What is behavioral segmentation?

Imagine walking into your favorite restaurant. The waitress greets you by name and walks you to your favorite table by the window. Without asking, she brings you your Diet Coke over ice with a lemon wedge and mentions that the daily special is vegan today since she knows your dietary restrictions. This experience is likely to feel seamless and delightful because someone has been observing your past behavior to give you the best possible experience. 

In the digital world, behavioral segmentation allows businesses to create tailored experiences by first understanding how groups of their customers interact with their websites and applications.

The more advanced you are at segmenting your users, the more you can customize your approach for each group, and the more you can drive the success metrics that matter most for your business. You can optimize your messages and user journeys for each group to keep them engaged and satisfied. And when you can gain deep insight about the behaviors of your most valuable users, it’s easier to attract more users just like them.

Grouping users by their behaviors is the clearest way to understand the value they’re getting from your product, as well as any friction they face. Any digital action can be tracked and counted as a behavior. A media site may consider every click, refresh, and share to be valuable data. A SaaS company, on the other hand, is more likely to be interested in conversions on marketing campaigns and the paths users take through their app (known as a user journey).

Product and marketing teams use behavioral segmentation to identify their most valuable groups, such as repeat visitors, power users, or high spenders. Once this group is defined, you can learn which features, factors, and content correlate with higher engagement among these groups. This surfaces new ideas for attracting more of these users and drives higher retention amongst your user base. 

For example, a fitness app might find that users who share their workouts with friends work out more frequently than the average user. You could then A/B test whether nudging users to invite friends to work out together leads them to track workouts in the app more often. 

Behavioral data allows product, analytics, marketing, and customer service teams to:

By tracking your users’ actions at every step of the funnel, you can see which behavioral segments aren’t converting and why. By identifying high- and low-performing user segments, you can optimize your product to encourage the desired behavior, leading to higher conversions overall.

When you figure out the most popular products and features among your users, you can prioritize where your team should spend their time. Ultimately, you want to keep your most valuable customers happy. By understanding their favorite features, you can continue to invest, develop, or improve products with these users clearly in mind.

Behavioral segmentation helps product teams improve UX because it allows you to identify key spots where users drop off, then troubleshoot these places in the user journey. For example, the team Kaplan Test Prep used Mixpanel user analytics to test a hypothesis—that adding a sign-on option for new users who downloaded their app would increase user numbers. The change confirmed the team’s theory and improved their conversion rates by 40 percent.

There’s a wide variety of user behaviors you can use to segment your marketing and product experience. Here’s a breakdown of the most common types.

Purchase behavior segmentation divides customers into groups based on their buying habits and purchase histories. This can include grouping based on data of who has made a purchase before, who has made repeat purchases, or who has put items in a cart they abandoned.

This data allows marketers to create more targeted and effective campaigns. For example, if you’re an ecommerce company selling luxury apparel, you might want to create a segment of customers who purchased swimwear last summer and email them offering a discount to purchase similar merchandise this summer.

Usage behavior segmentation means grouping customers based on their usage habits in an application. For example, if you discover a segment of your customer base that is very active on your desktop application but not on mobile, you could target them with in-app promotions of your mobile app to deepen usage and expand the value they’re getting from your product. 

Occasion-based segmentation involves targeting customers when they complete specific actions. Occasions can include signing up for an app, making purchases, or adopting certain features. For example, a SaaS company that sells marketing technology may decide that customers successfully launching their first campaign is a noteworthy event. The team might then create a segment for customers who’ve hit this milestone and target them with a campaign asking for reviews and testimonials, since after this occasion, customers are likely to feel positive sentiment. 

Benefit-sought segmentation means grouping customers by the specific benefit they’re hoping to unlock from using your product. For example, an ecommerce beauty brand could use past purchase data to create segments for customers interested in skincare, customers interested in cosmetics, and customers interested in anti-aging products. By delivering tailored marketing campaigns that highlight the value propositions of each, the messages are more likely to resonate and lead to purchases.

Customer journey stage segmentation is a helpful way for marketers to understand where prospects are in their buying journeys and target them accordingly. For example, if you create a “top of the funnel” segment made up of prospects who’ve read 3-5 pieces of blog content, you could target them with emails or ad campaigns that show case studies or how-to guides that take their education deeper. 

Customer loyalty segmentation is a way to segment customers based on loyalty behaviors, such as making repeat purchases and promoting your brand to others. Many brands reward their most loyal customers with exclusive access to new products or features, discounts, or event invitations. This is an effective way to deepen customer relationships, leading to more customer advocacy, which can drive referrals. Brands can also target less loyal customers with content and offers to encourage deeper engagement and build greater loyalty over time.

Engagement level segmentation groups customers based on the depth of their usage of a product. For example, you may want to create a segment of power users and roll out new features to them first to reward them for their engagement. You could also use this segment to gather valuable feedback from your most highly engaged and knowledgeable users. Similarly, you could create a segment of low-usage customers and target them with educational campaigns that reinforce the value of your product and offer step-by-step tutorials on how to get started.

Behavioral segmentation is one extremely powerful type of segmentation. However, there are many other types of segmentation worth incorporating into your overall strategy. Below, we compare the benefits and limitations of each.

Here’s a proven 5-step process to get your first segments up and running:

The first step in implementing behavioral segmentation is to get clear on your objective. When you’re starting with behavioral segmentation, it’s wise not to get bogged down by tracking too many metrics. 

