Cohort vs Static Analysis
why cohort analysis is important for growth hacking?
Difference between Cohort and Static group data
Cohort Group Data
- Definition: Cohort group data involves categorizing users based on shared characteristics or actions within a specific timeframe. These groups are created based on when users join or perform certain actions.
- Usage: Cohort analysis helps track and compare the behavior of users who start or perform actions at similar times. For example, a cohort might be users who installed the app in a particular week or those who made their first purchase during a specific month.
- Purpose: It helps understand how different groups of users behave or engage with the app over time. Analyzing cohorts assists in measuring retention, engagement, conversion rates, and other performance metrics relative to the user’s starting point or action.
Cohort data Examples
- New Player Onboarding: Tracking cohorts of new players to understand which onboarding experiences result in better player retention and engagement.
- Event Participation: Analyzing cohorts participating in in-game events to measure their impact on player engagement and spending behavior.
- Update Adoption: Assessing cohorts based on when players adopt new game updates to understand the impact of updates on player retention and activity.
- In-Game Purchase: Analyzing cohorts of players making their first in-game purchase to identify patterns leading to higher spending among specific player groups.
- Level Completion: Tracking cohorts based on completing specific levels to analyze the correlation between level completion and player retention.
Static Group Data:
- Definition: Static group data involves organizing users based on predefined characteristics or segments that remain constant irrespective of time or actions.
- Usage: Static group data focuses on specific user attributes like demographics (age, gender, location), interests, behavior patterns, or user types (free users vs. paying users). These groups are usually fixed and don’t change based on user actions or time.
- Purpose: It aids in understanding broader user demographics, preferences, or behavior patterns across the user base. Static group data helps in targeted marketing, personalization, and understanding the overall user base’s characteristics.
Static Data Examples
- Player Type Segmentation: Categorizing players into static groups like casual gamers, competitive gamers, or collectors to personalize game features or offers for different player types.
- Player Skill Levels: Identifying static data on player skill levels to match players with opponents of similar skill levels in multiplayer games for a balanced gaming experience.
- In-Game Currency Spending Habits: Analyzing static data on how players spend in-game currency (e.g., on power-ups, cosmetics) to optimize in-game economy and monetization strategies.
- Device Preferences: Understanding static data regarding the devices players use to optimize game performance and tailor the gaming experience to specific devices.
- Playtime Preferences: Using static data on when players are most active in the game to schedule events or updates during peak activity times for maximum player engagement.
Comparison Table of Cohort and Static Data
Example by Revenue
Here is an example of Rainbow Puzzle’s data, Revenue and DAU, on Jan. 01. 2024.
The chart reflects the revenue on Jan 01, 2024, based on static data, offering an overall view. However, by delving deeper into specific cohorts, like those who installed within particular periods, we uncover the highest-spending groups on that day. This insight allows us to target these groups for revenue enhancement strategies.
Conclusion
Typically, we rely on static data to assess overall volume and revenue. However, examining cohort data on the chart offers deeper insights into specific user groups, revealing their contribution to our product’s performance. By analyzing cohorts, we pinpoint areas requiring attention and development within our product, enabling a more targeted approach for improvement and growth.
