App Store Keyword Research: Free Method + Data

App store keyword research is a loop: take a seed term, expand it with App Store autocomplete, check each phrase's top 10, keep the ones with weak competition, and place them in your name, subtitle and 100 byte keyword field. In 143 live US searches we ran on November 7, 2026, long-tail phrases were open 40% of the time and head terms 25%.

Reddit shows how many developers start from zero here. One reader under a keyword guide in r/iOSProgramming wrote: “I need to learn how to do ASO at some point because I am dire.” Another asked: “do you have play store keyword research tips ?” This page answers both, with numbers.

Best ways to do app store keyword research, ranked

Five approaches cover almost every indie developer. They differ in how much measuring you do by hand, not in where the keywords finally go: App Store Connect and Google Play Console are always where they are saved.

1. BigIdeasDB Desktop: the App Store Lab brainstorms with your own AI, measures every idea against the live search before it shows, pulls competitors from the same search, sweeps a category and audits your listing. It also covers Google Play. One-time purchase. It does not import from App Store Connect yet.
2. The App Store search bar: free. Type a seed and read the autocomplete. It is the same source we used for this study, one phrase at a time.
3. Apple Ads keyword suggestions: the only first party popularity number. It needs an Apple Ads account, and Apple says it shows popularity based on App Store searches.
4. A spreadsheet: free and fully flexible. You paste phrases, count ratings in each top 10 and score them yourself.
5. A general AI chatbot: good for brainstorming synonyms. It has no live App Store data, so every phrase it suggests still needs the top 10 check.

Desktop is ranked first because it is the only option here that automates the measuring step. The difficulty proxy below shows how to do the same check by hand.

How does App Store search pick keywords?

Apple matches your listing text and then weighs behavior. Apple's App Store search page says results are based on text relevance, meaning matches for your app's title, subtitle, keywords and primary category, plus user behavior such as downloads, ratings and reviews. Source: Apple, App Store search.

That gives you a short list of fields that count and a few that do not. Promotional text, for example, does not affect search ranking, according to the same page.

One wording difference matters. Apple's search page says keywords are limited to 100 characters total. The App Store Connect reference says 100 bytes. They are the same for plain English letters. They are not the same for German umlauts, accented letters, Japanese or Korean, so count bytes and you are safe in every language.

How to do app store keyword research, step by step

Run these six steps in order. Each one narrows the list and costs nothing but time.

1. Write 5 to 10 seeds. Name what the app does, the problem it solves and the object it works on. A habit app might use “habit tracker”, “daily routine” and “streak counter”. Plain words, the way a stranger would type them.
2. Expand with autocomplete. Type each seed into the App Store search bar and note every suggestion. In our test each seed returned 9.7 suggestions on average, with a cap of 10. About half were clean extensions of the seed.
3. Open the results and read the top 10. For each phrase, count how many of the first 10 apps have under 1,000 ratings. Note whether the exact phrase appears in their titles.
4. Score each phrase. Use the three bands from the next sections: locked, contested or open. Keep phrases that are open or contested and clearly relevant. Drop the rest.
5. Place the winners. Put the most valuable phrase words in the name and subtitle, the rest in the keyword field. The placement section has a field by field example.
6. Ship, wait, re-check. Search the phrases a week after the release goes live and note where you appear. Replace the words that clearly do nothing. Another reader in r/iOSProgramming asked the obvious question: “How long does it take to rank?” Nobody can promise a date, so measure instead.

Doing this by hand for 10 seeds and their suggestions means a few hundred searches. That is the step the BigIdeasDB Desktop App Store Lab automates. Its brainstorm uses your own AI to propose ideas, and every idea is measured against the live search before it shows. Competitors come from the same search, so there is no extra request. A category sweep lists weak spots across a whole category. Setup is in the Desktop help guide.

How do you estimate search volume without a paid tool?

You cannot get an exact number. Apple does not publish search volume on the public App Store. The only first party popularity figure we found is the keyword suggestion tool inside an Apple Ads account, which Apple says displays keyword popularity based on App Store searches. Source: Apple Ads, Keywords best practices. A Reddit reply to a free tools question describes the workaround: “just start creating a campaign without launching or paying for it, you will have a pretty decent keyword tool at your hands there.” (via r/iOSProgramming)

Without an account, use three signals together. None is a volume number. Each is a clue.

• Autocomplete presence. A phrase that Apple suggests is one people search. Absence proves little.
• Modifier habits. The extra words shoppers add show what they want. Free dominates, which is a filter shoppers type, not a keyword every app can honestly own.
• Top 10 size. If the leading apps hold tens of thousands of ratings, many people have installed them for this job. Ratings follow installs, though they lag behind them.

Here is what Apple's autocomplete added to our seeds. We kept only suggestions that were the seed plus one or two plain words, and dropped app-name style suggestions.

Free was the most common extra word, in 37 of 235 clean suggestions. Everything else was far behind.

The second half of the list is where the ideas are. Widget, game and AI each appear as modifiers on different seeds. They point to product angles, such as a widget version or an AI version of a common app, that shoppers already type. Our mobile app ideas list and mobile app idea generator start from the same idea: read what people ask for, then check the competition.

How hard is a keyword to rank for?

Our difficulty proxy is simple. Search the phrase, take the first 10 apps and count how many have under 1,000 ratings. Ratings are public and slow to earn, so a top 10 with several unrated apps tells you that ratings alone do not gate the page. We call a phrase locked with 0 such apps, contested with 1 to 3 and open with 4 or more.

