing processes and procedures at once. Instead, use these six best practices to get your team started with agile marketing. 

1. Identify goals and areas needing improvement 

Clarity is key to delivering successful marketing campaigns. When you start by identifying clear goals and pinpointing areas that need improvement, you’ll lay a strong foundation for agile marketing success. 

Set your goals before you begin to employ agile marketing tactics. When you need to pivot or take a new approach, you’ll always be striving to meet the same common goal. 

Knowing your goals and improvement areas helps you allocate resources effectively. Agile marketing often involves short cycles of work, and having a clear idea of priorities ensures that the entire team is investing time and effort where it matters most.

Evaluate your current marketing strategy and performance. What are your strengths? Where do you notice gaps or underperformance? Look for bottlenecks in your processes or systems. For example, if there’s a certain step or stage that the team gets caught up in and delayed, identify what you could change or adjust to make things move more quickly and efficiently. 

Next, set SMART goals — Specific, Measurable, Achievable, Relevant, and Time-Bound — for your campaigns. Whether you want to boost website traffic, increase conversions, or engage a certain target audience, defining these goals and recognizing areas that need improvement help your team gain a clear sense of direction. Agile marketing tactics should then be tailored to directly address these goals and areas, making your efforts more focused and impactful.

2. Foster cross-departmental collaboration

Different departments within your organization — such as product, sales, and customer service — all have valuable insights to help create and deliver the most impactful campaigns. Collaborating with these teams ensures that your campaigns are aligned with the latest product updates, feature releases, and customer needs.

Ongoing regular meetings are key to an agile process. You should create a schedule for meetings, establish clear channels for communication between all teams, and regularly share updates, insights, and objectives to make sure everyone is on the same page. 

During these regular meetings, gather input from other teams, like sales and customer support. These teams interact directly with customers and provide insights into customer pain points and trends. You should also use these regular meetings as brainstorming sessions to generate innovative campaign ideas that leverage insights from different areas of the business.

3. Prioritize delivering value early (and often)

The goal of agile marketing is to launch campaigns or components quickly to provide value to your audience rather than trying to make everything perfect before you release it. 

Waiting for perfection can lead to delays, missed opportunities, and excessive resources spent on minor details. With an agile approach, you’ll prioritize launching versions of campaigns sooner and more frequently, so you can engage with your audience right away and implement feedback faster.

This approach not only prevents the waste of valuable assets but also enables you to pivot in case a campaign doesn’t resonate with your intended audience. 

The first step in delivering value early and often is identifying the essential elements of your campaign that provide value to your audience. These could be key messages, unique features, or benefits that you already know resonate with your target customers.

Then you can work on developing a minimum viable version of your campaign with these core elements. Remember, it doesn’t need to be perfect. Instead, focus on delivering the most value to your audience with your messaging, visuals, and benefits.

By delivering value early and often, you’re continuously learning from your audience’s responses. This knowledge informs your decisions, allowing you to improve your campaign for the next iteration. 

4. Perform iterative testing 

The goal of iterative testing is to refine and optimize a campaign over time. It involves distributing the campaign, analyzing the results, learning what resonates with your target market, and making incremental changes in any newer versions. Each iteration builds upon the insights gained from the previous one.

Iterative testing involves testing multiple components within a campaign — such as messaging, visuals, and user experience — and adjusting them based on feedback. Consider starting smaller rather than testing across all platforms, channels, and mediums right away. You could start by testing copy and visuals on two or three social media platforms. Once you’ve mastered iterative testing on a smaller scale, gradually expand to other platforms and channels.

The iterative cycle of agile marketing ensures that campaigns evolve quickly so you can capitalize on trends, preferences, and customer demand before you lose relevance.

5. Create a process to collect ongoing feedback 

In agile marketing, your strategies and campaigns need to evolve alongside changing market dynamics and customer preferences. Feedback is your compass, guiding you toward what works, what doesn’t, and what your customers truly want. 

Agile marketing thrives on data-driven decision-making, and feedback is the most direct source of data you can tap into. It offers invaluable insights for making informed adjustments, optimizing campaigns, and ensuring that your marketing efforts genuinely resonate.

Make sure your business owns your listings on sites like Yelp and Google so you can collect reviews and ratings. You should also collect feedback from social platforms and online forums like Reddit or Quora. 

Once you’ve established easy, convenient places for your customers to review your products, you have to encourage them to actually leave a review. You should send out post-purchase surveys after a customer makes a purchase or interacts with your brand. Ask about their experience, satisfaction level, and areas where you could improve their journey. 

You can also try incorporating rating scales in your communication touchpoints. These could be in email signatures, on your website, or in post-purchase follow-up messages. Customers can quickly rate their experience on a scale, providing you with valuable quantitative feedback.

6. Use data to implement effective changes

Using both quantitative and qualitative data empowers you to navigate the evolving e-commerce landscape with precision. It’s about transforming assumptions into certainties, intuition into strategy, and reactions into responses.

By analyzing patterns, trends, and insights, you can pinpoint exactly where your efforts are paying off and where improvements are needed. This approach provides a solid foundation for iterative testing and ensures your strategies are aligned with audience preferences and market shifts.

After you’ve collected quantitative and qualitative data — from reviews, online discussions, industry research, and more — analyze the data to identify recurring trends, patterns, and correlations. Then you can prioritize the data and insights. Rank feedback and other data points based on their impact and relevance. Focus on insights that align with your marketing goals and objectives.

For example, if you have constant feedback about your slow site speed and also notice that a high percentage of people tend to leave the site after just a few seconds, you should prioritize making your website load faster. 

Create a plan that allows your teams to constantly implement the appropriate changes based on data and insights. Remove bottlenecks like inaccessible knowledge or a lengthy approval process so your team can make improvements quickly and continuously. 

Examples of agile marketing 

Many companies have successful agile marketing stories that your team can learn from. These examples showcase how brands have harnessed agile tactics to navigate challenges, streamline processes, and ultimately elevate their market impact. 

Mozilla embraces agility for predictable growth

Mozilla, an open-source web browser, needed a way to make its marketing initiatives more impactful with less guesswork and inconsistency. It faced a common dilemma in marketing — lots of ideas and projects stuck due to the absence of effective processes and systems. To address these challenges, the team began working in an agile way, implementing lean practices similar to those used in product or engineering teams.

Mozilla’s adoption of agile marketing allowed it to overcome the unpredictability that often plagues marketing efforts. By implementing agile practices, it transformed its marketing team into a well-coordinated and adaptable force, enabling them to predictably contribute to business growth and respond effectively to changing market dynamics.

Fresh quickly pivots to UGC to build awareness 

Fresh, a natural cosmetics brand, faced a significant challenge in raising awareness and fostering engagement among its customers both online and offline. The company collaborated with Bazaarvoice to embrace agile marketing tactics that would reshape its customer engagement and enhance its impact.

Using Ratings & Reviews and Retail Syndication, Fresh created an enticing shopping experience while leveraging user-generated content. By capitalizing on the power of authentic feedback and visual content, Fresh improved its online engagement and customer satisfaction.

