The Measurement Foundation Just Got Bigger
Apple has rolled out significant updates to two core measurement systems that sit at opposite ends of the app marketing funnel. In Apple Ads, the Insights workspace now offers a flexible reporting environment across campaign groups, campaigns, ad placements, and keywords. In App Store Connect, Analytics has been expanded with more than 100 new metrics covering monetization, subscriptions, cohort behavior, and peer group benchmarks. Together, these updates give marketers a clearer view of what drives installs and what happens after acquisition — a critical shift in an environment where keyword optimization alone no longer guarantees sustained rankings.
Insights replaces the previous Custom Report Builder with a more scalable interface. The landing page shows a performance snapshot for selected campaign groups, defaulting to the last seven days but adjustable across a 24-month window. Reports are organized into two types: Performance reports cover common account views (campaign groups, campaigns, ad groups, keywords, search terms, placements, and geographies), while Advanced reports focus on competitive context — particularly Impression Share, which shows how well an app ranks against other advertisers for specific search terms in a given market.
Reports are shared by campaign group, not by individual user, which simplifies collaboration but requires attention to ownership. Anyone with access to a campaign group automatically sees shared reports. Editing someone else's report requires saving a copy; deleting a report removes access for everyone it was shared with. All reports can be exported as XLSX files, making offline analysis and cross-platform workflows straightforward.
What App Store Connect Analytics Now Unlocks
While Insights focuses on paid performance, App Store Connect Analytics now covers a much broader set of organic and monetization outcomes. The expansion includes:
- Monetization and subscription metrics — Previously scattered across multiple tools, in-app purchase and offer performance data now live inside Analytics. This brings revenue outcomes into the same system where acquisition is tracked.
- Cohort analysis — Marketers can now group users by shared attributes (download date, download source, offer start date) and track how those cohorts perform over time. This is particularly useful for comparing regional rollouts or evaluating how users acquired through different channels behave after install.
- Peer group benchmarks — Two new benchmarks (download-to-paid conversion and proceeds per download) let marketers compare their monetization performance against similar apps. These benchmarks are generated using differential privacy, which protects individual app data while still providing aggregated comparison points.
- Subscription-specific reports — Two new subscription reports are now exportable via the Analytics Reports API, enabling offline analysis or integration into custom dashboards.
- Expanded filtering — Up to seven filters can now be applied simultaneously, allowing much more granular segmentation without needing separate queries.
Privacy Thresholds and Data Boundaries to Keep in Mind
Before drawing conclusions from the new metrics — particularly cohorts, benchmarks, and engagement data — it is worth understanding what the data includes and where the limits are.
On acquisition metrics: 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.
On engagement data: Active device and session metrics only include users who have agreed to share diagnostics and usage information. This means engagement figures reflect an opted-in subset of the user base, not everyone who has the app installed.
On privacy thresholds: Certain acquisition sources, app referrers, web referrers, and campaign links require a minimum amount of data before they appear in Analytics. If a particular source is not visible, it may be below the threshold rather than absent entirely. These privacy protections apply throughout Analytics, including subscription and cohort views.
On peer group benchmarks: Benchmark values are generated using differential privacy. Peer group benchmarks also only include data from users who have agreed to share their app analytics.
Before making a significant change based on a metric — especially a new one — confirm what that metric includes, what it excludes, and whether privacy thresholds could be affecting visibility.
Keyword Optimization Still Drives Organic Discovery
Even as measurement expands, wiki:keyword-research remains the primary organic growth lever. Search accounts for 65-70% of app installs, and apps that rank in the top three results capture up to 90% of all organic downloads from those queries. The difference between ranking and not ranking is the difference between growth and invisibility.
The mechanics of keyword optimization differ significantly between iOS and Android. On iOS, the 30-character app title carries the strongest ranking weight, followed by the 30-character subtitle and the 100-character keyword field. The keyword field is invisible to users but fully indexed for search. Best practice is to lead with the brand name in the title, use the subtitle for a high-value secondary keyword, and pack the keyword field with singular forms of target terms (Apple automatically matches plurals). Keywords should be separated by commas with no spaces, and duplicate words from the title or subtitle waste characters.
On Google Play, the approach is different. There is no dedicated keyword field. Instead, keywords are inferred from the 50-character title, the 80-character short description, and the 4,000-character full description. The short description carries high keyword weight and should include the primary keyword naturally within a compelling value proposition. The full description is indexed, and keyword density matters — the primary keyword should appear 3-5 times naturally throughout the text, with secondary and long-tail keywords distributed across the body.
