Overview and Use Cases

User Analysis is an advanced extension to SegmentIQ that enables user-level insights through dynamic segmentation and custom behavioral analysis. It is designed for flexible, fine-grained exploration of player behavior, making it ideal for teams looking to explore player behavior, understand user journeys, compare segments and identify what drives engagement and monetization for groups of users.

User Analysis provides premium capabilities best suited for teams that need:

• Dynamic segmentation with time-based filtering
• Custom funnel definitions with strict step logic
• Deep comparison of behavior cohorts
• Flexible event property queries and metrics calculations

Use Case Examples

Time-based segmentation: Create and analyze segments of users based on recent activities	Spent over $20 last week Completed 5+ levels within 3 days Watched more than 10 ads in a single session
Combined behavioral segments: Create and analyze segments of users based on multiple conditions	Installed from a campaign, completed onboarding and have not made a purchase Completed onboarding and triggered more than 3 in-app purchases Used a weapon and triggered an error event in the same session
Segment comparison: Make comparisons between any defined segments of users	Players who converted in the first session vs. those who didn’t
Behavioral distributions: Analyze behavior ranges across your audience	Revenue brackets (e.g. $0-$10, $10-$50, $50+) Session counts per week Ad views per user
User Lookup: Investigate the events triggered by single users	Edge case behaviors Validating support tickets Exploring anomalies in aggregate metrics

User Analysis Capabilities

User Segments	Define groups of users based on behavior, properties, and time-based criteria. Once created, segments are available across all analysis tools.
Event Analysis	Explore how segments of users engage with in-game actions over time.
Funnel Analysis	Build strict-ordered funnels to understand how users progress through a defined sequence (e.g. onboarding, monetization flows).
Retention Analysis	Measure how many users in a segment return to the app or trigger a follow-up action after an initial event.
User Comparison	Compare metrics across two or more user segments to uncover behavioral differences.
Distribution Analysis	Visualize how users are spread across ranges of values (e.g. levels, completed, items purchased, session played).
User Lookup	Investigate individual users or devices to explore event-level behavior and session histories.