Fresh’s partnership with Bazaarvoice to adopt agile marketing tactics enabled it to overcome challenges and achieve substantial results. By emphasizing authentic user-generated content, agile decision-making, and strategic review syndication, Fresh redefined its marketing impact, enhanced customer engagement, and witnessed a remarkable revenue impact of $1.48 million.

Work with collaborative tools and vendors that support agility 

To truly harness the potential of agile marketing, it’s crucial to leverage collaborative tools and vendors that support this mindset. By adopting solutions like ratings and reviews and retail syndication offerings, you’ll streamline your processes, drive customer engagement, and scale your marketing efforts efficiently.

Bazaarvoice also has a team of experts who are here to be your personal champions. Our Client Success Directors partner closely with you, developing tailored strategies, sharing expertise, and ensuring your business achieves its goals.

With 24/7 global support, white-glove implementation, and managed services, we offer a holistic approach to help you fully capitalize on agile marketing’s potential.

FEATURED RESOURCE

A guide to user-generated content for lean marketing teams

Read here

Artificial intelligence (AI) is no longer “on the rise” or simply a passing trend — this disruptive technology is here to stay. In our 2023 AI research report, a third of people said they’d used generative AI tools. Of those folks, 55% said they’d use them again. 

According to research from McKinsey, the impact of generative AI on productivity could potentially add trillions of dollars in value to the global economy. As e-commerce leaders, there’s multiple ways it can work for us — to save time and resources and ultimately help our businesses grow. 

Chapters:

1. Three key benefits of AI marketing for e-commerce
2. How AI marketing works
3. Top applications of AI marketing
4. Drive your marketing forward with AI

Three key benefits of AI marketing for e-commerce

AI helps create smoother and more efficient internal operations that extend to the customer during the buying process. As Benj Fein, Group Project Manager at Bazaarvoice, puts it, “AI lowers the cost of your workflows so you can work faster and smarter.”

Here’s the top three key benefits. 

1. Improved marketing efficiency

AI empowers marketing teams to automate tasks so they can work smarter and achieve more significant results. Using tools with these automated capabilities takes the more time-consuming tasks off your plate, so you have time to focus on creating successful marketing campaigns and meeting company goals. 

AI lowers the cost of your workflows so you can work faster and smarter

It’s not just simple tasks that can be automated, either. E-commerce companies can employ AI to automate a lot of different marketing functions, including email campaigns, social media posts, ad targeting, and content optimization.

AI-driven tools analyze customer data and behavior to deliver personalized and timely content, streamlining processes and increasing efficiency.

2. Faster customer feedback and CX insights

When it comes to customer feedback analysis, AI achieves quicker and more detailed insights than traditional methods. Using natural language processing (NLP), AI can decipher customer experience and sentiment signals, like keywords linked to touchpoints and activities, and emotions that correlate with complaints or positive experiences.

Other tools like customer satisfaction surveys and Net Promoter Scores can’t extract this kind of nuanced data.

The CX insights that AI can unearth have a range of business benefits for marketing professionals. AI can reveal misalignment in customer pain points, expectations, and unmet needs. This information can help treat CX issues in real-time, as well as inform ongoing processes, procedures, and strategies.

For example, AI can analyze customer behavior, purchase history, and preferences which is information you can use to offer personalized recommendations. 

A better understanding of CX can improve staff training to provide better shopping experiences. This, in turn, leads to customer retention, loyalty, and long-term growth.

3. Personalized marketing messages

The use of AI in crafting targeted marketing messages has become increasingly common, offering e-commerce companies a powerful tool to streamline their communication strategies. AI uses keywords and sentiments to create highly personalized content that aligns with customer preferences.

Using the feedback and insights generated by AI, e-commerce businesses can now craft marketing messages that foster more meaningful connections with individual customers. 

A common example of this is automated A/B testing. AI can efficiently evaluate different message variations and identify the most effective ones based on real-time customer responses and engagement metrics. This iterative approach allows marketers to continuously refine their messaging strategies and deliver content that maximizes customer engagement and conversion rates.

How AI marketing works

AI e-commerce marketing uses data to assess customer behavior and intent through machine learning. AI tools can then take action by interacting with customers or providing predictions and recommendations for the appropriate business departments.

Because AI relies on data, e-commerce companies need to have data resources in place, including customer relationship management (CRM) software, campaign insights, and website data. They also need to establish goals for using AI and have internal or outsourced experts train on the technology. That way, you get the desired outcomes based on those goals. Part of AI’s capability is to automatically improve its performance with experience and management.

The companies experiencing the best results from AI are the ones that use advanced data, technology, and models in addition to core best practices. So, having an internal or third-party team dedicated to AI and data development will yield the best ROI.

Applications of AI marketing

Deloitte estimates the generative AI market will likely double every other year for the next ten years. You can capitalize on this growing trend by adopting AI for some of your marketing functions. Here’s a few common applications of AI marketing. 

Conducting keyword research

E-commerce companies can use AI to supercharge their keyword research efforts, gaining valuable insights into customer behavior and preferences.

AI augments traditional keyword research by leveraging its capabilities in NLP and data analysis. When you employ an AI-driven tool like Jasper or Surfer SEO, you can quickly process large amounts of data from search engines, websites, and social media platforms to identify relevant keywords and uncover hidden patterns in customer search behavior.

Using automation, you can uncover the words and phrases that resonate most with the target audience, enabling you to tailor your content and product offerings accordingly. This level of personalization can lead to better customer experiences and higher satisfaction. According to McKinsey, 71% of people expect brands to personalize their interactions, and 76% of people get frustrated when interactions aren’t personalized. 

AI’s ability to analyze vast data sets quickly and accurately allows for real-time keyword monitoring. This means that e-commerce companies can stay on top of emerging trends and adapt their keyword strategies promptly, maintaining a competitive edge in the fast-paced online market. 

You can incorporate these AI-generated keywords into your website copy, social media discussions, product descriptions, advertising campaigns, and more. By adding these keywords to your website copy, more potential customers will find you online.

And because the AI did the heavy lifting with the keyword research, your team has the time to engage directly with those potential customers.

Implementing voice commerce

Voice commerce refers to the ability for consumers to use voice commands for product search, discovery, and even purchasing. Globally, over four billion digital voice assistants are in use, including Apple’s Siri and Amazon’s Alexa. It’s a quick, convenient way for people to take an action — like shopping.

Voice commerce eliminates the need for manual input, which streamlines the purchasing process significantly. Users can simply say a command and the AI-powered voice assistant quickly responds with relevant product options and information. This level of convenience and speed saves valuable time for consumers, allowing them to complete purchases effortlessly, no matter where they are or what they’re doing.

Enable these digital voice assistants for your e-commerce app and website so customers can use them to browse and buy. You can register your business with Siri, Alexa, or other digital voice assistants, so customers can easily find your brand and products through voice commands on their devices. 

Creating effective advertising copy 

Use AI to craft compelling advertising messages that engage your target audience effectively. AI tools that use NLP can assess the language and tone that resonate best with your target audience. You can use these tools to make sure your ad copy aligns with your brand’s voice while appealing to their emotions and preferences. Through advanced algorithms, AI can craft unique copy that aligns with specific customer interests, boosting engagement and conversion rates.

