App Store Keyword Research: Find Keywords and Read Popularity

In short: Apple does not publish App Store search volume. The only first-party demand signal is search popularity from Apple Ads (1 to 5 in the Apple Ads interface, 5 to 100 in most ASO tools), and since late September 2025 most long-tail terms sit at the floor value of 5. Good App Store keyword research therefore combines popularity with autocomplete, the strength of the apps already ranking, and your own data, then picks keywords by relevance × popularity ÷ difficulty.

Most keyword advice borrowed from web SEO starts with a monthly search volume column. In the App Store that column does not exist, and tools that show one are estimating it. That is not a reason to guess. It means you need to know exactly which signals Apple gives you, how reliable each one is, and how to combine them into a decision.

This guide covers the signals, the difficulty check, a scoring heuristic and a full worked example. If you want the mechanics of the fields themselves (name, subtitle, the 100-byte keyword field), read our companion guide on App Store keywords after this one.

Why "App Store search volume" does not exist

Apple has never released query counts for App Store search. Two places come close, and both are easy to misread.

App Store Connect Analytics shows how people found your app. Its acquisition source types include "App Store search", defined as users who viewed or downloaded your app from search on the App Store, including views and downloads from ads in search results. You get impressions, product page views, downloads and conversion rate for that source. You do not get the search terms: the filters and dimensions reference offers source type, app referrer and web referrer, but no query dimension. As of October 2026, App Store Connect does not tell you which words brought people to you.

Apple Ads is where Apple exposes search demand, as a relative score called search popularity. Everything else in App Store keyword research is built around that score and its gaps.

Search popularity: Apple's only first-party demand signal

Where Apple shows it

• Apple Ads keyword suggestions. When you add keywords to an ad group, the suggestion tool shows popularity "based on App Store searches" as five circles: the more circles filled, the more popular the term.
• Apple Ads reports and Recommendations. The reporting definitions state that search popularity "is displayed as numbers from 1 to 5, with 5 being the most popular", and it appears next to impression share and rank in the predefined Impression Share reports.
• The Apple Ads Platform API. The Search Term Popularity Query endpoint returns the most popular search terms for an App Store genre and country, weekly or monthly. Its fields include searchPopularity1to5, searchPopularity1to100, rankInGenre and searchPopularityInGenre. It is built for discovering high-volume terms in a genre, so do not expect it to cover every long-tail phrase you care about.

You can open an Apple Ads account and look up popularity without spending anything on a campaign.

1 to 5 versus 5 to 100

Two scales describe the same signal, and mixing them up causes most of the confusion:

• 1 to 5 is what Apple shows people in the Apple Ads interface. A 1 to 5 score is coarse: a "3" covers a wide band of demand.
• 5 to 100 is the finer number most ASO tools have displayed for years. On that scale the lowest value Apple returns is 5, not 0 or 1. Apple's own Platform API now also documents a 1 to 100 field.

When a tool says "popularity 42", it is on the 100-point scale. When an Apple Ads screen shows three of five circles, it is the coarse scale. Neither is a search count. Both are relative: a 60 is clearly more searched than a 30, but you cannot say it is twice as many searches.

The floor value of 5

On the 100-point scale, 5 means "too few searches for Apple to report a number". That has always been true of rare searches. What changed is how many keywords sit there. ASO.dev reported that starting September 29, 2025, the number of US keywords with popularity above 5 fell from 165,875 to 39,254, about 77 percent, and that Apple's endpoint now returns 5 for most queries. As of its last update in August 2026, the article reports no recovery. This is a practitioner measurement, not an Apple announcement, but it matches what we see in Searvia's own data.

Practical consequence: a 5 is "unknown", not "zero". A keyword stuck at 5 can still bring real installs. In Searvia, keywords at the floor are labeled "Apple: 5" with our own estimate of where they sit, for example "Apple: 5 · est. 6–29", so you can still compare them. The Apple popularity guide explains how to connect Apple Ads and read those labels.

Estimating long-tail demand without a number

For everything at or near the floor, combine several imperfect signals. None of them is a search count, but together they rank candidates well enough to decide.

