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App Store Data Studies: Method and Reports
Every App Store statistic in these guides comes from one catalogue, counted one way, on a named date. Here is that method, where the data comes from, and every report built on it so far.
Quick answer
The AppTierList data studies measure ranked iPhone apps in AppTierList's active use-case lists, from public App Store data, on a fixed snapshot. At the snapshot behind the current reports (a snapshot taken on 3 November 2026, data as of 2 November), that meant 30,075 ranked list entries across 1,235 active lists, made up of 18,934 different apps, with 6,308 tracked search terms and search ranks read in five countries: the US, UK, Canada, Australia and Germany. A list entry is one app in one list, and only the top 40 of a list hold a tier, so an app in three lists counts three times. Rating counts are summed across the storefronts AppTierList reads, never called worldwide or US. Where a study compares tiers on something the score itself uses, such as rating count, update recency or search position, part of the gap is there by construction. Every list's figures can be recounted in its JSON at /api/v1/lists/ plus the list's slug.
Every study starts from the same ranked list entries
AppTierList sorts iPhone apps into use-case lists, such as habit tracking or password managers, and gives the top apps in each list a tier from S down to F. The data studies all begin from one base: the ranked members of every active list. A ranked member, or list entry, is one app inside one list that holds a tier there. Only the top 40 of a list get a tier, so the long tail of each list stays out.
At the snapshot behind the current reports, the base held 30,075 ranked list entries. They belong to 1,235 active lists and to 18,934 different apps. By tier it splits like this:
| Tier | Ranked list entries |
|---|---|
| S | 6,601 |
| A | 7,414 |
| B | 6,116 |
| C | 6,546 |
| D | 2,223 |
| F | 1,175 |
The reason for counting list entries rather than apps is simple. A tier is not a verdict on an app in general; it is its place among the apps that do the same job. A note app can be S tier for quick capture and C tier for long writing. Counting each list entry once matches what a reader sees on the list pages, and it keeps an app that sits in many lists from being squashed into a single average.
A study that needs a wider base says so. The directories study, for example, counts every active member of an active list, tiered or not, which gives 30,935 different apps, against 18,934 different apps in the ranked set.
The data is public App Store data, read on a dated snapshot
The data in the base comes from public App Store listings and searches: app names, prices, star ratings, rating counts, current version dates and where each app appears when the App Store is searched with a list’s terms. At the snapshot, 6,308 search terms were tracked across the active lists, and search ranks were read in five countries: the US, UK, Canada, Australia and Germany.
Rating counts need one extra word of care. Apple shows each territory its own summary rating, so no single public rating count exists for an app. The studies add up the counts AppTierList holds and label them “summed across the storefronts we read”. For most apps that means the five countries above; 4,237 of the 30,075 ranked list entries had a total from every storefront. A study never calls these counts worldwide, and never calls them US figures.
Each number is counted on a fixed copy of the catalogue, not on the live site. The current reports use a snapshot taken on 3 November 2026, with data as of 2 November 2026. The catalogue moves every day: on the evening of 3 November 2026 the public lists index already showed 1,248 active lists and 19,084 apps holding a tier. That is why every study states its date, and why a refresh of a study changes its numbers.
One limit is fixed by time. Chart history (the US top free and top paid charts) starts on 25 September 2026, so no study can say how an app placed on those charts before that date, or in any other country.
Some tier gaps come from the method itself
The score behind every tier rests mostly on public App Store data. Every part of it is set out on How we rank. Several of those parts are the very things a study might compare across tiers: how many people rated an app, how recently it shipped a version, and where it shows up in App Store search.
When a study compares tiers on one of those inputs, some of the difference exists by construction. If recency feeds the score, S tier apps will look fresher than F tier apps partly because the method rewards freshness. Each study that does this says so next to its numbers. Inputs also lean on each other outside the score: Apple says App Store search weighs text relevance and user behaviour such as downloads and ratings, so a high rating count and a strong search position tend to travel together.