By leveraging AI-driven data analysis, e-commerce companies gain a deeper understanding of their audience’s preferences and pain points. From there, you can use prompts with AI tools like ChatGPT to create copy that directly addresses customer needs, leading to higher relevance and resonance.

And it’s incredibly easy to do once you learn the program! You simply input customer data, such as preferences, purchase history, and social media interactions, into your AI copywriting tool. From there, the AI tool analyzes this data and generates personalized ad copy for each customer segment, highlighting relevant products and appealing to their unique style preferences.

AI tools can integrate with your existing marketing platforms, such as social media, email marketing, and website content management systems. This integration ensures a seamless data flow between your AI tool and all your other company tools.

You should also segment your audiences based on key characteristics so your AI tool can create more personalized copy for each audience. 

Improving product discovery

AI analyzes data to deliver personalized marketing messaging, especially in the shopping discovery stage. A big part of that is product recommendations on e-commerce sites, apps, and social selling channels. AI uses customers’ purchase history and other shopping behaviors, like product page views and abandoned cart items, to showcase relevant product recommendations. Personalized product recommendations are particularly helpful for those brands with extensive product catalogs.

There’s a lot of examples of how AI strengthened product discovery for large, prominent brands. IKEA leveraged Google Cloud’s Recommendations AI to create a better search experience for their customers with personalized product recommendations. Implementing this technology delivered accurate recommendations to customers in a quick, user-friendly fashion. The result was a 400% increase in relevant product recommendations, a 30% increase in click-through rate, and a 2% increase in average order value.

Better search means a better overall e-commerce experience, which the majority of consumers and website managers say leads to a high likelihood of repeat business. Not delivering relevant, helpful content to customers has consequences. Customers who can’t find one item they’re looking for will abandon their entire cart, and three out of four will give up and go to a competitor after an unsuccessful search.

Staples Canada significantly enhanced their product discovery performance with AI. With more advanced search results and personalized product recommendations, they’re able to show many more customers the products they’re looking for that also match their interests. This implementation led to a significant increase in conversion rate.

Likewise, Wayfair uses a multifaceted AI system to produce precise yet thorough search results on its e-commerce site. They train their algorithm to detect visual elements, like design features, color, material, style, and more, from customer, supplier, and rendered photos. They also manually tag their products with relevant keywords so the algorithm produces broader search results based on keywords and visual elements.

This feature led to an increased add-to-cart rate and completed purchases.

Presenting product reviews and detecting fake reviews

It’s well understood in e-commerce that product reviews are an effective tool for converting shoppers into buyers. AI can manage, organize, and display your product reviews from customers, which is essential for large-scale businesses with lots of products and reviews to wade through.

“In the purchasing stage, AI can help showcase reviews that can convince consumers to make the purchase,” says Fein. For example, Bazaarvoice’s reviews tools have a range of features powered by AI, like highlighting the most helpful reviews from a large volume of reviews and displaying them strategically throughout your e-commerce site.

AI can also scan your entire product catalog and identify items gaining traction that have few to no reviews. Fein says this automated process enables you to identify which products need review coverage or other content that adds value for customers, like visual user-generated content (UGC).

Insulated water bottle brand Takeya leveraged Bazaarvoice tools supported by AI to increase sales on their own site and their retail partner site, Target.com. They were able to display reviews for all of their products on both sites and automatically add visual UGC sourced from social media to corresponding products.

Detecting fake reviews

Ironically enough, AI can also help you detect fake reviews from bots that use AI. This allows you to remove them and protect your brand image and reputation. Consumers are much more discerning about reviews than they were several years ago — they can easily pinpoint a fake review from an authentic one. 

Using NLP, AI tools can comb through reviews on your website, social, and Google to examine the language and tone used in the text. Fake reviews often exhibit certain patterns, such as an excessively positive tone with repetitive phrases.

AI can also detect suspicious language patterns and grammar inconsistencies commonly found in fake reviews. It can compare the writing style of other reviews to look for indications of automation or bots. 

Enhancing the customer experience

A primary function of AI for marketing is to support CX teams. With the help of AI, they can handle customer interactions on a much larger scale and gain insights to refine their processes.

Chatbots

Chatbots are a classic example of AI in action. When interacting with customers, chatbots can provide personalized responses that go beyond the typical FAQ answer. A survey of high-level operations and CX professionals concluded that companies that invest in advanced conversational AI tech will reap benefits, including decreased operational costs, more productive agents, and more satisfied customers.

Conversational AI is instrumental in capturing and guiding customers during the research and discovery stage. It can quickly answer questions with live chat, enable purchasing via a chatbot, use NLP to correspond with users, and offer hands-free voice assistance. AI bots can also respond to user actions with prompts designed to inspire purchases, like validating their cart item by announcing that another customer just bought the same thing. This kind of messaging can increase conversion rates by 5x or more.

Some types of conversational or chatbot AI can also offer guidance to the human reps on the other end of the screen. They can analyze the customers’ tone and recommend different responses for the best resolution or suggest that a supervisor step in to manage the inquiry or issue.

Airlines are examples of companies that get a lot of customer service activity. And for a rapidly growing airline, that can be overwhelming. Before adopting an AI approach to customer service management, AirAsia relied on localized call centers to handle inquiries from international locations, which meant up to hour-long wait times and time zone conflicts.

To resolve this problem, AirAsia implemented a 24-hour, multilingual chatbot that could check flights, book flights, answer questions, update passenger information, and add bonus products to bookings. The ROI included a 98% wait time improvement, an 8x increase in upsells, and significant live agent relief.

Translation technology

With machine translation, NLP, and other capabilities, AI can automatically take your marketing efforts global. This is more than just translating basic small pieces of web content in other languages, which often doesn’t produce the most accurate or natural results. AI can pick up on tone and context to provide quality translation and communication on a larger scale. As with other AI applications, this doesn’t replace professional human staff but makes their job easier and more efficient.

The translation technology industry is in high demand and thriving because it can provide significant support in translating documents, software, and websites in multiple other languages. This is crucial for meeting brand, communication, and legal standards for all pertinent audiences.

Analyzing customer feedback

AI can mine through all your customer touchpoints — from website comments and messages to product reviews and social media interactions — to synthesize all kinds of customer feedback. These insights keep you up to date on any service or product issues that need resolving and let you know what customers are liking. So you can give them more of it. AI tools can organize this info by customer, making robust customer profiles by tracking positive or negative experiences, questions, product reviews, and more.

AI algorithms can understand vocabulary that expresses a range of emotions and perspectives that “can directly shape both short-term and long-term actions to retain customers,” according to Harvard Business Review. And it can deliver this analysis in real-time, so staff across departments can all be aligned on customer behavior and pain points.

Customers aren’t shy when it comes to making their grievances or exceptional experiences heard. That’s why Bazaarvoice’s customer sentiment analysis tools give you the full rundown of what customers are saying using advanced machine learning and NLP. Not only that, but our Premium Network Insights can categorize sentiment by topic and product and compare that feedback against your competitors.

Boosting efficiency and strategy optimization

AI supplies you with insights and goes the extra mile to recommend what actions to take in response. Fein considers this one of AI’s best functions. “The most effective features in AI for marketers are ones that are built with data personal to marketers, [so] the system is saving time making recommendations similar to what the marketer would choose if they had more time themselves,” he says.