Rather, pick a few key indicators to focus on, ideally ones tied to the topline KPIs you’re responsible for in your role. For example, for many freemium software companies, activity metrics such as website views and clicks can be less important than sign-ups and upgrades to premium features. 

After you’ve gotten clear on your goal, ask yourself which user behaviors are most relevant to achieve this goal. For example, if you’re a product manager promoting a freemium app, you may decide that reducing churn is your North Star metric. User behaviors to track could include monitoring monthly active users and adoption of high-value features that are known to correlate with retention. 

Next, you’ll want to make sure that the behaviors you’ve identified as contributing to your goals are being tracked in your digital analytics tool. In Mixpanel, every action that end users take in your app can be tracked as an event. Each event is associated with a time and a user by default and can be set up to track other associated properties as well, depending on your business model and needs. Having clean, consistent data is essential, so it’s well worth investing effort to set things up properly.

Next, it’s time to build reports in Mixpanel that help you segment users into cohorts based on the behaviors you’ve identified. Navigate to the Cohorts tab in the navigation bar, and click on the Create Cohort button in the top right of the screen. From here, you can build segments of users who have exhibited the behaviors you’ve identified in step 1. This can look like building a segment of ‘power users’ who log into your app each month or those who regularly use your most high-value features, and another segment of ‘churn risk’ users who aren’t MAUs and don’t use your most powerful features.

Many companies rely on data scientists and methods like SQL or BI tools to perform behavioral analytics and build segments, but this can be time-consuming, cumbersome, and require deep technical skills. With a user analytics solution like Mixpanel, you can quickly and easily build segments and take action without any technical know-how. 

Now that you’ve created a segment of customers who exhibit a shared behavior, it’s time to target them with specific messaging and offerings to ease the friction they face and provide more value. To continue our above example, this can look like sending marketing emails to inactive users with messaging about the value they’re missing out on, or sending in-app messages to users to point them towards your most high-value features. If your digital analytics platform integrates with your email marketing and ad platforms, you can target this user segment directly with emails and ads based on the behaviors they’ve shown.

It’s important to measure the impact of your targeted activities on your segments, based on both the success metrics you established at the outset. Does your marketing email bring more users into the app more regularly? Are churn-risk customers using more of your high-value features? 

As is often the case with data analytics, each question you answer successfully may lead to more questions to answer to drive the results you’re hoping for. The more you think of this process as a continuous cycle of experimentation and refinement, the more likely you are to see success with behavioral segmentation. 

The team at Lemonade, an NYC-headquartered insurance company, noticed that new users weren’t completing their sign-up process. When the team used Mixpanel’s Funnels, they discovered a sizable drop-off right after new users requested a quote. 

“We tested the placement of features, order of different sections, and even the copy,” explained Gil Sadis, Head of Product at Lemonade. After reconfiguring the sign-up experience, Gil’s team increased the number of people who viewed a quote and then purchased by 250%. (To learn more about their strategy, read Lemonade’s full case study.)

DocuSign, the global e-signature provider, largely owes its success to its viral distribution strategy. That is, the more contracts sent out on the platform, the more new users are exposed to its ease-of-use, and the more new sign-ups they drive. That’s how the company can draw in 130,000 new users every single day. Senior Product Manager Drew Ashlock was tasked with scaling the company’s user base even more. 

Since users are accustomed to DocuSign’s generous freemium features, Drew and his product team knew there were numerous opportunities to encourage free users to upgrade as they used DocuSign more. They used Mixpanel’s Funnels to track the behaviors of both paying and non-paying users. Then, they got curious about experimenting with which features they offered to each group. When Drew and team offered what were typically paid features to non-paying users, they saw a remarkable 5% lift in conversions and purchases. 

There are few techniques more powerful than behavioral segmentation for truly giving your users an experience that keeps them coming back for more. 

By identifying the places customers experience friction, you can handle objections, create new pathways, and ease their journeys. If you can master this type of analysis—and pair it with actionable steps–you’ll be well on your way to converting more customers, boosting user retention, and increasing your company’s bottom line.

For example, say the product team at a video streaming platform used a digital analytics platform to visualize their funnel and see where users drop off. Their funnel consists of three ‘events’ or user behaviors: open app, watch video, and make a purchase. 

The team could then create a segment of users who watched a video, but did not make a purchase and target them with paid ads promoting value of their paid upgrades. This is one way you can use behavioral segmentation to increase app engagement and generate more revenue.

The seven main types of behavioral segmentation are purchase behavior segmentation, usage behavior segmentation, occasion-based segmentation, benefit-sought segmentation, customer journey stage segmentation, customer loyalty segmentation, and engagement level segmentation. (For a detailed explanation of each, see above!)

Where demographic segmentation looks at a customer’s characteristics (like their age, gender, income, or geographic location) to divide them into groups, behavioral segmentation groups customers based on the actions they take (e.g., previous purchases made, pages viewed, or CTAs clicked). 

There are a wide variety of indicators that your behavioral segmentation is effective, depending on what insights you uncover and how you put them into action. If you’re a growth marketer, effective behavioral segmentation might look like better campaigns that yield more clicks, more downloads, or more purchases. If you’re a product manager, this could look like more feature adoption, more monthly active users, and a lower churn rate.

There are a wide variety of web and product analytics tools you can use for behavioral segmentation, as well as business intelligence or BI tools. Customers love Mixpanel because it allows for robust segmentation without technical knowledge.