What is behavioral segmentation?
Behavioral segmentation allows companies to group their users based on actions they’ve taken. For example, a business can group website visitors who clicked a link or app users who made at least one purchase. Segmentations allow teams to treat each group differently, personalizing their messaging and nudging users to buy or sign up. Segmentation is key to making products profitable.
Why is behavioral segmentation so important?
Grouping users by their behaviors gives companies the clearest possible indication as to whether they’re likely to buy or adopt their product. Whereas demographic characteristics such as age, location, or device may indicate that a user is generally a good fit for a given service, only behaviors can reveal whether that user is interested in purchasing now, next week, or next year.
Any digital action users take can count as a behavior so long as the company thinks it’s worth tracking and can track it. A news site, for instance, could consider every click, refresh, and share valuable, whereas a SaaS email marketing service could only be interested in the paths users take through the app (known as user flows).
Teams can use behavioral segmentation to identify unusually profitable groups such as habitual visitors, power users, or high-spenders. Once defined, these high-performers can be compared to the broader user population to identify meaningful, and, hopefully, predictive, differences.
A personal finance app, for instance, might find that its paying users are more likely than the average user to have enabled push alerts. The team could A/B test whether nudging non-paying users to enable push alerts leads them to pay for the service.
Behavioral data allows marketing, product, customer service, and analytics teams to make better decisions. Rather than sort users by demographics, which are imprecise, teams can group users by precise actions they’ve taken, such as abandoning a shopping cart. This allows teams to:
- Prioritize their time: Teams can identify which groups deserve their attention by analyzing their activity and behaviors. That way, teams can act on the Pareto principle—the idea that 20 percent of a company’s users are responsible for 80 percent of its revenue—to make feature adjustments that please the highest-margin customers, thereby increasing revenue with minimal effort.
- Personalize the product: Teams can adjust one product to serve different users’ needs. For example, an app for building personal websites could detect whether a user has created websites before and let them to skip the tutorial. If the user has created many websites, the team can email the user, inviting them to upgrade to a membership that gives them access to more advanced tools.
- Forecast user behaviors: While past behaviors don’t necessarily predict future ones, they do provide insights that leads to smarter decision-making. Kaplan Test Prep used Mixpanel user analytics to test a hypothesis—that adding a new sign-on option for new users who downloaded its app would increase successful sign-ups. The change confirmed their theory and improved Kaplan Test Prep’s conversion rates by 40 percent.
Behavioral segmentation examples
Lemonade increases conversions by 250 percent
The insurance company Lemonade used Mixpanel user analytics to understand why more newly acquired users weren’t completing its sign-up process. With Funnels, the team discovered a sizable drop off right after new users requested a quote. By analyzing those behaviors and gathering qualitative feedback by messaging users, the team learned that the navigation was unclear and the language was convoluted.
“We tested the placement of features, order of different sections, and even the copy,” explained Gil Sadis, Head of Product at Lemonade, in an interview. After the changes, Gil’s team increased the number of people who viewed a quote and then purchased by 250 percent.
DocuSign converted 5 percent more paid users
The global e-signature provider DocuSign used Mixpanel to track the behaviors of both paying and non-paying users and, using Mixpanel, tested which features they offered to each group. Because the team was able to see lifts in conversions and purchases when they exposed paid features to non-paid users, they settled on a more optimal feature set and increased conversions five percent—a non-trivial number for a company that attracts 130,000 unique site visitors every day.
Vente-Privee drives three billion in revenue
The French e-commerce site Vente-Privee used Mixpanel user analytics to map its user behavior across devices, so they could zero in on the visitors most likely to buy. The team realized that many of its most active users were browsing on mobile, leaving, and returning to shop on desktop. But the experience was discordant: shoppers’ saved items didn’t follow them across devices. As a result of the finding, the team decided to re-code their shopping cart to allow users to browse on mobile and purchase later—a change which increased overall sales significantly.
How to segment users by behavior
Few digital products are designed to track the behavior of individual users, so teams typically have two options: download the data into a spreadsheet or purchase a user analytics platform. Most choose the latter. Spreadsheets are cumbersome, don’t stay up-to-date, aren’t linked to other customer or marketing tools such as email platforms, and aren’t a secure way to store customer information. User analytics, on the other hand, bundle these segmentation tools as well as offer:
- An intuitive visual interface
- Integrations to pull data from the product
- Analytics and reporting tools
- Integrations to marketing and customer support tools
Whether pulling data manually or with a tool, teams must create a tracking plan, or select the events they wish to track. It’s important not to track too much, otherwise the noise from less useful data can drown out the behavioral signals.
Teams should also focus on quality, not quantity. Activity metrics such as views, visits, clicks, and taps occur frequently, but don’t necessarily indicate that something valuable has occurred. Many news sites, for example, serve users who have ad-blockers, and whose actions offer little value to the company. Instead, teams should track events and actions that can be tied back to bottom-line metrics and KPIs, such as sign-ups and revenue, to ensure the team is tracking and encouraging profitable user behaviors.
Here are a few examples of common behavioral segmentations:
- Purchasing activity
- Customer journey stage
- Product or feature interest
- Usage and flows
- Responses to satisfaction surveys
When in doubt, an easy win for teams that are new to behavioral segmentation is to establish a purchase funnel, or the steps most users take toward a purchase and look for areas where there are drop-offs, or many users exiting the app. Exiting is generally an undesirable behavior, and teams can explore that page or stage to identify why the drop off is occurring, and fix it.
Companies can use behavioral segmentation to understand users on a deeper level than demographics alone allow. Behaviors are real-time indications of whether users are on the cusp of upgrading or moments away from churning, and allow teams to adjust their product, marketing, and customer service to retain and grow their most profitable customer cohorts.
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