An example of this is using customer reviews as a resource to inspire product and messaging improvements. The toy manufacturer KidKraft uses Bazaarvoice Insights tools to evolve their brand according to customer demand. These tools provide KidKraft with, “an automated way to understand what customers are saying about its products and see recommended actions the brand can take to improve its marketing strategy and design better products.”

This extends to social content as well. Fein says part of Bazaarvoice’s AI can, “highlight trends in your social strategy so that the content you are spending time pushing to your discovery path [is] more likely to receive engagement.” That capability includes recommending the types and timing of content that are likely to perform well based on your past content.

AI can even predict the success of partnering with different influencers. “We have AI to help estimate the value of content generated by your influencers to help you gauge the ROI of those relationships,” says Fein.

AI tools can scan product catalogs to reveal product pages that require content coverage like reviews and visual UGC to display that would enhance the product’s presentation. Customers who interact with this type of UGC on e-commerce sites are twice as likely to convert.

“AI can benefit e-commerce brands by [reducing] the amount of steps in scaling their business. When managing a full catalog and ensuring it’s properly covered in the tons of channels out there, AI can help step in and help automate some of the steps in that process,” says Fein.

Drive your marketing strategy forward with AI

Don’t you wish you could go back in time and invest in Tesla? Back when everyone else was still scoffing at the idea of a luxury electric car? Well, that’s the current situation with AI, and specifically AI marketing. Keep an eye on AI developments and grow with the technology as it evolves and expands.

And remember: AI doesn’t replace your marketing department. It complements and enhances it. here’s some examples of how top brands are using AI, for your inspiration

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Chapters:

1. Sources of customer feedback
2. Ways to analyze customer feedback data
3. Take action on your customer feedback analysis
4. Integrate customer feedback analysis into your business strategy

The information you need to grow your business already exists. It’s out there in the world — you just need to find and harness it. Your customers are already talking about your brand whether you want them to or not, and within those conversations they’re leaving valuable insights.

But to reap the benefits of customer feedback, you have to know where to collect it, how to analyze it, and what to do with it, so you can keep your customers coming back again and again. 

Sources of customer feedback

Before you can start your customer feedback analysis, you must first collect it. Customer feedback comes in many different forms. It’s important to know where to look for it to avoid missing important information about how customers feel about your business.

Reviews

Reviews offer a goldmine of information about your target audience. Within customer reviews, you’ll find genuine, unfiltered opinions shared by customers who have firsthand experience with your product.

When you analyze your reviews, you can find recurring pain points or common issues your customers are facing. These pain points serve as opportunities for improvement. Look at reviews for other similar products on the market, too, to learn what customers like and dislike about them. You can use this information to strategize improvements to your product offering based on demand. 

But how do you get customers to actually leave reviews? Make it easy and convenient for customers to leave reviews — provide clear instructions and user-friendly review platforms. You can also streamline the review process by minimizing steps and eliminating unnecessary barriers, such as requiring account creation. 

Prompt customers to leave a review while their experience is fresh in their minds so you can increase the likelihood of receiving feedback — like by sending them follow-up emails right after a customer makes a purchase. Make it convenient by including a link to your website and/or review platforms.

You can even take it one step further by including a star-rating scale within the body of the email where they can rate their customer service experience or your product with one click.

Review platforms like Yelp, Google, Tripadvisor, and industry-specific sites provide a wealth of info for your customer feedback analysis. If you want people to leave more reviews on these sites, use the direct link to your company’s page on that platform in your review request communications. Then monitor these platforms regularly to collect feedback.

Satisfaction surveys

Satisfaction surveys are an opportunity to gather detailed and specific feedback from customers. You can design the survey to ask specific questions that dig deep into customers’ experiences and expectations, allowing you to uncover valuable insights on what needs to be improved.

With a satisfaction survey, you can get more specific and targeted feedback than you can with reviews. You can ask customers’ opinions about the quality of your products, the level of customer service they received, and your brand in general. If you find commonalities in their answers on a certain topic, you can make a plan to escalate the feedback and implement changes.

For example, if your survey answers consistently show that customers aren’t happy with the quality of your product, work with your product, QA, and other teams to identify where you can improve.

To encourage customers to participate in satisfaction surveys, keep them concise. Lengthy surveys can discourage participation. Rather than asking a lot of questions, focus on a few key questions that provide the most actionable insights. 

Clearly communicate the purpose and benefits of the survey to customers. Explain how their feedback will contribute to improving products, services, or the overall customer experience and highlight that their opinions will be considered for future enhancements. If it’s within your budget, consider offering incentives or rewards to customers who complete the survey.

Use multiple channels to deliver timely surveys, so you can cater to customer preferences. Offer options such as email, SMS, website pop-ups, or mobile app notifications. For example, after their product has been delivered, send them a mobile app notification asking them to complete a survey to rate their satisfaction with your company and product.

Social media comments and messages 

Social media platforms provide your customers with a space to share their experiences, opinions, and feedback. Businesses can leverage social media comments and messages to gather customer feedback and gain valuable insights. You can use both user-generated content (UGC) — posts created by customers, including reviews, photos, videos, and testimonials related to your brand’s products or services — and responses to your own brand posts. 

Monitor the comments and interactions on UGC posts to uncover authentic customer feedback. Look for recurring themes, sentiments, and specific pain points mentioned by customers. For example, if many folks are consistently saying your clothing products tend to run small, you can bring that to your product team and work with them on a resolution like Vertbaudet did with a maternity line.

Or consider adding a sizing chart and size info to your product descriptions to help customers understand your brands’ particular measurements.  

Also, look at your own product posts and direct messages for customer feedback and, as with UGC content, search for commonalities in the commentary. 

Customer support interactions 

Customer support interactions are a valuable opportunity to gather customer feedback. These interactions, whether through phone calls, live chat, email, or support tickets, offer a direct line of communication to customers who may have questions, concerns, or suggestions. Consider implementing a workflow for logging customer feedback during these interactions so you can capture and analyze valuable insights more effectively.

Your workflow could be as simple as asking agents to document feedback in your CRM. Or you could employ a specific feedback tool that they would use during each interaction. Ask agents to include key details when documenting feedback, such as the customer’s name, contact information, date of interaction, nature of the issue or suggestion, and any additional context to give a comprehensive view of the feedback.

Regularly review and analyze the logged feedback to extract meaningful consumer insights. Look for common themes, recurring issues, or emerging trends that can inform product enhancements, identify training opportunities for support teams, or drive process improvements. 

Online forums and communities

Online platforms like Reddit and Quora allow individuals to engage in discussions, seek advice, and share their experiences with other consumers. You can tap into these online communities to gather feedback and information to improve your products and overall customer experience. 

Start by establishing a regular cadence — such as monthly or quarterly — to collect data from online forums and communities. Set aside time to search for discussions, threads, or posts related to your brand, products, or industry. You can filter through the platforms to look for mentions of your brand, products, or services. 

