App Store Competitor Keyword Research: Find What Rivals Rank For
A manual process for reverse-engineering competitor App Store keywords from public metadata and search rankings, plus where real volume data actually comes from.
App Store Competitor Keyword Research: Find What Rivals Rank For
You cannot see a competitor's keyword field — Apple keeps it private. What you can see is every public surface they optimized: app name, subtitle, description, in-app purchase names, and the search results they appear in. Reverse-engineering those surfaces gives you a working keyword list in about an hour, without paying for a tool.
Finding the App Store keywords competitors rank for is the fastest way to build a validated term list, because someone else already paid to test it. An app sitting in the top five for a term has proven the term drives installs. This guide covers the manual App Store keyword research process, where search volume data actually comes from, and how to decide which terms are winnable.
For the field mechanics — the 100-character limit and what Apple rejects — see the App Store keyword rules guide. This page is about finding the terms.
Step 1: Build Your Competitor Set
Start with three groups, five apps each:
- Direct competitors. Same core function, same audience.
- Ranking competitors. Apps in the top 10 for the two or three terms you most want. These are often not direct competitors, and that is the point — they are who you actually have to outrank.
- Adjacent apps. Different function, overlapping audience. They reveal use-case terms you have not considered.
Search the App Store on a real device, not a simulator, and use the same country storefront you sell in. Results are localized and personalized enough that desktop previews mislead.
Step 2: Harvest Their Visible Metadata
Every competitor exposes four indexable surfaces. Copy each one into a spreadsheet verbatim:
| Surface | Character limit | Why it matters |
|---|---|---|
| App name | 30 | Their single highest-value term lives here |
| Subtitle | 30 | Their second-priority phrase |
| Description | 4,000 | Not indexed on iOS, but reveals vocabulary |
| In-app purchase names | 30 each | Indexed by Apple, frequently overlooked |
The name and subtitle are the signal. A team that spent 30 characters on "Habit Tracker & Routine" is telling you exactly which two phrases they consider worth the space. The description is not indexed on the App Store, but it shows you the words their customers use — useful raw material for long-tail terms.
In-app purchase display names are indexed and almost nobody audits them. Scroll to the In-App Purchases section on a competitor's product page and read every name.
Step 3: Find the Terms They Rank For
Work backwards from search results. Pick 20 to 30 candidate terms from Step 2, search each one, and record where each competitor lands. A simple grid works:
| Term | Competitor A | Competitor B | You |
|---|---|---|---|
| habit tracker | 2 | 7 | 34 |
| daily routine | 5 | 3 | — |
| streak counter | 11 | 1 | — |
Three patterns are worth acting on:
- Terms where every competitor ranks and you do not. These are table stakes — you are invisible for demand your category already serves.
- Terms where exactly one competitor ranks. Usually an under-contested term someone found first.
- Terms where the top results are weak — low ratings, few reviews, stale updates. That is where a new app can break in.
Step 4: Get Real App Store Keyword Search Volume
Apple publishes no App Store keyword search volume. The only demand signal Apple exposes is the Apple Search Ads popularity index, a relative score from 5 to 100 attached to each keyword inside an Apple Search Ads account. You need an advertiser account to see it, but you do not need to spend money to look.
Two things to know before you trust it:
- It is not a count. A popularity of 40 does not mean 40,000 searches. It is a relative index.
- The scale is exponential. The gap between 50 and 60 is far larger than the gap between 20 and 30, and the bottom of the range compresses hard — a 5 can mean anything from near-zero to a few hundred searches a month.
Third-party ASO platforms estimate absolute volume by modelling that index against their own panel data. Treat those numbers as directional. For prioritisation — which of two terms is bigger — the index is reliable. For forecasting installs, it is not.
Google Play exposes no equivalent index at all. On Android, use Google Ads keyword data as a rough proxy for web demand and validate against your actual Play Console search-term acquisition report after launch.
Do You Need a Paid App Store Keyword Tool?
An App Store keyword tool — Sensor Tower, AppTweak, Mobile Action, AppFollow and similar platforms — buys you three things: historical trend lines, automated rank tracking across many terms, and a modelled absolute volume figure. None of those are the research itself. They are convenience over a process you can run manually.
Run the manual process first for one release cycle. You will know within a month whether the time cost justifies a subscription, and you will understand what the tool's numbers actually represent. Teams that buy a tool before doing the manual pass usually end up trusting a modelled figure they cannot interpret. The free ASO tools roundup covers what you can get without paying.
Step 5: Score and Cut
A term earns a spot in your 100 characters only if it clears three tests:
- Relevance. Does the app actually do this? Irrelevant terms are a rejection risk and convert badly.
