Mobile App Analytics by App Studio with 30M+ Downloads

AppsFlyer is our default recommendation for most clients. It has the widest ad network integrations, strong fraud protection tools, and the most comprehensive India-market support. Adjust is a strong alternative with cleaner UI and good cost data aggregation. Branch excels for deep linking and web-to-app conversion tracking. We help you evaluate based on your tech stack and requirements.

SKAdNetwork (SKAN) is Apple's privacy-preserving attribution framework for iOS 14.5+. It replaces device-level attribution with aggregated, probabilistic signals. Setting it up correctly requires configuring conversion value maps in your MMP, defining postback windows for your campaign objectives, and adjusting UA campaign optimisation for delayed data. We handle full SKAN configuration as part of every iOS analytics engagement.

Cohort analysis groups users by install date and tracks their behaviour over time. It shows how retention, revenue, and engagement differ for users acquired in different months — letting you compare channel quality, creative performance, and seasonal effects. Cohort analysis is essential for calculating true LTV, identifying churn patterns, and attributing long-term results to specific acquisition sources.

The essential KPI stack: installs by channel (volume and trend), D1/D7/D30 retention (quality signal), session length and frequency (engagement depth), install-to-registration and install-to-purchase rates (funnel conversion), ARPU and LTV by cohort (revenue quality), and blended CPI vs. CPE (unit economics). Secondary KPIs depend on your business model — subscriptions add trial conversion and churn rate.

Store analytics (Google Play Console, App Store Connect) show organic and paid install volumes, store listing conversion rates, and keyword ranking data — but cannot attribute installs to specific ad campaigns. MMPs (AppsFlyer, Adjust, Branch) provide campaign-level attribution for paid channels, connecting installs to the specific ad, creative, and network that drove them. You need both for a complete picture.

LTV measurement requires cohort-level revenue tracking: for each install cohort, track cumulative revenue per user at D7, D30, D90, and D365. The LTV curve lets you model expected lifetime value and set CPI targets that maintain positive unit economics. For subscription apps, LTV requires tracking trial conversion, subscription length, and churn rates. We set up full cohort revenue tracking as part of every analytics engagement.

Funnel analysis tracks the conversion rate between sequential events — install → launch → registration → first key action → repeat session. Each step shows both the conversion rate and the absolute drop-off count. Typically, the biggest drop-off in mobile apps is between install and registration (often 40–60% of installs never complete registration). We instrument each step and build funnel reports in your analytics stack.

Event tracking starts with a taxonomy — a structured naming convention and parameter schema for all events you want to measure. We define the taxonomy first, then implement SDK calls at each relevant user interaction (button taps, screen views, form completions, purchases). Events are validated in real-time using MMP debug views before going live. Proper taxonomy prevents the "data lake with no useful data" problem.

A well-structured dashboard has three layers: daily health metrics (installs, DAU, revenue — anomalies trigger investigation), weekly trend metrics (retention by cohort, channel CPI, funnel conversion rates — shows trajectory), and monthly strategic metrics (LTV vs. CPA by channel, keyword footprint growth, paywall conversion — informs budget allocation). We build dashboards in your existing BI tool or set up Looker Studio connected to your MMP and store data.

Organic install share measures how many installs come from search, browse, and word-of-mouth vs. paid advertising. A healthy split for most apps is 40–60% organic. If organic share is below 30%, you're overly dependent on paid spend — improving ASO will reduce your blended CPI. If organic share is above 80%, paid channels may be underinvested. Tracking organic share monthly identifies whether your ASO investments are compounding.