Document any insights you get from these platforms so you can analyze the sentiment expressed in the discussions. Use these insights to gauge customer satisfaction levels and identify areas of concern. Look for recurring themes or common issues mentioned by multiple users. This analysis can provide insights into product strengths, weaknesses, and opportunities for product enhancement.

Ways to analyze customer feedback data

There’s a few key ways to analyze feedback to get the most valuable insights. Use these tactics to get a more holistic view of your customers’ perceptions and feelings toward your brand and product. 

Key themes and trends

Categorizing and grouping customer feedback into distinct topics or clusters that share common characteristics helps you make sense of vast amounts of unstructured data, such as customer reviews, open-ended survey responses, and social media comments. 

Recognizing themes and trends in your customer feedback analysis can inform product development and enhancement strategies. By aligning product features with customer needs and desires, you’re better equipped to increase customer satisfaction and loyalty.

There’s several tools and techniques to use when you want to identify key themes and trends in customer feedback. 

• Text mining: Text-mining tools analyze unstructured text data to identify patterns and extract relevant information. Natural language processing (NLP) techniques are commonly used in text mining to identify sentiment, keywords, and themes from customer feedback

• Topic modeling: Topic modeling is an NLP technique that groups similar words or phrases into clusters, representing specific topics within the data. Algorithms like Latent Dirichlet Allocation (LDA) are used for topic modeling to uncover hidden themes

• Cluster analysis: Cluster analysis is a statistical technique used to group similar data points based on their characteristics. In customer feedback analysis, cluster analysis can be applied to groups of customers with similar feedback, enabling businesses to identify distinct customer segments

After you’ve gathered the information and categorized it, start by prioritizing themes and issues based on their frequency, impact on customer experience, and alignment with business goals. Addressing high-priority items first ensures an efficient use of resources.

Sentiment analysis

Sentiment analysis, also known as opinion mining, is the process of using data to determine the sentiment or emotion expressed in all types of customer feedback. This analysis categorizes the text as positive, negative, or neutral, providing valuable insights into customer perceptions and feelings toward a product, brand, or service. 

Sentiment analysis helps identify specific pain points and issues that customers may be facing. Businesses can use this information to prioritize improvements and address critical concerns.

To conduct this analysis, brands use automated tools that review text with NLP algorithms. Certain tools (like Bazaarvoice’s Insights & Reports ) offer specific and actionable recommendations to strengthen marketing efforts. Insights & Reports provides a holistic view of consumers’ sentiment across retail channels. With the use of automated tools, businesses can monitor customer sentiment in real time, enabling rapid responses to negative sentiment and the timely identification of emerging trends or issues.

Interpreting sentiment-analysis results involves understanding the distribution of sentiment (positive, negative, neutral) and the context in which it occurs using four key steps. 

• Segmentation: Segment the data based on relevant factors, such as product categories, customer demographics, or time periods. This allows for more granular analysis and enables targeted improvements

• Contextual analysis: Consider the context in which sentiments are expressed. Sometimes, customer feedback may appear negative but include constructive criticism that can drive positive changes

• Comparisons: Compare sentiment analysis results over different time periods or against competitors to identify trends or changes in customer perception

• Actionable insights: Translate sentiment analysis results into actionable insights. Use the information to drive product enhancements, adjust marketing strategies, and prioritize customer experience improvements

Sentiment analysis gives you valuable customer feedback insights that allow you to make data-driven decisions to strengthen your product offerings.

Quantitative analysis

This customer feedback analysis approach involves the use of metrics, key performance indicators (KPIs), and numerical data. It involves converting qualitative feedback into quantifiable data for analysis, so businesses can measure and track customer satisfaction, identify trends, and make data-backed decisions. 

Quantitative metrics allow you to compare your performance over time. This process aids in setting performance targets and monitoring progress toward achieving them. It also reduces your reliance on assumptions and intuition. It enables you to make informed choices based on concrete, data-driven evidence.

Tracking quantitative feedback effectively requires four steps.

1. Establish baseline metrics: Begin by establishing baseline metrics for customer satisfaction and other key performance indicators. These metrics serve as reference points for comparison in the future
2. Collect data regularly: Continuously collect quantitative data from customer surveys, feedback forms, and other sources. This data can include ratings, scores, and numerical responses
3. Use visualization tools: Utilize data visualization tools like charts and graphs to represent quantitative data visually. This makes it easier to spot trends and patterns over time
4. Set up tracking mechanisms: Implement tracking mechanisms to capture changes in customer sentiment and satisfaction over specific periods, such as monthly or quarterly

Create an ongoing plan to analyze the quantitative data to identify trends and changes in customer feedback. Look for improvements or declines in key metrics and investigate underlying factors.

Take action on your customer feedback analysis

Acting on customer feedback is crucial for driving product improvements, enhancing customer satisfaction, and fostering loyalty — it’s why you collect it in the first place! When a brand responds to a review, be it positive or negative, both past and future shoppers pay attention.

Prioritize feedback

When customers share urgent concerns or complaints, quick action shows that their feedback is valued and taken seriously — 91% of shoppers say a brand should respond to social media posts the same day that they’re posted.

Failing to address critical issues promptly can lead to customer frustration, negative word-of-mouth, and potentially lost business. Start by creating categories for feedback based on severity and impact.

• Urgent or critical: Identify feedback that requires immediate attention, such as product defects, service outages, or safety concerns. Escalate these issues to relevant departments for immediate resolution

• High priority: Address feedback that has a significant impact on the customer experience or a considerable number of customers. These issues should be tackled promptly to prevent widespread dissatisfaction

• Medium priority: Feedback that indicates areas for improvement but may not have an immediate, severe impact can be categorized as medium priority. Plan for timely action on these issues

• Low priority: Feedback that represents minor improvements or isolated incidents can be classified as low priority. Address these issues when higher-priority concerns have already been addressed

Prioritizing your feedback lets you know if you need to escalate it to other people or departments. 

Escalate feedback

Escalating feedback becomes necessary when addressing certain issues that require cross-functional collaboration or input from specialized departments. 

• Technical issues: When customers report complex technical issues or software bugs that need involvement from the technical or development team for resolution

• Product suggestions: Feedback suggesting significant product enhancements or new features that require input from the product management team

• Legal or compliance matters: Feedback involving legal or compliance concerns that need involvement from the legal department

• High-value customers: When feedback comes from high-value or key customers, it may warrant special attention and escalation to senior management or dedicated customer relationship managers

Create a plan for escalating feedback that includes which situations need to be escalated and the proper workflow for escalating feedback. For example, if you have urgent/critical feedback, give a time frame (e.g., one to two hours) on when it needs to be escalated to a senior team member in the relevant department.

Define the channel folks should use to escalate feedback, too, whether via email, a messaging system, or a call. 

Monitor feedback-driven improvements

When feedback results in improvements or changes to your product offering, monitor these changes so you can evaluate the impact. Monitoring feedback-driven improvements helps you understand the effectiveness of your actions, assess customer sentiment post-improvement, and make data-driven decisions for further enhancements.

Establish a customer feedback loop so you can continuously improve. You can encourage customers to share feedback on the changes made. You can even follow up with customers by sending them post-implementation surveys or customer interviews to gather additional insights.

