At a glance: Level Analytics is a product-focused feature that provides user acquisition performance breakdown by game levels. Dissect and understand your UA metrics based on Level Play, Ad Impression, Ad Revenue and IAP Revenue at each level to enhance your game engagement, driving higher retention and LTV.
By analysing insights and signals found in your game play you can implement best practices and strategic decisions for your apps, including:
Comparing game play abandonment across countries and date period
Identifying correlation between game level and ad revenue types (e.g. Interstitial ads, Banner ads and Rewarded ads)
Pinpointing on game level with low Ad Revenue LTV or IAP LTV for A/B variant testings
1. Go to Your App > Level Analytics
Enable Cost Center’s Level Analytics once you have set up the relevant Firebase events. You can read more on Firebase tracking here.
2. Run report for countries and specific date period. You can compare the report with a different set of values for in-depth analysis, such as app version, selected countries and/or date range.
3. Choose the range of game levels to narrow down your report. This is especially useful when you want to focus on specific levels for product optimisation.
4. Once the report is generated, scroll down to the sub tabs for the charts illustrating your game performance breakdown.
Use Case: Identifying the trigger for Level 25 abandonment rate due to higher failure rate
On Level 25, Abandonment rate is recorded at 10.16% with 46 users failing this level. This could be due to a more difficult game play.
Suggestion: Evaluate Level 25’s game play complexity. Product team can then optimise it with easier mechanics to encourage level completion. You can use Cost Center’s Advanced A/B Testing for variants comparison post new version release.
Note:
Level format is only designed for numerical, sorting lexicographically i.e. 10-1 would come before 2-1. It is recommended to have level format similar to:
1001 = Chapter 1, Level 1
2003 = Chapter 2, Level 3
Our Calculation Logic
Below are the logic for the graphs within Level Analytics:
prevUserLevelSuccess = Users who successfully completed the previous level userLevelSuccess = Users who successfully completed the level
userLevelFail = Users who failed the level
userStart = Users who started the level
Completion Rate = (userLevelSuccess / userStart) * 100
Failure Rate = (userLevelFail / userStart) * 100
Continuation Rate = (userStart / prevUserLevelSuccess) * 100