What the studies can show is the contrast between the top and the bottom of a list. They cannot prove that a higher count, a faster release rhythm or a keyword in the name caused a higher tier.
Any list can be recounted with one API call
Each list has a public JSON record. The call GET /api/v1/lists/habit-tracking returns the habit tracking list with every member’s tier, score parts, rating counts, version date and search ranks by country. Swap in any slug from all lists to get another. The API returns today’s data, not the snapshot’s, so a recount follows the same method but will not land on a study’s exact figures. The rating count the studies use is the field rating_count_worldwide (the field rating_count holds the US count only); until an app’s first pass over every storefront, that field holds the best known count. GET /api/v1/lists returns the full index with the count of active lists and of apps holding a tier, and GET /api/v1/health publishes the current catalogue counts with the time they were taken.
The same record feeds the list pages, the API and the MCP server that AI assistants can query, so a number in a study, a tier on a page and an answer from an assistant all trace back to one source. Each study also prints its exact query in its stat block, with the snapshot date beside it.
The reports so far, and what each one found
Each report below uses the base and the caveats above. Most figures are a share or a median of ranked list entries at the same snapshot; the directories study counts apps across every active member, as it says.
- How often top apps update: the current version shipped within 30 days for 78.5% of S tier list entries and for 11.2% at F tier, where 72.3% had gone over a year without one. Recency is a score input, so part of this gap is by construction.
- App Store ratings: the median S tier list entry had 77,582 ratings and the median F tier entry 1,898, summed across the storefronts AppTierList reads. Rating count is a score input too.
- App Store optimization: 38.2% of S tier list entries had a name containing one of the list’s tracked search terms, against 13.4% at F tier. A name keyword can lift search position, which is a score input, so part of this link runs through the score.
- App directories: for 97.7% of apps in active lists, at least one of their lists holds 10 or more rivals, which is why being listed next to competitors matters.
- Ways to promote an app uses the ratings study’s under-50 count (34.0% of F tier list entries, 0.0% at S) beside its table of channels.
New studies join this page as they publish, each with its own snapshot date and query.
Claim your page, then set it next to the numbers
The studies describe whole lists. Your own page is where a reader, or an assistant, sees how one app sits inside its list. Adding your app is free and fast. To make that page yours:
- Claim it: submit the app with your email if it is new, or open its page and tap Claim. Free, no password, a single email address.
- Fill in your website and a short note, written as yourself, about what the app is for. The note becomes visible after verification.
- Share the page link wherever your users and your press kit live.
Then come back when a study refreshes. Its date will be newer, and the list your app sits in will show how the same measures look for you today.
The numbers
- 30,075ranked list entries (one app in one list, holding a tier) in active lists at the snapshotAs of
- 18,934different apps behind those ranked list entriesAs of
- 1,235active lists with ranked members at the snapshotAs of
- 6,308search terms tracked across the active listsAs of
- 5countries in which search ranks are read (us, gb, ca, au, de)As of
- 40apps at most per list hold a tier (only the top 40 of a list get a tier)As of
- 6,601S tier list entries in active listsAs of
- 7,414A tier list entries in active listsAs of
- 6,116B tier list entries in active listsAs of
- 6,546C tier list entries in active listsAs of
- 2,223D tier list entries in active listsAs of
- 1,175F tier list entries in active listsAs of
- 2 November 2026the data date of the snapshot behind the current studiesAs of
- 3 November 2026the day the snapshot behind the current studies was taken, and the day of the live API read belowAs of
- 4,237of the 30,075 ranked list entries had a rating total from every App Store storefront; most of the rest are summed over the five countries read (us, gb, ca, au, de); 156 have a single-storefront countAs of
- 1,248active lists reported by the public lists index on the evening of 3 November 2026 (count)As of
- 19,084apps holding a tier in at least one active list, on the same readAs of
- 25 September 2026the first stored chart snapshot (US top free and top paid charts only; 38 of the 40 days to 2026-11-03 have a snapshot)As of