- Winnable difficulty. If the top five are all apps with 100,000+ ratings and you have 200, you are not ranking there this quarter. Target terms where the weakest top-10 result is beatable.
- Intent. "Free habit tracker" converts better than "productivity." Specific beats broad at small scale.
Score each term 1 to 5 on all three, multiply, and sort. Take the top terms until you hit 100 characters. Everything else goes in a backlog for the next release.
A Worked Example: Two Competitors, One Gap
A meditation app runs the process against two rivals.
Competitor A — name "Calmly: Sleep & Meditation," subtitle "Relax, Focus, Sleep Better." Their name spends 26 characters on three high-volume terms. The subtitle adds "relax" and "focus."
Competitor B — name "Breathe Space," subtitle "Anxiety Relief & Mindfulness." A weaker name, but the subtitle claims two terms A ignored entirely.
Running 25 candidate terms through the ranking grid produces this:
| Term | Calmly | Breathe Space | Weakest top-10 result |
|---|---|---|---|
| sleep meditation | 3 | 22 | 2.1★, 400 ratings |
| anxiety relief | 19 | 4 | 4.6★, 90k ratings |
| breathing exercises | 31 | 8 | 3.9★, 1.2k ratings |
| focus timer | 44 | 51 | 3.4★, 600 ratings |
The read: anxiety relief is contested by a strong incumbent and not worth the fight yet. breathing exercises and focus timer are both weakly defended — neither competitor optimized for them and the current top-10 has beatable apps. Those two go in the keyword field first.
Note that the gap did not come from the terms both competitors ranked for. It came from the terms neither prioritised but users still search. Ranking grids surface those; metadata scraping alone does not.
Step 6: Re-Run It Every Release
Competitor metadata changes silently. A rival who rewrites their subtitle can take a term you held for months, and you will only notice in your install numbers. Snapshot your competitor set's name and subtitle every release cycle and diff it against the last snapshot. Changes are a direct signal about what is working for them.
Pair the keyword work with the rest of the listing. The App Store description guide covers converting the traffic once you rank, and IconikAI's Store Description Generator writes ASO-optimized listing copy from your final term list.
Step 7: Track What Moves After You Ship
Research is only half the loop. Once the new field is live, you need to know which terms actually moved.
Three signals, in order of reliability:
- Your own rank grid, re-run. Same terms, same storefront, two weeks after the release lands. This is the only measurement fully under your control.
- App Store Connect impressions and product page views. These will not break out by keyword, but a step change after a keyword-only release is strong evidence.
- Apple Search Ads search-term reports, if you run any campaign. Paid search terms overlap heavily with organic demand and give you term-level data organic reporting does not.
Log every keyword field you ship with its date. Six months in, that log is the only record of what you tried, and it will stop you from re-testing a term that already failed. The best free ASO tools roundup covers the platforms that automate rank tracking if manual grids stop scaling.
FAQ
Can I see the App Store keywords competitors use? Not directly — the 100-character keyword field is private. You can reverse-engineer it from their app name, subtitle, in-app purchase names, and the search results they appear in.
How do you search keywords for App Store optimization? Start from competitor app names and subtitles, expand with synonyms and use-case terms, then check each candidate's Apple Search Ads popularity score and the strength of the current top 10. Keep terms that are relevant, in demand, and weakly defended.
Where does App Store keyword search volume come from? Apple's only public demand signal is the Apple Search Ads popularity index, a relative 5-to-100 score visible inside an Apple Search Ads account. Third-party tools model absolute volume estimates from it. Apple does not publish raw search counts.
Is the Apple Search Ads popularity score accurate? It is reliable for ranking one term against another, less so as an absolute figure. The scale is exponential and compresses at the low end, so small differences near the bottom mean very little.
Do I need a paid ASO tool? No. Manual competitor research plus the Apple Search Ads popularity index covers most of what a paid tool provides. Tools mainly save time on tracking and historical trends.
How many competitors should I analyze? Fifteen is a practical target — five direct, five ranking, five adjacent. Beyond that the term list stops producing new ideas.
Can I use a competitor's app name as a keyword? No. Unauthorized trademarked terms are a documented cause of App Store rejection. Target the category and use-case terms they rank for instead.
How often should competitor research be repeated? Every release cycle. Snapshot competitor names and subtitles each time and diff against the previous version to catch silent metadata changes.
Next Steps
Research produces a term list; the 100-character field decides which ones survive. Read the App Store keyword rules guide for the format constraints, and the App Store keyword optimization guide for how the field fits the wider ASO strategy across both stores.
If competitor tracking every release is not something you want to own, IconikAI's ASO Growth Agent runs keyword research, metadata optimization, and competitor tracking at $50 per app per month, with a 30-day money-back guarantee.