ASO Reporting Metrics: What to Track and How to Read It
ASO Reporting Metrics: What to Track and How to Read It
A useful ASO report answers one question: did the changes we made to our store listing bring more of the right users? To answer it, you need metrics from four layers: visibility (impressions and keyword rankings), conversion (product page views, store listing visitors and conversion rate), volume (organic downloads) and business impact (retention, subscriptions and revenue). Anything beyond that is usually noise.
This guide shows what each metric means on the App Store and Google Play, how the two stores differ, how to segment the data, and how to build a report you can read in ten minutes.
TL;DR
- Report on four layers: visibility, conversion, organic installs and business impact. Read each metric next to its neighbors, never alone.
- Apple and Google define “conversion” differently. Apple divides downloads by unique-device impressions. Google Play now reports click-through rate on the store listing. Never compare the two numbers directly.
- Segment by store, country, traffic source and, where the console allows, search term. A blended global number hides most of what changed.
- To judge a listing change, look for several signals moving together: rankings, impressions, conversion, installs and downstream cohorts.
- Keep the weekly report to a handful of metrics and add the business layer monthly.
Table of Contents
- The four layers of an ASO report
- Visibility metrics
- Conversion metrics
- Organic installs: the volume metric
- Segment before you conclude
- Business impact: retention and revenue
- How to tell if a listing change worked
- A report you can actually use
- Common reporting mistakes
- Perspective: why we built reporting around one view
- Put the report together with Apptenium
- FAQ
- Sources
The four layers of an ASO report
Most reports go wrong by dumping every available chart onto one page. A better structure follows the user’s path from discovery to value:
- Visibility: how often your app appears in front of people. Impressions, keyword rankings, share of search.
- Conversion: how many of those people act. Product page views, store listing visitors, conversion rate or click-through rate.
- Volume: how many installs you actually get from organic sources.
- Business impact: whether those users stick around and pay. Retention, subscription conversion, revenue per user.
Each layer explains the one below it. If downloads fall, you check conversion. If conversion is flat, you check impressions. If impressions drop, you check rankings. Having the layers in this order in your report turns a diagnosis into a checklist.
Visibility metrics
Impressions
On the App Store, impressions are the number of times your app was viewed on the Today, Games, Apps or Search tabs for more than one second, and that count includes product page views. That detail matters: an impression is not a guaranteed look at your icon, but a view that lasted at least a second.
Impressions are an early signal. They tell you whether a metadata change put you in front of more people, but they do not say whether those people were the right ones. Treat a rise in impressions as a reason to check conversion, not as a win.
Keyword rankings
Rankings explain why impressions move. When you change a title, subtitle, keyword field or short description, the first thing that should shift is where you rank for the terms you targeted. Track a defined set of keywords, grouped into clusters by intent (for example, brand terms, category terms and feature terms), and report the median position per cluster, not only the best single keyword.
Two cautions help here. A rank gain on a term nobody searches changes nothing, so pair each keyword with its estimated popularity. And a rank drop on one term may be a trade you made on purpose when you swapped it for a stronger one. Annotate your report with every metadata change so the reader sees cause and effect.
Our ASO tools track keywords and search rank across both stores, so the rankings and your listing changes sit in one view.
Ratings and reviews
Ratings and reviews are the context behind a conversion swing. A new release with a crash, a pricing change or a sudden batch of one-star reviews can lower conversion even if your keywords and screenshots are untouched. Report the average rating, the number of new ratings in the period and the themes of recent negative reviews.
Google Play’s official app statistics put ratings next to quality indicators such as user-perceived crash and ANR rates, which is a useful reminder: a rating dip often has a technical cause that metadata work cannot fix. When conversion and rating fall together, look at the release before you rewrite the listing.
Conversion metrics
Product page views and store listing visitors
Once someone sees your app in search or a chart, the next step is opening the page. Apple reports this as product page views, defined as views of your app’s product page.
Google Play counts differently. Store listing visitors are users who visited your listing and did not already have the app installed on any of their devices, counted once per day and per dimension. Existing users are filtered out, which makes the number cleaner for acquisition analysis but not equal to Apple’s.
Conversion rate and click-through rate
Apple defines conversion rate as total downloads and pre-orders divided by unique-device impressions. Because total downloads include first-time downloads plus redownloads, a surge in returning users can lift the number without any change in how well your listing persuades new people.
Google Play’s current listing report uses click-through rate, the share of listing visitors who clicked Install, Open or Pre-register. It replaces the legacy conversion rate metric. The report focuses on unique user clicks, the part of the journey your listing most directly controls.
The practical rule: benchmark each store against its own history. Do not put an Apple conversion rate and a Google Play CTR in the same chart as if they measured one thing.
| Question | App Store Connect | Google Play Console |
|---|---|---|
| How many saw the app? | Impressions (Today, Games, Apps, Search tabs, over one second) | Store listing visitors (not already installed) |
| How many opened the page? | Product page views | Unique user install clicks |
| How well does the page convert? | Conversion rate: downloads and pre-orders over unique-device impressions | Click-through rate on the listing |
| Where did they come from? | Source types | Search, Explore, ads and referrals, UTM source and campaign |
Organic installs: the volume metric
Impressions and conversion are means. The result is downloads from organic sources. A sound reading is that impressions are the early signal, while organic downloads are the figure that proves a visibility change worked, and conversion rate is the figure that proves a creative or copy change worked.
Two definitions to keep straight. Apple’s total downloads combine first-time downloads and redownloads. For ASO analysis, first-time downloads are the better yardstick, since redownloads reflect your existing user base and not new discovery. On Google Play, the listing report pairs visitors and clicks with store listing acquisitions, while completed acquisitions also appear in the broader acquisition and statistics reports.
