Segment users to understand personas

Using Heap’s addUserProperties API you can pass any user-level properties to Heap, including company name, user type, or other identifying information. Additionally, many properties can be attached to anonymous users via addUserProperties, such as A/B test values, input values from unsubmitted forms, and last touch properties.

Using Segments, you can create a subset of users who match a certain profile using both user-level properties and behavioral metrics. You can filter users in two separate ways:

1. On property values using equals, does not equal, contains, does not contain, and wildcard matches (the wildcard is an asterisk) – this is generally the easiest way.
2. Add filters that include has done, has not done, and/or count of actions is <, =, > x. You can then analyze any graph, funnel, or retention view for this segment by including a filter for In Segment x or using Compare.

Using time-bounded segments to monitor active users

Heap allows you to create flexible and accurate definitions for active users. You can combine behavioral filters to create the true image of an active user (a session doesn’t necessarily mean a user is engaged)! You can also include a time range in your definition – does active mean past week, past month, all time? Once you have defined your segment, you can analyze how the number of active users changes over time. Simply graph Size of Segment or select analyze this in graph view.

This graph will show you the number of active (or in this case, hungry) users as time passes. You can see if the release of a new feature or a feature enhancement causes a spike in engagement, and investigate when you see a decrease. This will also show trends in adoption – and brings up another set of questions. Is your audience growing? Are retention rates consistent? Did something happen with another team causing a change in activity?