Examples of brands leveraging customer feedback analysis

Success stories can offer insights and inspiration if you’re trying to leverage feedback for your own brand. Here’s two examples of brands that used customer feedback analysis to drive results. 

Fresh uses reviews and ratings to increase engagement and revenue

Fresh, a beauty and skincare brand, faced the challenge of increasing brand awareness, building trust, and driving customer engagement to boost product sales. To address this, Fresh partnered with Bazaarvoice and used our Ratings & Reviews and Retail Syndication tools. Collecting and sharing authentic reviews across its website and partner sites helped Fresh create an inviting shopping experience that resonated with potential customers.

UGC allowed customers to gain insights into product efficacy and quality, compensating for the inability to test products physically. As a result, Fresh witnessed a remarkable 10.7% conversion rate for those engaging with UGC and experienced an astounding 7,702% increase in review volume.

This impactful feedback loop led to an overall revenue increase of $1.48 million, illustrating the power of leveraging customer feedback to drive engagement and revenue growth.

Électro Dépôt makes customer feedback central to its marketing strategy

Électro Dépôt, an online electronics retailer, successfully integrated customer feedback into its marketing strategy with the help of Bazaarvoice. To address its challenges of raising brand awareness and identifying products that fell short of premium quality standards, it established a community of engaged customers who actively shared product reviews and interacted through questions and answers.

By analyzing customer feedback, Électro Dépôt identified product strengths and areas for improvement, empowering it to provide an authentic and informative shopping experience.

The inclusion of customer reviews on product pages helped Électro Dépôt double conversion rates for reviewed products while maintaining an impressive average product satisfaction score of 4.1 out of 5.

Integrate customer feedback analysis into your business strategy

In today’s competitive marketplace, you need all of the tools in your tool belt to help you understand your customers and meet their demands. As we explore various ways to collect, analyze, and leverage customer feedback analysis, one thing is clear: data-driven decisions fueled by authentic customer insights can lead to transformative growth.

And with Bazaarvoice, you have access to unmatched solutions like Ratings & Reviews and Insights & Reports to empower your business. With our tools, you can increase your number of reviews and ratings, gain actionable intelligence, and drive profound customer engagement.

To learn more, join Caroline Macmillan, E-commerce Product Content Merchandiser at Arc’teryx, as she outlines Arc’teryx’s strategic approach to responding to customer feedback, like Q&A and reviews, in our on-demand masterclass Arc’teryx’s review strategy: Acquiring and responding to customer feedback.

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The smart marketer’s guide to finding and using customer insights

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Chapters:

1. What is marketing automation?
2. Benefits of marketing automation
3. How to implement a marketing automation strategy
4. Examples of successful marketing automation strategies
5. Prepare for big changes

The only constant in life is change — or in the e-commerce industry’s case, total digital transformation.

Marketing automation is an essential conductor of a huge range of digital operations required to meet consumer demand and the latest industry standards. Companies know they need to adopt marketing automation strategy, but many don’t know how. 

According to the McKinsey Global Survey, there’s an increase in the number of companies using automation technologies (70%), “yet few of these companies have achieved automation’s full potential.” Most respondents agree they can implement automation for some of their organizations’ tasks, but less than 20% have applied it more extensively across departments.

It will take a mindset shift and concerted effort for companies to widely introduce marketing automation. The ones that do will improve customer and employee satisfaction and ultimately grow their business. The survey respondents who had the most success with automation were the ones who made it a business priority. So, to borrow another trope, you have to go big or go home. 

Find out how to craft and execute an effective marketing automation strategy that will make your business run more smoothly, efficiently, and successfully.

What is marketing automation?

Essentially, marketing automation performs marketing tasks based on triggers. Software designed for these purposes manages tasks and stores the customer data necessary to execute and measure them. 

It’s a way to mechanize, streamline, and expedite targeted, data-driven marketing campaigns. Marketing automation can take over mechanical and repetitive day-to-day tasks from individuals, such as:

• Data visualization
• Content creation
• AI powered personalization
• Managing and segmenting email lists
• Manually launching individual social media campaigns
• Running paid ads campaigns

Automating tasks like these gives marketers and other team members space and time to focus on other priorities (that are likely a better use of their time ). 

Marketing automation is a crucial tool for delivering personalized content to customize the online shopping experience for your e-commerce site and app users. It does this by generating messages and notifications based on consumer data like website activity and purchase history.

It also provides real-time insights based on campaign results, so you can quickly and easily adjust and optimize targeting, messaging, and other details of your strategy as needed. 

Benefits of marketing automation 

Allowing digital tools to complete sometimes tedious yet impactful tasks has many benefits. Perhaps the most obvious is that your team doesn’t have to do them. You have to set up the tasks and monitor them, but the software does most of the work — and fast. Because time is money, this means the technology investment is definitely worth the saved operation costs and increased team productivity in other areas. 

Automation also enables personalized campaigns, improved targeting, lead generation, better customer experience, higher average order values (AOV) and conversions. And it provides rich customer data on demographics and behavior. 

The following chart shows the top benefits of marketing automation observed by global marketers who integrate it into their strategies. 

Regardless of these coveted outcomes, marketing automation is becoming more of a necessity for e-commerce brands and retailers to keep up with current trends and stay competitive. If you’re not automating, you’re not going to be as quick and nimble as the other guy.

How to implement a thoughtful marketing automation strategy

Before you enforce marketing automation as quickly and vigorously as possible, make a plan first. It might be tempting to forge ahead at full speed, but you need to be intentional about where and how to focus your automation efforts for the best results. 

1. Define the goals for your marketing automation strategy

Any good marketing strategy starts by defining what goals it wants to achieve, and the tactics should align with those goals. To identify your automation goals, start with the weaknesses and unmet needs in your current marketing program. That will guide all the actions you take to overcome those pain points and meet your goals, including what campaign types and channels you lean on for automation.  

Setting the goals for your marketing automation strategy will provide the “why,” which is where the real value is. This will also help you orchestrate your strategy. Orchestration means intentionally setting up the steps for automation, including the specific action that triggers each task.

Creating bandwidth and reducing task overload to prevent employee burnout is an example of a primary goal for your automation strategy. You could further refine that goal by thinking about what in particular your team is spending time on that’s keeping them from doing their best and most fulfilling work. This is already a leading goal for 78% of marketers who welcome the chance to hand off tasks to digital tools so they can devote more time to other priorities.

The need to provide online shoppers with a more personalized experience could be another important goal. In that case, you could consider automated personalization tactics — think targeted product recommendations and review request emails that feature product info and reviews based on shoppers’ website activity. 

The uses of marketing automation extend beyond marketing too, so other departments should collaborate on the best ways to leverage the tools you have. For example, SMS marketing and live chat are two automation possibilities that can provide significant support to your customer service team.

2. Decide what automation types and channels to leverage

Once you’ve established your goals, drill down on the channels that will produce the desired results. Below shows the current top channels used for marketing automation worldwide. Let’s dig deeper into the use-cases of some of these top channels.

Email marketing  

Email marketing is the top channel for automated campaigns worldwide, probably because it’s a main driver of customer acquisition and retention. Despite of what maybe some marketers think, email is still a versatile tool for sending targeted and relevant automated campaigns to customers. There’s many triggers you can program to deploy a variety of different emails. 