Algorithm Shifts Now Reward Retention as Heavily as Relevance
The most significant shift in app store ranking factors over the past year is the increased weight given to retention and engagement metrics. Both Apple and Google now treat post-install behavior as a primary quality signal, on par with keyword relevance.
On iOS, Day 1, Day 7, and Day 30 retention are tracked as quality signals. Apps that are frequently uninstalled within 24 hours may receive ranking suppression. Session frequency and depth signal ongoing value to users. The algorithm likely uses engagement data from App Analytics, though the exact implementation remains undisclosed.
On Google Play, retention and uninstall rate are now major factors in 2026. Early uninstalls (within 24-48 hours) send a strong negative signal to the algorithm. Apps with high uninstall rates after organic discovery see progressive ranking decay. Google has publicly stated that user engagement metrics directly affect quality scores in their ranking model. This creates a feedback loop: poor retention leads to lower rankings, which means fewer quality users discover the app, which further hurts retention.
Beyond retention, Google Play tracks specific engagement signals that feed into ranking calculations: session frequency, session duration, feature usage depth, and in-app actions such as completing purchases or sharing content. Technical quality is also a hard ranking factor. Google monitors crash rate (threshold: 1.09%) and ANR rate (threshold: 0.47%). Apps above these thresholds may see ranking penalties.
The practical implication: keyword optimization can no longer be treated in isolation. Ranking well on either platform now requires building an app that people actually use, not just download.
Two Recent Algorithm Changes Worth Noting
Two recent changes to the Apple App Store algorithm have expanded the available keyword optimization surface.
First, as of June 2025, Apple now indexes text that appears in screenshot captions for search. This is one of the most significant algorithm changes in recent years. Keywords in screenshot overlay text can now contribute to wiki:search-visibility. This makes screenshot design a dual-purpose optimization — conversion and discoverability. Caption text should be natural and user-facing (not keyword-stuffed), since it is visible to users. This change effectively expanded the total indexable metadata on the App Store for the first time in years. Developers who adapted quickly saw measurable ranking improvements for keywords that appeared in their screenshot captions.
Second, Apple's Custom Product Pages (CPPs), originally designed for paid acquisition campaigns, now appear in organic search results. This is a significant shift for keyword strategy. Each CPP can target different keyword themes with unique metadata. CPPs now surface in organic App Store search when their metadata matches a query. This effectively gives marketers multiple landing pages for different search intents. Up to 35 CPPs can be created per app, each with distinct screenshots, descriptions, and promotional text. Google Play offers a similar feature called custom store listings, which can be targeted by country, pre-registration status, or Google Ads campaigns.
Avoiding Keyword Cannibalization Across Multiple Pages
As Custom Product Pages and custom store listings become more widely used, a new risk emerges: keyword cannibalization. This occurs when multiple pages on the same domain (or, in the app store context, multiple product page variations) target the same search query, leading them to compete rather than reinforce a single strong result.
The consequences include diluted authority across multiple URLs, unstable rankings as the algorithm struggles to determine which page should rank, and lower click-through rates when the wrong page is served for a given search intent. The fix is straightforward but requires discipline: each product page variation should target a distinct keyword intent. Create a keyword map that assigns one primary keyword and intent per URL. If two pages are competing for the same keyword, merge them into one stronger page or redirect the weaker URL to the primary one so all authority flows to a single source.
Preventive measures include regular content audits, tracking keyword rankings and performance for anomalies (such as rank swapping between two URLs for the same query), and focusing on topics and search intent first, keywords second. If the same question is being answered in slightly different ways across multiple pages, consolidation is the answer.
What This Means for Practitioners
The combined effect of these changes — expanded analytics, algorithm shifts toward retention, new indexable surfaces, and the rise of custom product pages — is that app store optimization has moved from a purely metadata exercise to a full-funnel discipline. Keyword optimization remains the foundation, but it must now be supported by post-install quality, cohort-specific measurement, and variant testing across multiple product page experiences.
Marketers who treat ASO as a set-and-forget task will see diminishing returns. The new measurement capabilities in Insights and App Store Connect Analytics make it possible to close the loop between keyword targeting, user acquisition, and downstream outcomes. The apps that will win in this environment are those that combine strong keyword coverage with strong product experience — and measure both continuously.