How do I find apps in a specific App Store category?

Apple's own search takes a term, not a set of conditions, so it cannot answer "every finance app rated above 4.3 with fewer than 500 ratings". You need a catalogue you can filter on metadata. ASOApp's App Discovery does this against the apps this site has indexed, per storefront, filtering on category, price, rating, rating count, localization, devices, file size, age rating, minimum iOS, title length, screenshot count, release and update date, and chart position and movement.

What is a good sign that a niche is underserved?

A category with steady chart movement where the ranked apps have few ratings, short titles, no localization beyond English and no update in a year. Each of those is a metadata filter, so the combination is one query rather than an afternoon of browsing. Low rating counts with recent chart entries is the strongest single signal — demand exists and incumbents are not entrenched.

Can I do App Store market research without paying for a data platform?

For structural questions, yes. Category composition, rating distribution, localization depth, update cadence and title conventions are all public App Store metadata. What you cannot get free is licensed download and revenue estimates, which come from panel data no public endpoint exposes. Be clear which kind of question you are asking before deciding whether you need to pay.

Does filtering apps like this need an account?

App Discovery needs a free account, because it hands back the whole indexed catalogue in bulk. The free plan combines two filters at a time; PRO lifts that and adds CSV export.

App Store Market Research: Finding Apps by Filter, Not by Search

Most App Store research starts with a search box, and a search box is the wrong instrument for it. Search answers "which apps match this word". Market research asks "which apps match these conditions" — and those are different questions with different tools.

Why search cannot answer a research question

Apple's App Store search takes a term and returns apps ranked by relevance to it. That is exactly right when you know what you are looking for. It falls apart the moment your question has conditions instead of keywords:

Every Health & Fitness app rated above 4.3 that has fewer than 500 ratings.
Apps in my category that ship in more than eight languages.
Apps that entered the top 100 this week and have not been updated in a year.
Competitors whose title is already at the 30-character limit.

None of those is a search term. Each is a filter over metadata, and answering it by typing words into a search box means eyeballing result lists and guessing — which is how a morning disappears and the conclusion still rests on a dozen apps you happened to notice.

The three questions filtering answers well

1. How is this category actually composed?

Before you pick a category, you want its shape: how many apps are in it, what the rating distribution looks like, how many are free, how many are localized, how recently the ranked ones shipped. Filtering the catalogue by category and reading the counts gives you that in a minute. It is the difference between "Productivity looks crowded" and "Productivity has this many indexed apps in this storefront, and the ones actually ranking have this many ratings".

2. Which apps are genuinely comparable to mine?

"Competitor" usually means one of two things, and conflating them costs you. There are apps that rank for your keywords — that is a search question, and a competitor teardown answers it. And there are apps that are structurally like yours: same category, same price model, similar rating count, similar age. Those are the ones whose metadata choices are actually evidence about what works at your size, because a category leader with 200,000 ratings tells you nothing you can act on.

Filtering on rating count is the single most useful move here. It replaces "who is big in this category" with "who is where I am".

3. Where is demand not being served well?

An underserved niche is a combination, not a single signal. The one worth looking for:

Chart movement exists — apps in this slice are entering or climbing, so people are searching and installing.
Rating counts are low — no incumbent has accumulated an unassailable social-proof moat.
Update dates are old — the apps that are there are not being actively defended.
Localization is thin — English-only listings in a market where the storefront is not English-speaking.

Each of those is one filter. Together they are one query. That combination is the actual argument for filtering over browsing: the interesting questions are always intersections, and intersections are what a search box cannot express.

The metadata worth filtering on

Not every field is equally informative. In rough order of how much they tell you:

Field	What it tells you
Rating count	Real scale, far better than rating value. A 4.9 from 30 people means nothing; a 4.4 from 40,000 means an entrenched incumbent.
Last update date	Whether the app is defended. A category full of two-year-old listings is a category with room.
Localization count	How seriously a developer takes non-English storefronts — and where the gaps are.
Chart position and movement	Live demand. A recent entrant is a signal; a static top-10 is a wall.
Price model	Whether the category monetizes up front or through IAP, which shapes what your listing has to do.
Title length	Whether the incumbents have exhausted their keyword surface, or left it on the table.
Screenshot count	Conversion effort. Two screenshots in a competitive category is a listing nobody has worked on.
Minimum iOS and devices	Reach constraints, and occasionally a legacy app that has quietly stopped keeping up.

Rating value is the field people reach for first and the one that misleads most. Use rating count for scale, and read the value only alongside it.

What this kind of research cannot tell you

Be precise about the boundary, because it determines whether public metadata is enough:

Downloads and revenue are not public. No public Apple endpoint exposes them. Anything quoting them is modelling from panel data, and that is what paid platforms sell. Metadata research tells you about structure and behaviour, not volume.
Rating count is a lagging proxy for installs. It correlates with scale but the ratio varies enormously by category and by how aggressively an app prompts.
An index is not the App Store. Any catalogue you filter is a subset of Apple's, so counts are relative, not absolute. Read them as "of the apps indexed here" and compare slices against each other rather than treating any number as a census.
Metadata does not explain why. Filtering finds the interesting apps. Understanding what they did still means opening the listing and reading it.

A workable routine

Frame the question as conditions, not as a term. Write it down before you touch the tool — "finance apps, over 4.3, under 500 ratings, updated this year" is a query; "good finance apps" is not.
Start with category and storefront, then add one condition at a time and watch the count fall. The filter that collapses the result set is the one carrying the information.
Sort by rating count, not rating. You are looking for your own weight class.
Open five listings, not fifty. The filter's job is to get you to a handful worth reading properly.
Take the keywords with you. The apps you found this way are the right input to a competitor teardown and to keyword research — filtering finds who to study, keyword tools tell you what they are winning.

Doing it in ASOApp

App Discovery is the tool for this. It opens directly on every app this site has indexed for a storefront — no search box, because the starting point is the whole catalogue, not a term — and you narrow from there on category, price, rating, rating count, localization, devices, file size, age rating, minimum iOS, title length, screenshot count, release and update date, and chart position and movement.

The index grows on its own: every app that surfaces in a keyword score, a teardown or a chart here gets added and enriched with its full App Store metadata, per storefront, and is kept fresh. It is not a census of the App Store and the tool does not present it as one — the app count for the storefront is shown next to the filters so you always know what the numbers are relative to.

App Discovery needs a free account, since it hands the catalogue back in bulk. The free plan combines two filters at a time, which is enough for the "category plus one condition" questions; PRO lifts the limit and adds CSV export, saved filter sets and unlimited saved competitors. See pricing for what each plan includes.

Track your own app — free to start

See where your app ranks for keywords like this, across countries and over time. A new account starts a 7-day PRO trial — cancel before it ends and you pay nothing.

Add a single app — or paste a developer link to track all of their apps at once.