A big one is abandoned cart emails, prompted when a customer adds items to their online shopping cart but doesn’t follow through with the purchase. Email is also effective for generating product reviews that will encourage other shoppers to make purchases. These types of emails can increase product review volume by a whopping 4–9x. You can set a review collection email trigger for when an order has been delivered or a few days after, for example.

Social media marketing

Social media marketing is critical to the success of digital brands and retailers. Leveraging marketing automation in conjunction with social media will supercharge its results. There’s many reasons to focus on social as an automation channel. Those include: 

• Making tasks more efficient and manageable
• Increasing engagement
• Gaining more awareness of mentions and feedback about your brand
• Analyzing campaign performance

Social automation tools allow you to manage all of your different accounts in one dashboard. You can schedule posts on the days and times when most of your followers are active on each channel. You can easily follow mentions, keywords, and hashtags to find opportunities for engagement and discover customer insights about your products. And you can access analytics to measure your KPIs, like follower growth, reach, and engagement.

You can also automate certain social commerce functions to strengthen connections with your customers on social. For example, if a customer clicks the Like2Buy link in your Instagram store, you can collect their contact info to retarget them with relevant emails featuring products and promotions they would be interested in.

Certain social commerce tools will also segment your current customers on social into categories and identify new audiences based on the qualities of your current email list. 

Landing pages

The primary purposes of landing page automation are lead generation and lead nurturing. First, you build a landing page for a specific purpose, like to attract shoppers to your rewards program, monthly subscription option, or new product collection. Then, you integrate that landing page with your automation platform. Finally, you assign actions to certain triggers, for example:  

• Collecting zero-party data when a customer fills out a form
• Segmenting customers based on the product or service they’re signing up for 
• Adding subscribers to an email list 
• Adding leads to a customer relationship management (CRM) platform 
• Sending a review request email, like a welcome or FAQ email

Cross-selling and upselling

Cross-selling and upselling are fundamental marketing automation strategy tactics for increasing AOV and conversions across your e-commerce site. Product recommendations labeled with calls to action (CTAs) like “you might also like,” “people also bought,” and “based on your past orders” are examples of cross- and upselling. 

These automated prompts appear to your website visitors based on triggers like a product page visit, adding an item to a shopping cart, or a checkout page visit. Another example of an automated upsell is a CTA encouraging customers to add more to their cart to reach the minimum amount for free shipping. 

Live chat

Chatbots are a way to automate live chat on your e-commerce site and messaging platforms like Facebook Messenger and WhatsApp. Originally, the latter two were meant for personal use, but as we all know, they’ve scaled much larger to become major marketing tools for brands. An effective conversational commerce strategy can have a big business impact for e-commerce brands. 

Automating live chat gives customers and shoppers access to a chat option literally anytime since it doesn’t require a human operator. With live chat, you can provide answers to common customer questions, direct customers to the right pages according to their needs, upsell and cross-sell, and a variety of other actions.  

Automated chat is a helpful option for e-commerce companies to leverage during off-hours and to support their customer support teams. 

Quiz funnels

Marketing quizzes on your e-commerce site – a.k.a. quiz funnels – are a fun and interactive automated lead generation tool. You can create quizzes as a website pop-up or landing page to learn more about your customers, collect first-party data, and include product recommendations to increase conversions.

Some different types of quiz funnels include:

• Personal style quizzes – fitting for beauty, apparel, and interior design brands
• Product discovery quizzes for to help customers decide which products are best for their needs
• Consultation quizzes for specialized health and beauty products 

3. Select the right tools for your marketing automation strategy

Just as you need to align your automation channels to your goals, you need to match the tools you use to each channel. That will likely require using a variety of different tools with different functions. According to Gartner, the number one automation mistake is “falling in love with a single technology.” Instead, they recommend building a “toolbox of technologies that provide a more comprehensive set of capabilities to align to a flexible range of business outcomes and redesign approaches.”

Do the necessary research to find the tools that are the best fit to execute your strategy. For example, if you want to offer live chat on your e-commerce site, make sure your website platform has a chat option. If you want to focus on email and SMS marketing, you may consider a specialized tool that can do both. 

When assessing the performance of your automation tools, focus on whether or not you’re meeting or making progress toward your initial goals. Are these tools and processes delivering their intended outcomes? If not, you should modify or optimize your strategy, which is often the case when testing new technologies. 

A built-in benefit of whatever marketing automation tools you use is insights and analytics. These features allow you to track the performance of your automation campaigns. You can access a wealth of sophisticated data depending on which reporting platform you use, from customer sentiment to competitor analysis, conversions, content gaps, subscriber growth, and more.

Leverage a Bazaarvoice partner for added insight. Working together with Bazaarvoice and Movable Ink, marketers can leverage real-time ratings and reviews within email in an automated way to create a relevant shopping experience for each user, and influence more purchases.

Examples of successful marketing automation strategies in action

SMBs and enterprise companies alike are finding ways to automate areas of their marketing for better efficiency and ROI. Each of the following examples demonstrates how different types of brands identified challenges that automation could solve.

Those areas of opportunity include improving online customer support and experience, simplifying processes, and scaling their business. 

Luxury retail brands and conversational commerce

Before all the chatter about digital transformations and the metaverse, luxury retail brands relied heavily on the in-store experience. Now, they have to increase their investment in online channels, and three iconic luxury brands show how to deftly wield the power of conversational commerce. 

• Louis Vuitton’s automated Virtual Assistant takes a tactful approach that’s natural, easygoing, and welcomed by its visitors. The experience guides shoppers to a quicker and more confident purchase decision by providing unique value. It’s also transparent, making it clear that it’s AI-powered while giving the user the option to connect to a real agent. 
• In addition to live website chat, Burberry offers a texting option on WhatsApp. We’re officially in the next era of customer service. Its virtual shopping assistant Lola often initiates conversations to determine the needs of each customer, then passes the mic to sales associates who can help with product recommendations, sizing advice, etc.
• Another luxury innovator in conversational commerce is Prada, which is an early adopter of WeChat to serve its Chinese market. Prada cleverly uses WeChat as a channel to share engaging video and photo content, practice social commerce, and offer the option to live chat anytime with the Prada team. 
• HSN’s marketers know how important it is to celebrate major milestones. In this campaign, HSN used their 41st birthday as an opportunity to promote app downloads via an email communication. Once the customer downloaded the app, the same creative appeared in their in-app messages promoting the exclusive app-only deals.

Minted and paid ads

Paid ads are another primary marketing channel that performs well with marketing automation. For one agency, implementing automation for paid campaigns was a “breakthrough moment.” The agency leveraged Google’s automated, cross-channel campaign dashboard, Performance Max, for the home decor and gifts company Minted. 

By automating elements of its ad strategy, the agency experienced a 55% increase in ad spend ROI, which led them to scale the same approach to other clients. Overall, managing multiple automation campaigns and tracking their results all in one place enabled them to focus on “simplifying account structures to consolidate performance data and free up more time for strategic thinking” across the agency.