This is a proxy, not Apple's ranking formula. Apple also weighs downloads and text relevance, and we cannot see those. A weak app in the top 10 may rank on a title match alone. That is the point: it shows that a well-matched listing can get in without a large rating history.

Head terms against long-tail phrases

Of 48 head terms, 35% were locked and 25% open. Of 63 long-tail phrases, 10% were locked and 40% open.

Head terms and long-tail phrases behave differently. Head terms split into very hard and fairly open, because some categories are packed and some are thin. Long-tail phrases are rarely locked. They are also rarely worth much on their own, which is why you want several.

Habit tracker is the clearest case. The head term had no weak app in its top 10, and its smallest top 10 app had 2,549 ratings. The phrase “habit tracker widget” had 7 apps under 1,000 ratings and a median of 31. Same product idea, very different door.

Categories are not equal

The median top 10 app in budgeting had about 1,200 ratings. In photo and video it had about 102,800, roughly 87 times more.

This is why category choice beats clever wording. A photo editor competes with apps that hold hundreds of thousands of ratings. A bill reminder competes with apps that hold a few hundred. If you are still choosing what to build, our low competition mobile app ideas and mobile app pain points study rank niches by demand and competition.

Examples across the range

What the title tells you

The exact head term sat in 46.5% of top 10 titles. The exact long-tail phrase sat in only 6.5%.

Competitors name their apps after the head term. Almost none name them after the long tail. A phrase that only appears in a keyword field, or in your subtitle, is rarely matched word for word in rival titles. That is the room a small app can use.

Where should app store keywords go?

Put the strongest phrase in the app name, a supporting phrase in the subtitle and everything else in the keyword field. Apple combines words across fields, so you do not need to repeat a word, and Apple tells you not to. The App Store search page says not to repeat words included in your app name, subtitle or category, and to avoid plurals of words you already used, generic terms such as app or game, filler words such as the and to, and special characters.

Here is a worked example for a made-up app. It is not a real listing. The name and subtitle hold the words in bold. The keyword field then adds words that are not already used, so the store can build phrases such as habit tracker (name plus keyword) and morning routines.

Copy the keyword field and replace the words:

tracker,goal,planner,checklist,self care,morning,wellness,mood,journal,focus,motivation,calm

Keep the commas with no spaces between them. A space inside a keyword, as in “self care”, is fine because it joins words into one phrase. Count bytes, not characters, if you localize into a language with accents or non-Latin script.

In Desktop's Optimize tab, the name and subtitle are counted in characters and the keyword field in bytes, and a field that goes over the limit is refused with a copy of the rule. Every option is measured before it shows numbers. If you localize, the Other languages table measures only phrases you already track.

App Store vs Google Play keywords

Apple gives you a hidden keyword field. Google Play does not. Google publishes limits for the title, short description and full description, and warns against stuffing. Source: Google, Best practices for your store listing.

In practice, App Store work is placement: a few fields, each with a strict budget. Play work is writing: natural sentences that contain your phrases. Google's help page tells you not to repeat your short description in the full one and not to write lists of keywords. The example Google gives of what to avoid is a word block such as car racing, car driving, race cars.

Desktop covers both stores in the same Lab. For Google Play it tracks apps by link or package name, reads Play search ranks to a depth of 30, estimates volume and difficulty from installs and ratings, audits the listing, runs Optimize on the title, short and full description, and exports a fastlane supply zip. Play Console upload is not part of the current release.

Common app store keyword research mistakes

1. Only chasing head terms. 35% of the head terms we tested had no weak app in the top 10. Start with long-tail phrases and the subtitle.
2. Repeating words across fields. A word in the name is already indexed. Spend those bytes on a new word instead.
3. Counting characters, not bytes. A German or Japanese keyword field fills faster than the character counter suggests.
4. Using competitor names. Apple lists competing app names and trademarked terms among the things you must not include. It is a known reason for rejection.
5. Treating one search as the truth. Results differ by country, device and day. Check the storefront your buyers use. Our pricing by country study shows how much storefronts differ.
6. Ignoring the words in your reviews. Users describe your app in their own language. Read it before you pick phrases. See app store review analysis tools, and plan review timing with when to ask for App Store reviews.

Free vs automated: which should you use?

Use the free method if you have one app, a few seeds and an afternoon. Use automation if you run several apps, localize into several languages or re-check often. The cost of the free method is your time, and it grows with every phrase you add.

Desktop is a one-time purchase with no membership. The price rises $1 with every sale, and the current price is on the Desktop pricing page. Lifetime Basic and Pro plans include it. Two honest limits: it does not import from App Store Connect in the current release, and it cannot read your hidden keyword field for that reason. Estimates in the app are labelled estimates.

Once your keywords are set, the screenshot studio in the same Lab builds store screenshots at exact sizes, and our App Store revenue calculator shows what the downloads could be worth. If your app has global buyers, read App Store pricing by country next.

If the question is which app to make, not how to name it, scan a niche in BigIdeasDB before you spend a week on keywords.

Methodology and limits

We label the output a difficulty proxy because it is one. A phrase marked open is a lead worth testing, not a promise of rank. Apple Ads popularity, which needs an account, would add the demand side. Official references: Apple, platform version information, Apple, app information and Google Play Console Help.

FAQ

Keep reading: BigIdeasDB Desktop, App Store pricing by country, the App Store revenue calculator and mobile app ideas backed by data.

Scan your app niche before you pick keywords →

BigIdeasDB Research. (2026). App Store Keyword Research: Free Method + Data. BigIdeasDB. Retrieved from https://bigideasdb.com/app-store-keyword-research