Connect acquisition, in-game behavior, and monetization in one view. Use Google Analytics Insights to spot drop-offs, optimize live ops, and scale ROAS with confidence.
Why it matters
Benefits
Map acquisition source to in-game events like tutorial_step, level_complete, match_start, and first_purchase. Identify exactly where new players drop and which channels deliver players who reach the fun faster.
Break down D1–D30 retention by app version, OS, region, and device tier. Catch churn caused by performance regressions, balance changes, or matchmaking issues before it spreads to your entire player base.
Track purchase funnels (view_item – add_to_cart – begin_checkout – purchase) alongside rewarded/video ad engagement. Spot where payment fails, which offers convert, and how ad frequency impacts session length and churn.
Use automated insights to flag spikes and drops in key KPIs – ARPDAU, payer conversion, ad ARPDAU, session count, and event completion. React quickly with offer tuning, event extensions, or hotfixes.
Use cases
Challenge
After releasing v2.1, installs stay flat but D1 retention falls. Support tickets mention “stuck” early on, but it’s unclear if it’s UX, difficulty, or a device-specific bug.
Solution
Instrument tutorial_step events and compare completion rates by app_version, device_model, and OS. Google Analytics Insights highlights the exact step with a conversion cliff and the impacted segment, enabling a targeted fix and a quick rollback or hotfix.
Challenge
Paid campaigns drive volume, but ROAS is unstable. Some ad sets produce high install counts yet low progression and near-zero payer conversion.
Solution
Link acquisition source to downstream events – first_win, level_5_reached, day_3_return, and purchase. Build cohorts by campaign and evaluate retention and payer conversion, then shift budget toward sources with strong early progression and higher predicted LTV.
Challenge
A new battle pass and starter pack launch, but revenue doesn’t move. You suspect price points, offer placement, or currency sinks are misaligned.
Solution
Track offer_view, offer_click, purchase_attempt, purchase_success, and currency_spend by segment (new vs returning, spender tier, region). Insights surfaces which step underperforms and which cohorts respond, guiding changes to pricing, placement, and bundle composition.
More industries
FAQ
Track events that represent the player lifecycle and the core loop. For acquisition and onboarding: first_open, tutorial_step, tutorial_complete, first_win, and early progression milestones (level_3, level_5). For engagement: session_start frequency, match_start – match_end, quest_complete, and social events like party_join. For monetization: offer_view, add_to_cart, begin_checkout, purchase, refund, ad_impression, rewarded_ad_complete, and currency_spend. Pair these with parameters like app_version, device_model, region, and acquisition campaign so Insights can pinpoint which cohorts are changing and why.
Insights can flag abnormal drops in retention, session length, or key progression events after updates, balance changes, or new content releases. By slicing results by version, device, region, and player segment (new vs returning, spender tier), you can identify whether churn is driven by performance issues, difficulty spikes, matchmaking changes, or economy friction – then prioritize hotfixes or tuning where it will recover the most players.
Yes. For IAP, analyze the purchase funnel and offer performance – impressions, clicks, purchase attempts, and successes – plus post-purchase behavior like session depth and repeat purchase rate. For ads, measure ad exposure, rewarded completion rate, eCPM by placement, and ad ARPDAU. Insights helps you see trade-offs – for example, when increased ad frequency boosts short-term revenue but reduces D7 retention for non-spenders.
Use campaign tagging and integrate ad platforms so acquisition dimensions (source, medium, campaign, creative) flow into Analytics. Then build cohort reports that follow players from install to milestones such as level reached, D7 retention, payer conversion, and revenue per user. With event-based measurement, you can compare campaigns by quality – not just CPI – and optimize toward ROAS and long-term LTV.
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