Beko and email automation

Customer reviews are instrumental to the success of Beko, a leader in European home appliances. Without a reliable collection of product reviews, the brand wouldn’t have been able to successfully expand into new global markets. 

Beko’s review strategy focuses on acquiring native reviews on its main e-commerce site and then catapulting that content to retail partners. Syndicating its reviews to retail partners, especially in new markets, has resulted in “exponential sales growth.”

In order to syndicate a large volume of authentic customer reviews across different retail partners, the company needed a solid base to pull from. That’s why its native reviews are so important. Out of the 8,000+ reviews the company has accumulated, “most [are] from review request emails sent to customers after registering their appliance.”

Big moves mean big changes. Prepare accordingly. 

The more comprehensive your marketing automation strategy is, the more ROI you’ll see. The automation leaders identified in the McKinsey Global Survey “are making sweeping (rather than incremental) process changes part of their automation agenda.” That means applying automation to a diverse range of business functions across departments, not just marketing. 

Such far-reaching changes require people in different teams in the organization to adapt to new systems and processes. Your teams will need training on these technologies. In order to manage new tools effectively, they’ll need to be adept at analyzing data and insights, as well as project management. 

This shift also means refocusing efforts beyond the laborious tasks that will no longer be necessary. A top benefit of marketing automation is the freedom for employees to take on higher-level tasks and responsibilities. They’ll need the necessary support to succeed, whether that means more learning and development opportunities, a redefining of roles, or whatever will best benefit your team.

These are all important factors to consider when planning to implement a marketing automation strategy, but they’re all manageable and achievable if you prepare for them. And one way to ease the transition is with the best tools for the job.

Bazaarvoice specializes in marketing automation tools and provides the guidance and attention needed to support customers throughout the implementation process. Just saying.

Working together with Bazaarvoice and Movable Ink, marketers can leverage real-time ratings and reviews within email in an automated way to create a relevant shopping experiences for each user and to drive more purchases. Get in touch below to learn more.

The community surrounding your brand is like a best friend who always provides honest feedback, even when you don’t want it. And input from your community can be one of the most effective ways to make meaningful product improvements. By leveraging feedback, you can continuously build better products while strengthening customer relationships.

3 ways to improve products through customer feedback

Customer feedback can empower lean marketing teams to make customer-centric decisions, refine strategies, build brand loyalty, and foster innovation.

Let’s look at three strategies for harnessing customer feedback to improve your products.

1. Gauge community sentiment with social listening

With 74% of consumers using social media to guide their purchasing decisions, it’s crucial for brands to have a presence on these platforms. Don’t just observe from the sidelines – actively engage with the community to discover what people are saying about your products.

It’s normal to be totally attached to your brand, so viewing your products from an objective perspective can be hard to do. Building a strong community means taking others’ opinions seriously. Social listening provides a platform for unbiased feedback and the wake-up call you might need. Plus, customers who’ve had their voices heard are more inclined to recommend your business to others, which can significantly contribute to organic growth and expanding your customer base.

As Tony Tran writes for Hootsuite, “Your customers are telling you what they want from your brand. If you care about them, you need to take a look at the insights you might gain from social listening.”

Social listening may seem overwhelming at first, especially when sifting through negative comments. However, don’t be discouraged. Over half of global marketers use social listening to understand changing customer preferences and gain valuable insights from customer feedback.

Social listening tips for businesses

When social listening, be sure to:

• Cast a wide net, and don’t focus all your attention on one social network. Expand your reach by maintaining an active presence on multiple social media platforms. This ensures that feedback from all segments of your audience is represented and provides a more comprehensive view of their opinions on your products. Different age groups and lifestyles use platforms like TikTok and Facebook, so having a presence on both allows you to hear from a broader range of demographics

• Take action and engage with your audience every chance you get. Listening is one thing, but validating your customer’s feedback through engagement fosters a stronger relationship. A 2021 SproutSocial-sponsored report found that 70% of consumers develop a stronger bond with a brand through social media interaction. That bond will lead to more valuable feedback and loyalty

• Learn from what your competitors are doing. You can apply social listening to what your competitors are doing on social media, too. Regularly check out how they interact with their audience and gauge how differently your community behaves compared to your competition This will give you a good idea of whether your social efforts are working or could use some tweaking

Whatever the best approach for your brand, keeping an ear to the ground and taking social feedback seriously will help you deliver more value to your customers.

2. Gain customer feedback insights through at-home focus groups

At-home focus groups are a fantastic way to generate excitement while also gathering in-depth customer feedback from your customers.

An at-home focus group involves participants receiving product samples in the mail. Once they’ve experienced the product and formulated an opinion, they have the chance to volunteer their thoughts. These focus groups make a lasting impact because:

1. The customers get to keep the product sample — everyone loves free stuff!
2. Sharing feedback makes them feel seen and heard by the brand
3. They get a chance to try new products risk-free

While customer feedback on social networks can be all over the place, at-home focus groups allow you to really dig deep into your product’s positives — and flaws. Whether you survey these customers or organize a conference call with participants, you can guide the conversation to where it’s most helpful. And what’s more, receiving product samples motivates people to give quality feedback, with 45 reviews generated for every 50 product samples sent out.

Another key driver here is the interest that product sampling sparks. Consumers appreciate the generosity and feel that your brand takes their opinions seriously. This helps maintain loyalty with existing customers and creates memorable experiences for those just starting their journey with your brand.

3. Inform product improvements through negative reviews

It’s totally normal to be ecstatic about glowing reviews, but you should actually spend more time analyzing negative customer feedback. These less-than-favorable reviews will help you identify product flaws that went unnoticed during development and testing.

There’s typically no shortage of negative feedback to draw from, either. Consumers, on average, are 21% more likely to leave a review after a negative experience than a positive one. So the best move is to turn this sea of negativity into lasting improvements to your products.

If not, ignoring negative feedback can damage your brand’s reputation. Take Nintendo, for example. They’ve famously soured their standing among long-time supporters by seemingly disregarding — and in some cases even removing — products and features that customers have been vocal about wanting. Nintendo has decades of brand identity and billions in revenue to fall back on, though — most businesses aren’t so lucky.

So, while it might make sense that your main priority should be hoarding 5-star reviews so other customers see them, the opposite can be true. Constant praise won’t help you identify your shortcomings. Do you want to win 100 new customers via positive reviews or fundamentally improve your product to gain 1000s of repeat customers?

As Neil Patel says, “treat every kind of feedback you receive as a gift. It’s a free piece of information that you can use to improve and grow your business.” Basically, instead of being offended by negative feedback, think of it as a free, constant, and substantial source of insight into how you can improve. Many businesses pay top dollar for that type of guidance.

Brands that use customer feedback build loyalty

Remember, your customers are more than a source of revenue. Leveraging their feedback is crucial for product improvement because it provides valuable insights into your customers’ needs, preferences, and pain points. 

You can identify areas of improvement and make informed decisions about product enhancements by using social listening to gauge community sentiment, at-home focus groups to gain deeper insights, and negative reviews to inform key product improvements.

This iterative feedback loop helps align your products with customer expectations, enhances user experience, fosters customer loyalty, and ultimately leads to better and more customer-centric products.

Learn how to build relationships with your customers to discover what they care about in our e-book below.

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