Article · Updated August 2026

App analytics and ASO tools compared

App analytics and app store optimization tools overlap at the edges, but they do not answer the same question. App Store Connect explains your app’s performance inside Apple’s store. A subscription platform explains customer entitlement and recurring revenue. Product analytics explains what measured users do in the product. An ASO platform adds keyword, competitor and market intelligence.

The right tool is the one that owns the missing evidence. Buying all four does not repair a broken identity join or an undefined first-value event.

MetricsJar publishes this comparison and sells a cross-source founder-reporting layer. That bias is explicit. MetricsJar is useful when the sources already exist and the recurring job is reading their top-line signals together. It is not a replacement for keyword intelligence, event exploration or subscription infrastructure.

The four jobs are different

Start by writing the question in one sentence. If it contains “keyword,” “competitor” or “category opportunity,” it is probably an ASO intelligence job. If it contains “what did this user do?”, it is a product-analytics job. If it contains “is this customer entitled?”, it belongs to subscription infrastructure.

Native App Store Connect analytics

Apple says App Store Connect Analytics covers acquisition, engagement, monetization, retention and quality, with interactive views and bulk reports available through the API (Apple). Analytics is included with Apple Developer Program membership and requires no additional technical implementation (Apple).

For acquisition, Apple exposes sources including App Store search, App Store browse, app referrer, web referrer and custom campaigns. It can connect a recorded download source to subsequent sales, usage and subscriptions, although a manual redownload resets the source attribution (Apple).

Use it when you need first-party answers about:

• impressions and unique impressions;
• product-page views;
• first-time downloads, redownloads and total downloads;
• store conversion rate;
• source type, territory and device;
• Apple-defined subscription and retention metrics.

The boundaries matter. Apple’s usage data depends on users opting in to share analytics, and the dashboard suppresses some data until privacy thresholds are met. Its conversion rate divides total downloads and pre-orders by unique-device impressions. That is not the same as product-page-view conversion, account activation or paid conversion.

Best fit: first-party store performance and Apple-attributed acquisition.

Poor fit: competitor keyword research, unrestricted product-event exploration or a cross-platform subscription ledger.

RevenueCat and subscription analytics

RevenueCat is subscription infrastructure with charts and analytics around customers, entitlements, transactions and recurring revenue. Its current pricing page says the product is free to start and prices by active subscriptions monitored rather than feature gates (RevenueCat). Check the live page before buying because pricing can change.

Use a subscription layer when the question is:

• Is this customer in a trial, active, cancelled, expired or in grace period?
• Which transaction created or renewed the entitlement?
• How did trial, renewal, cancellation and refund state change?
• What does normalized recurring revenue look like across store plans?

RevenueCat and App Store Connect can both display revenue-related metrics while using different calculations, observation rules or customer entities. A founder asking whether RevenueCat is “accurate compared with App Store” may be comparing two valid measures with different definitions. Preserve the metric name, revenue basis, time window and currency before treating the mismatch as an error.

Best fit: cross-platform subscription state, entitlements and subscription lifecycle.

Poor fit: organic keyword demand, competitor research or detailed non-subscription product behaviour.

Product analytics

Product analytics begins after a measured user enters the product. It is the right layer when the blocked question depends on events, identities, funnels, paths, cohorts or feature use.

PostHog, for example, offers product analytics and session replay alongside other products, with usage-based pricing and free allowances published on its pricing page (PostHog). The category is broader than one vendor: the important requirement is an event plan and an identity model that match the decision.

Use product analytics when you need to know:

• whether an eligible account completed the first-value event;
• where a measured funnel loses accounts;
• which features retained cohorts use;
• which observed behaviour to inspect with replay;
• how one segment behaves differently from another.

Instrumentation creates both power and responsibility. An event that fires twice, changes meaning or never joins to an account can make a sophisticated funnel less trustworthy than a simple source count. Start with entry, first value, commercial and return events. Add more only for recurring decisions.

Best fit: behavioural diagnosis and repeated event-based questions.

Poor fit: authoritative App Store downloads, subscription entitlement or external keyword intelligence.

ASO intelligence platforms

ASO platforms add market data that your own store account cannot provide. The category commonly includes keyword tracking, competitor monitoring, download or revenue estimates, creative history, reviews and market reports.

Two examples illustrate the range:

• Appfigures currently lists a free Starter option, a Connect plan at $9.99/month on monthly billing, Monitor at $44.99/month and higher tiers for deeper ASO and app intelligence. The pricing page separates connected-app analytics from keyword and market intelligence (Appfigures).
• AppTweak currently lists its Essential ASO plan at $79/month billed annually, with 500 tracked keywords, one seat and six months of historical data; higher plans add more keywords, history and features (AppTweak).

Prices and packaging were checked on 12 August 2026 and can change. Compare the live plan against the exact job, country coverage, historical window and number of tracked apps you require.

Use an ASO platform when you need to:

• discover and monitor relevant keywords;
• compare ranking movement by country;
• inspect competitor metadata or creative changes;
• estimate market or competitor performance with disclosed limitations;
• manage review or store-optimization workflows.

Estimates are not your first-party store ledger. Keep estimated competitor downloads separate from your own App Store Connect downloads, even when both appear in one interface.

Best fit: keyword, competitor and market decisions.

Poor fit: product-event truth, customer entitlement or a fixed founder operating brief.

Cross-source founder reporting

A founder-reporting layer sits above the sources. It is useful when the question is not “which keyword should we target?” but “can I see acquisition, activation and recurring revenue in one recurring view?”

MetricsJar is designed for that layer. It keeps source metrics visible together, preserves their definitions and reduces repeated dashboard assembly. The current offer is one complete dashboard free with local compute and the founder’s own keys; paid hosted dashboards are $40/month or $400/year for unlimited dashboards. Source credentials stay local. MetricsJar does not promise deep ad hoc analysis, ASO intelligence or unrestricted event exploration.

Best fit: recurring multi-source founder review across existing systems.

Poor fit: replacing the authoritative source or solving a missing instrumentation problem.

Comparison table

Current public facts were checked on 12 August 2026.

No row is a universal winner. The columns are different jobs.

A practical decision sequence

If downloads are the problem

Begin in App Store Connect. Separate impressions, product-page views, first-time downloads and redownloads. Segment by source, territory and device. Add an ASO platform only when you need external keyword or competitor evidence.

If paid conversion is the problem

Begin with the subscription source. Define trial eligibility and allow cohorts enough time to convert. Add product analytics when you need to observe the events before the paywall or trial decision.

If activation is the problem

Begin with product instrumentation. Define the first-value event and stable account identity. Store downloads and ASO ranks are context, not the activation denominator.

If reporting work is the problem

Keep the existing sources. Write down the recurring questions, align the reporting window and choose a thin reporting layer. Do not buy market intelligence because four dashboards are annoying to open.

Worked example: an iOS subscription app

Acme Coach has 40,000 monthly App Store impressions, 2,800 product-page views, 900 first-time downloads, 420 accounts, 160 first-value completions and 35 mature trial conversions. Those numbers come from different layers.

The stack can contain all layers eventually. It should not begin there. Add the next one only when its question recurs and its output changes a decision.

Frequently asked questions

Sources

• Apple App Store Connect Analytics overview
• Apple acquisition sources and funnel metrics
• Apple App Store Connect metric definitions
• RevenueCat pricing
• PostHog pricing
• Appfigures pricing
• AppTweak pricing
• Discussion about ad spend versus customer value
• Discussion after 100,000 downloads
• Discussion comparing RevenueCat and App Store reporting