Dashboard Templates
Segment your users by what they actually do. See who’s active, who’s a power user, and how each segment’s churn risk compares.
User segmentation is the practice of grouping users into cohorts based on shared traits or behavior, so a product or marketing team can treat different types of users differently instead of applying one strategy to everyone. In Web3 and DeFi specifically, segmentation is often behavioral, based on which actions a wallet or user has taken, rather than static attributes like geography, since onchain identity rarely maps cleanly to a single location or demographic.
Common approaches include behavior-based segmentation (what a user does), tenure-based segmentation (how long or how often they’ve been active), and value-based segmentation (how much volume or activity they generate). Formo’s User Segment dashboard uses a behavior-based approach centered on each user’s most-used feature.
What’s included
Active users: a KPI number showing the percentage of users who fired at least one custom event.
Power users: a KPI number showing the percentage of users who fired ten or more custom events.
Avg features per user: a KPI number for the average number of distinct custom events per active user.
Segment overview: a table bucketing users by their primary, most-used, custom event, covering your top eight events plus an Inactive segment.
Churn risk by segment: a table showing churn rate, the share inactive for 30 or more days, for each segment.
Segment mix by tenure: a table breaking users into Inactive, Casual, Regular, and Power tiers by event count.
Segment trends by week: a stacked chart showing how your segment mix shifts week over week.
Use this dashboard to understand who your users are by behavior, not just by chain or geography, and to spot which segments are growing, churning, or ready for re-engagement.
Frequently Asked Questions
1. What is user segmentation in Web3 analytics?
User segmentation groups users into cohorts based on shared behavior, such as which feature they use most, rather than static traits like location or chain. It helps teams tailor messaging and prioritize product work by segment.
2. What are the main types of user segmentation?
The most common types are behavioral (grouping by what users do), demographic (age, location, or other static traits), tenure-based (how long or how often someone has been active), and value-based (how much volume or activity a user generates).
3. Why is behavioral segmentation preferred for Web3 apps?
Wallet addresses don’t carry reliable demographic data, so behavioral segmentation, grouping users by what they actually do onchain or in-app, is usually more actionable than demographic segmentation for crypto and DeFi products.
4. What is DeFi user segmentation used for?
DeFi teams use segmentation to prioritize support and product work for power users, target re-engagement campaigns at at-risk segments, and understand which behaviors distinguish long-term users from one-time visitors.
5. What charts are included in the User Segment Dashboard?
Active users, Power users, and Avg features per user KPI cards, plus Segment overview, Churn risk by segment, Segment mix by tenure, and Segment trends by week tables.
6. How are segments defined in the User Segment Dashboard?
Users are grouped by their primary custom event, the single custom event fired most often, covering the top 8 events with a catch-all Inactive segment.
7. Is the User Segment Dashboard the same as segmenting by chain or country?
No. This dashboard segments by behavior, what a user actually does in the app, rather than by chain, geography, or wallet type.
8. What counts as a Power user?
Anyone who has fired ten or more custom events is classified as a Power user in the Segment mix by tenure chart.
9. How is churn risk calculated in the User Segment Dashboard?
Churn risk is the share of users in a segment whose last activity was 30 or more days before today, shown per segment in the Churn risk by segment table.
10. Who should use the User Segment Dashboard?
Growth and lifecycle marketing teams who want to treat power users differently from casual or inactive ones, and product teams tracking which behaviors correlate with churn.