Acquisition Metrics: CPI, CAC, and Channel Efficiency

Acquisition metrics tell you how effectively GameOn brings new users into the funnel and at what cost. Cost Per Install (CPI) is a baseline paid metric: total ad spend divided by installs from that campaign. Customer Acquisition Cost (CAC) extends CPI by including non-ad costs (creative production, user acquisition team costs, platform fees) and dividing by the number of users acquired in a time window. Track CPI and CAC by campaign, creative, geography, ad format, and publisher to identify high-performing sources.

Channel Efficiency requires blending cost with quality: compare CAC to expected Payback Period and LTV to ensure acquisition is profitable. Use cohort analysis—track users acquired in the same week or campaign to measure retention and revenue over time. A commonly used benchmark is to aim for a payback period under 30 days for aggressive growth studios; more conservative strategies may accept 60–90 days if LTV is strong.

Beyond raw cost, measure install-to-DAU conversion and early retention (D1, D7) for each channel. High CPI with poor D1 retention indicates poor targeting or creative mismatch. Also consider organic uplift (organic installs attributed to brand or referral) and blended CPI (total spend divided by total installs including organic uplift) to evaluate marketing efficiency. Finally, track ROAS (Return on Ad Spend) at multiple windows (ROAS day7, day30) so you can stop or scale campaigns quickly based on real revenue performance rather than installs alone.

Engagement Metrics: DAU, MAU, Retention, and Session Depth

Engagement metrics show whether GameOn’s product hooks players and creates habit-forming behavior. Daily Active Users (DAU) and Monthly Active Users (MAU) are foundational: their ratio (DAU/MAU, “stickiness”) indicates how frequently users return. A stickiness of 20–30% is common for casual games; higher is better and signals daily play loops. Track DAU/MAU by platform, country, and acquisition channel to spot differences in product-market fit.

Retention is the most important early engagement KPI. Report D1, D7, and D30 retention consistently; D1 shows first-session quality, D7 captures short-term habit formation, and D30 reflects longer-term retention. Use cohort retention curves to see where drop-offs occur and test product changes to improve specific decay points. Session metrics—session length and session frequency—reveal how deeply users engage each visit. Average session length plus sessions per DAU gives total play time, which correlates with ad impressions and in-app spend opportunities.

Session depth measures specific in-game actions per session (levels completed, matches played, purchases attempted). Track conversion funnels within sessions (e.g., tutorial completion → first match → level 5 → first purchase) to identify friction. Use engagement segmentation: heavy, moderate, light users, and correlate with monetization metrics to prioritize features and marketing. Also monitor social and retention drivers: push notification open rates, event participation, and friend-invite acceptance rates—these operational engagement metrics guide retention experiments and lifecycle messaging.

Monetization Metrics: ARPDAU, LTV, Conversion Funnels, and IAP Performance

Monetization metrics translate engagement into revenue insight. ARPDAU (Average Revenue Per Daily Active User) aggregates revenue across ads, IAP, and subscriptions, normalized per DAU. ARPDAU by cohort and by acquisition source shows which users monetize best. LTV (Lifetime Value) projects future revenue from a user; cohort-based LTVs using empirical revenue curves yield more realistic predictions than simplistic assumptions. Calculate LTV for 30-, 60-, and 90-day windows and model longer horizons as needed for payback decisions.

Conversion funnels for monetization are critical: measure the percentage of users who see IAP offers, add items to cart, initiate checkout, and complete purchase. A/B test offer placement, pricing, and packaging to improve conversion rates. For ads, track eCPM by placement and format (rewarded video, interstitial, banners) and ARPDAU contribution from ads. Many successful mobile titles rely on a hybrid model: a portion of revenue from a small paying cohort combined with ad revenue from the broader user base.

Segmentation is essential: analyze ARPDAU and LTV by country, platform, cohort, and acquisition channel. High ARPDAU in one country can justify increasing CPI bids there. Monitor conversion rate of non-paying to paying users and average spend per paying user (ARPPU); small improvements in these metrics have outsized effects on overall revenue. Finally, optimize pricing and meta-economy features (timed offers, season passes, battle passes) using iterative testing, and measure impact not only on immediate spend but on retention and long-term LTV to avoid cannibalization or churn.

Product & Operational Metrics: Churn, Virality, A/B Testing, and Tech KPIs

Product and operational metrics connect product quality and growth execution. Churn, typically measured as the percentage of players who stop playing over a period, complements retention metrics. Calculate weekly and monthly churn, and analyze by cohort to determine if recent updates correlate with increased churn. A/B testing is your primary lever for improving product metrics—run controlled experiments on onboarding flows, reward rates, progression pacing, and pricing. Prioritize statistically significant tests with adequate sample sizes and guard against peeking; maintain a testing roadmap tied to key KPIs (D1 retention, D7 retention, ARPDAU).

Virality metrics quantify organic growth velocity: track invites sent per user, invite acceptance rate, and the K-factor (average invites accepted per new user times invite rate). Improve virality by reducing friction in invites, rewarding both inviter and invitee, and integrating social features that make sharing natural. Operational KPIs include technical health indicators: crash rate (crashes per DAU or per session), load time, and backend latency. High crash rates or long load times cause retention losses—set target SLOs (e.g., crash-free users >99.5%, load time <3s) and monitor across devices and OS versions.

Other operational items are release metrics (rollout failure rate, rollback frequency), support metrics (tickets per DAU, average response time), and analytics hygiene (event taxonomy coverage, percentage of sessions with complete telemetry). Combine these product and operational measurements into dashboards and weekly reviews so teams can act quickly: acquisition teams can reallocate spend, product can iterate on low-performing funnels, and engineering can prioritize reliability fixes that yield retention gains. Continuous measurement and tight experimentation loops are how incremental improvements compound into sustainable mobile growth.