Always split organic from paid. A campaign launch can inflate total installs and make a weak listing look healthy. Our app analytics view puts downloads, revenue and ad performance side by side so you can see which installs the listing earned.
Segment before you conclude
A blended number is rarely wrong, but it is rarely useful. Segment every core metric by:
- Store: App Store and Google Play behave differently and use different definitions.
- Country and language: a localization update in Germany should be judged in Germany. Google Play’s current report can segment by traffic source, country or region, language, search term, UTM source and campaign, install state and listing.
- Traffic source: search, browse and referral users behave differently. Search users arrive with intent. Browse users are often more casual.
- Keyword: where the store exposes search term data, tie conversion to the queries that produced it.
Segmentation also protects you from false alarms. If total downloads dropped 8% but all of it came from one country where a seasonal dip is normal, nothing is wrong with your listing.
Business impact: retention and revenue
ASO that fills the funnel with users who churn on day one is not success. The final layer connects store performance to value.
Google Play’s official statistics include user acquisitions and losses, total audience, DAU, MAU, revenue and average revenue per DAU. On Apple’s side, subscription reporting defines conversion rate (all) as the percentage of completed offers that converted to a paid subscription. And App Store Connect cohorts group users by download or subscription start and track download-to-paid conversion and subscription retention, which helps you judge changes to onboarding, pricing, offers or acquisition quality.
For an organic report, a short list is enough:
- Day 7 and day 28 retention for organic cohorts
- Download-to-paid conversion for subscription apps
- Revenue per install from organic users
- Ad revenue per user for ad-supported apps
If a listing change lifts downloads but the next cohort retains worse, you may have attracted the wrong audience. That is a metadata problem as much as a product one: promise in the listing what the app delivers.
How to tell if a listing change worked
No single metric proves that an update caused an improvement. Seasonality, a feature in the store, a press mention or a paid campaign can all move the same numbers. Confidence comes from agreement across the layers:
- Rankings moved for the keywords you targeted.
- Impressions rose in the segments where rankings rose.
- Conversion held or improved, so the extra traffic was relevant.
- Organic installs rose accordingly.
- Cohorts from the following weeks retained and monetized at least as well as before.
When all five agree, you can be fairly sure. When only impressions moved, you have a hypothesis. Where possible, strengthen the evidence with the stores’ native listing experiments, and compare against a country where you changed nothing. Log the date and the exact change for every update, and compare equal periods: two full weeks before against two full weeks after, ideally at the same point in the week.
A report you can actually use
Here is a structure that keeps the report short and decision-oriented.
Weekly: the pulse
Pick a few metrics that move fast and that you can act on: impressions, conversion rate (or CTR on Google Play), and the ranking of your priority keyword clusters. Our view is that a weekly report with more than a handful of numbers stops being read. For a primer on the underlying discipline, see these App Store Optimization basics.
Monthly: the verdict
Add the slower layer: organic versus paid share of installs, retention of organic cohorts, review volume and rating trend, and revenue per install. This is the report that tells you whether the month’s ASO work earned its keep.
Every report: the same three notes
- What changed in the listing, with dates.
- What moved in each layer, by store and top countries.
- What you will do next and which metric will confirm it.
Common reporting mistakes
- Comparing the stores’ conversion numbers. The definitions differ, so compare each store with itself.
- Judging by impressions alone. More views from irrelevant queries lower conversion.
- Mixing paid and organic. Report them separately or the listing gets credit for ad spend.
- Ignoring existing users. Redownloads and returning users flatter Apple’s total download counts.
- Reporting without annotations. A chart without a change log cannot support a conclusion.
- Using tiny windows. A three-day dip is rarely a trend. Use full weeks.
Perspective: why we built reporting around one view
We talk to developers and marketers who keep rankings in one tool, store data in the consoles, revenue in a third place and ad performance in a fourth. The report then takes half a day to assemble, and by the time it is done nobody trusts the connections between the numbers.
We think the fix is less about more metrics and more about putting the right ones next to each other. A ranking drop means little until you see the impressions and installs beside it. A conversion gain means little until you see whether those users paid. That is why Apptenium combines ASO scanning, keyword tracking, competitor intelligence and app performance reporting, with data from Firebase and Google Analytics and ad networks, and why each scan ends with copy-ready fixes you can apply the same day.
A report is only worth the decisions it produces. If yours doesn’t end with a next action, trim it.
— Mike
Put the report together with Apptenium
If you want these layers in one place, start with the free tier, which gives you a limited number of scans per month to audit your listing metadata. Pro is $9.99 per month and adds unlimited scans and premium features. You can also watch how rivals’ rankings and listings change in our competitor intelligence view, which is useful context when your own numbers move.
Not ready to commit? The free ASO tools include a scanner, a word frequency tool and an icon generator.
FAQ
Which ASO metrics matter most?
Start with impressions, keyword rankings, conversion rate (or CTR on Google Play) and organic downloads. Add retention and revenue per install monthly so the report reflects business value, not just traffic.
How is conversion rate calculated on the App Store?
Apple divides total downloads and pre-orders by unique-device impressions. Because total downloads include redownloads, read it alongside first-time downloads when you judge new-user acquisition.
Is Google Play conversion rate the same as Apple’s?
No. Google Play’s current listing report centers on click-through rate, the share of store listing visitors who clicked Install, Open or Pre-register. It replaces the old conversion rate metric, so benchmark each store against itself.
How often should I report on ASO?
Review a small set of fast-moving metrics weekly and the business-impact layer monthly. Wait for at least two full weeks of data after a listing change before drawing conclusions.