- 78.5%of S tier list entries shipped their current version within 30 days (update-cadence-study)As of
- 11.2%of F tier list entries shipped their current version within 30 daysAs of
- 72.3%of F tier list entries were on a version more than a year oldAs of
- 30days: the shortest window in the update studyAs of
- 77,582median rating count of S tier list entries, summed across the storefronts AppTierList reads (app-store-ratings-guide)As of
- 1,898median rating count of F tier list entries, summed across the storefronts AppTierList readsAs of
- 38.2%of S tier list entries have an app name containing one of that list's tracked search terms (app-store-optimization-guide)As of
- 13.4%of F tier list entries have an app name containing one of that list's tracked search termsAs of
- 34.0%of F tier list entries have fewer than 50 ratings, summed across the storefronts AppTierList reads (the figure best-ways-to-promote-your-app cites)As of
- 0.0%of S tier list entries have fewer than 50 ratings (2 of 6,601, which rounds to 0.0)As of
- 50ratings: the line of the under-50 countAs of
- 97.7%of apps in active lists sit in at least one list with 10 or more rivals (app-directories-guide)As of
- 10rivals in one list: the threshold of the directories studyAs of
- 30,935different apps in the directories study: every app that is an active member of an active list, tiered or notAs of
Method: 30,075 ranked list entries (one app in one list; only a list's top 40 hold a tier) of 1,235 active lists, 18,934 different apps, 6,308 tracked search terms, search ranks read in 5 countries (US, UK, Canada, Australia, Germany), data as of 2026-11-02. Rating counts are summed across the storefronts AppTierList reads. Where a study compares tiers on a score input, the link is partly by construction. Live counts from /api/v1/lists, read 2026-11-03.
Reproduce it: GET https://apptierlist.com/api/v1/lists
Keep reading
- Data · 5 min read
How Often Do Top Apps Update?
We measured how long ago every ranked app in every active list shipped its current version. The top of each list is almost always fresh; the bottom has mostly stopped. - Ratings · 6 min read
How Many App Store Ratings You Need
The star average gets the attention, but the number of ratings behind it is what people and rankings trust. Here is the target, the timing and the rules. - ASO · 7 min read
App Store Optimization for iPhone Apps
ASO is the work of being found inside the App Store. Here are the fields Apple reads, a way to pick a keyword a new app can own, and the order to do it in. - Competitors · 5 min read
App Directories Worth Your Time
A directory is worth your time when it shows your app next to the apps people compare it with. A bare listing does far less, for search and for AI. - Launch · 7 min read
Best Ways to Promote Your App in 2026
Ten promotion channels for a small iPhone app, compared on what they cost, how much work they take and how long they keep paying back.
FAQ
Where do AppTierList's App Store statistics come from?
From public App Store data: app details, ratings, version dates and the results of App Store searches run for each list in the US, UK, Canada, Australia and Germany. Each study is counted on a dated snapshot of that catalogue, and the How we rank page lists every part of the score the tiers come from.
Why do the studies count list entries instead of apps?
A tier belongs to an app inside one list, not to the app overall. An app that sits in three lists can hold three different tiers, so each study counts it once per list, the same way the lists themselves show it.
Are AppTierList rating counts worldwide or US only?
Neither. They are summed across the storefronts AppTierList reads, which for most apps means the US, UK, Canada, Australia and Germany, with a total from every storefront for a smaller group. Apple keeps a separate summary rating for each territory.
Does a study prove that more ratings or more updates cause a higher tier?
No. Rating count, update recency and search position are inputs of the score, so when a study compares tiers on one of them, part of the gap comes from how tiers are built. The studies show how the top and bottom of a list differ, not what caused the difference.
How can I check a number myself?
Open the list's JSON on the public API at /api/v1/lists/ followed by the list's slug. It returns every member with its tier, score parts, rating counts, version date and search ranks per country, so a list can be recounted without an account. The API returns today's data, so a recount follows the method rather than matching the snapshot's exact figures. The studies' rating count is the field rating_count_worldwide, which holds the best known count until an app's first pass over every storefront; rating_count is the US count only.
Sources
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