The Biggest Analytics Expansion Since Launch
On March 24, 2026, Apple expanded the Analytics platform in wiki:app-store-connect with capabilities that shift the system from a top-line performance dashboard into a complete post-acquisition intelligence suite. The update introduces over 100 new metrics, cohort analysis, peer group benchmarks, and programmatic export — the most significant measurement expansion for App Store marketers since the platform's inception.
For the first time, monetization and subscription performance now lives natively inside App Store Connect. Previously, assembling a complete view of in-app purchase effectiveness, offer performance, retention curves, and churn required stitching together data from multiple dashboards, third-party attribution platforms, and internal BI systems. That fragmentation is now optional.
What Changed and What It Unlocks
Monetization and subscription reporting now covers In-App Purchase performance, offer effectiveness, subscription retention curves, and churn analysis directly within Analytics. This consolidation eliminates the need to cross-reference Sales and Trends reports with external tools for basic revenue visibility.
Cohort analysis tools allow segmentation by download date, traffic source, region, or offer start date, with time-series tracking of how those groups perform over time. If you expanded to a new region, you can now compare how long it takes users from that market to make a purchase relative to users from more established territories. These cohorts respect Apple's privacy thresholds — segments below the minimum data requirement do not appear.
Peer group benchmarks introduce two new monetization-specific measures: download-to-paid conversion and proceeds per download. These benchmarks compare your app's performance against anonymized aggregates from similar apps in your category. Values are generated using differential privacy, which protects individual app performance within the peer group. Benchmarks reflect only users who have opted in to share app analytics.
Subscription data export via API enables programmatic access to subscription reports through the Analytics Reports API, supporting offline analysis and integration into internal BI systems. This API access removes a longstanding barrier for teams that need to merge App Store subscription data with other downstream metrics.
Enhanced filtering now supports up to seven simultaneous filters applied to selected metrics, enabling far more granular segmentation without running separate queries. This depth of drill-down makes it practical to isolate specific user segments — such as users from a particular region who downloaded via a specific campaign link during a limited time window.
Apple also published a comprehensive App Store Analytics Guide in the Help section to support teams building data-driven ASO strategies with the expanded toolset.
Privacy Boundaries and Data Inclusions
Before drawing conclusions from the new metrics, especially cohorts and engagement data, it is worth confirming what the data includes and where privacy protections apply.
Engagement metrics (active devices, sessions) only reflect users who have agreed to share diagnostics and usage information. This means engagement figures represent an opted-in subset, not the full installed base.
Privacy thresholds apply across all reporting, including subscription and cohort views. Certain acquisition sources, app referrers, web referrers, and campaign links require a minimum volume of data before they appear. If a source is missing from your reports, it may be below the threshold rather than absent.
Peer group benchmarks are calculated using differential privacy to ensure individual app performance within a category remains protected. Only data from users who have opted in to share app analytics contributes to benchmark values.
Conversion rate calculations differ depending on the metric. Total Downloads combines First-Time Downloads and Redownloads. Conversion rate is calculated as total downloads divided by unique impressions. Both are meaningful, but they measure different things — deliberate selection matters when using either for optimization decisions.
These boundaries do not diminish the utility of the expanded metrics, but they do require teams to interpret the data within the context of what is actually being measured.
How This Changes Post-Acquisition Measurement
The expansion shifts App Store Connect Analytics from a narrower acquisition-focused view to a tool that tracks what happens after users arrive. For subscription apps and monetization-driven products, this closes a measurement gap that previously required integrating multiple external platforms.
Cohort visibility makes it possible to compare how different user segments perform over time without exporting raw data to a spreadsheet. If you ran a promotional campaign in a new market, you can now track that cohort's retention and monetization trajectory directly within the platform.
Peer benchmarks provide external context for internal metrics. If your download-to-paid conversion is 8%, knowing whether that is above or below the category median changes how you prioritize conversion rate optimization work. These benchmarks are not perfect — they reflect aggregated, privacy-protected data from opted-in users — but they provide a reference point that was previously unavailable.
The API export capability matters most for teams with existing BI infrastructure. Subscription data can now flow programmatically into data warehouses, enabling joins with customer support data, LTV models, and cohort retention analyses that span multiple platforms.
Paired Update: Apple Ads Insights Expansion
Apple also updated the measurement picture on the paid side with the introduction of Insights, a flexible reporting workspace inside Apple Ads. Insights provides predefined reports across campaign groups, campaigns, ad placements, keywords, and search terms, with customizable metrics, dimensions, and filters.
Performance reports cover common account structure views (Campaign Groups, Campaigns, Ad Groups, Ads, Keywords, Search Terms, Ad Placements, Country or Region), helping identify what is working and what needs attention.
Advanced reports include Impression Share views, which show competitive positioning on search terms: impression share, rank relative to other advertisers, and search term popularity in specific countries or regions. These reports help answer whether low performance is a coverage issue, a bid issue, or a relevance issue.
Reports can be edited, saved, shared to campaign groups, and exported as XLSX files. Sharing is campaign-group-level, not individual-user-level — anyone with access to the campaign group automatically gains access to shared reports.
Insights supports up to 24 months of date range for most reports, though Impression Share reports are limited to 12 weeks of data. The system enforces one time dimension per report, and certain predefined report settings (such as timezone on Impression Share reports) are fixed by report type.
The pairing of Insights (paid performance) and Analytics (store and post-acquisition performance) gives marketers a clearer view of where each tool's measurement responsibility begins and ends. Insights answers questions about campaign efficiency, placement contribution, and competitive positioning. Analytics answers questions about acquisition sources, wiki:conversion-rate trends, retention, monetization visibility, cohort behavior, and peer benchmarking.
What This Means for ASO Practitioners
The Analytics expansion does not replace external attribution platforms or full-stack analytics tools, but it reduces dependency on them for certain workflows. Teams running subscription apps, in particular, gain native visibility into metrics that previously required integrating RevenueCat, Adapty, or similar subscription infrastructure.
For ASO practitioners, the most immediate value is in cohort analysis and acquisition source visibility. You can now validate whether metadata changes, seasonal campaigns, or new market entries are producing users who behave differently over time. If a metadata experiment increases downloads but those users churn faster or monetize poorly, that signal is now visible without waiting for downstream BI reports.
Peer benchmarks provide a reality check on whether performance gaps are app-specific or category-wide. If your proceeds per download are below the peer median, that is a monetization problem. If your download-to-paid conversion is above the median but total downloads are low, that is a top-of-funnel problem. The directional clarity helps prioritize where to focus optimization effort.
The privacy boundaries mean not all questions will have answers. Small-volume acquisition sources will remain invisible. Engagement metrics will reflect opted-in users only. But within those constraints, the expanded Analytics platform provides more granular, actionable post-acquisition data than App Store Connect has ever offered.