1. App Store search suggestions. Type the first letters of a phrase into App Store search on a device set to the target country and watch the suggestions. In our experience, a phrase that appears after two or three letters is searched often, and one that only appears once you type most of it is rare. Note the order of suggestions and the variants people add ("habit tracker widget", "habit tracker for adhd").
2. The strength of the apps already ranking. Look at the top 10 for the term. If they have tens or hundreds of thousands of ratings, the term carries heavy traffic, because big apps accumulate ratings from big traffic. If the top 10 is a mix of small, unrelated apps, demand is probably thin, or nobody has targeted it yet.
3. Apple Ads search terms. If you run ads with broad match or Search Match, the search terms report lists the real queries that triggered your ads. Apple applies a privacy threshold: in the Apple Ads interface a search term needs at least 10 impressions per day, otherwise it shows "low volume", and the API documentation says low-volume terms may be suppressed or aggregated. Any term that clears the threshold is proven demand.
4. Your own App Store search numbers. In App Store Connect, impressions and downloads from the App Store search source show whether a metadata change brought more search traffic in total. It cannot attribute traffic to a term, so pair it with rank tracking.
5. Google search volume, as a weak tie-breaker. Web searches have different intent (reviews, "best of" lists, how-to), so use Google numbers only to break ties between candidates that look equal in App Store signals.

Signals at a glance

How to judge keyword difficulty

Difficulty is the question "could my app realistically reach the top 10, and how long would it take?" Check the top 10 results for:

• Rating counts. The most useful single number. If every app in the top 5 has 50,000+ ratings and yours has 300, the head term is out of reach for now.
• Exact-match titles. Count how many top apps have the phrase in their name. Apple lists text relevance (title, subtitle, keywords and primary category) and user behavior (downloads, ratings and reviews) as ranking factors. When many leaders match the phrase in their name and have strong user signals, both levers are taken.
• Relevance of the results. If the top results do not really match the query (a meditation app ranking for "sleep sounds for babies"), Apple has no strong candidates. These are openings.
• Freshness. Apps that have not been updated in a year or two and still rank tend to be easier to pass than actively maintained ones.
• Number of results. A query that returns only a few dozen apps is usually both rare and easy.

Searvia's difficulty score (0 to 100) is built from these same inputs: ratings of the top apps, how many use the keyword in their name, app age and update dates. Hover the badge to see which factor drives it.

A prioritization heuristic: relevance × popularity ÷ difficulty

With popularity and difficulty in hand, score each candidate. A simple heuristic works well:

Priority = relevance × popularity ÷ difficulty

• Relevance, 0 to 3: 3 means the searcher wants exactly what your app does, 2 a close fit, 1 loosely related, 0 not relevant. Anything below 2 rarely converts, however popular.
• Popularity, the 5 to 100 score, or your estimate for floor terms.
• Difficulty, 1 to 100, from the checks above.

This is a ranking aid, not a law. It pushes you toward terms people search, that you can win, and that turn searchers into users. Searvia uses a related formula for its Opportunity column, popularity × (1 − difficulty²) with difficulty on a 0 to 1 scale, which punishes very hard keywords more steeply.

Golden keywords are the sweet spot. In Searvia a keyword counts as golden when popularity is at least 30, difficulty is at most 45, it is not another company's brand, and it is relevant to your app. The golden keywords guide shows how to filter for them.

Step-by-step workflow with a worked example

Here is the full process for a hypothetical habit tracker called Streakly, launching in the US App Store with about 400 ratings. Every number below is illustrative, chosen to show the method; do not read them as real data for these terms.

Step 1: Write a seed list

List words from four angles: what the app does (habit tracker, streaks, routine), the problem it solves (procrastination, consistency), who it is for (students, ADHD), and the words competitors use in their names and subtitles. Aim for 30 to 60 seeds.

Step 2: Expand with search suggestions

Type each seed into App Store search and record the suggestions. For Streakly this surfaces phrases like "habit tracker widget", "daily routine planner" and "streak app".

Step 3: Score popularity

Look up each phrase in Apple Ads or a keyword tool. Mark floor values (5) separately so you remember they are unknown, not empty.

Step 4: Check difficulty and relevance

Open the top 10 for every phrase with popularity above the floor, plus the most promising floor terms. Note rating counts, exact-match titles and how relevant the results are.

Step 5: Prioritize

"Habit tracker" is the most relevant head term, but at difficulty 85 Streakly will not reach page one soon. "Habit tracker widget" scores highest and is golden by Searvia's rule (popularity 34, difficulty 40, relevant, not a brand). "Streak app" sits at Apple's floor, but suggestions show it after a few letters and the top 10 is weak, so it earns a slot. "Self care" is popular but loosely relevant, so it drops.

Step 6: Place the words

Put the highest-priority words in the name and subtitle, since Apple names title and subtitle among the fields it matches for text relevance. Fill the rest into the keyword field: Apple allows up to 100 bytes, with terms separated by commas and no spaces, and asks you not to repeat words already in your name, subtitle or category. The name and subtitle are each limited to 30 characters.

For Streakly that could be:

• Name: Streakly: Habit Tracker (23 characters)
• Subtitle: Daily Routine & Streak Widget (29 characters)
• Keyword field: planner,goals,checklist,adhd,students,reminder,motivation,consistency,focus,todo,journal

The phrase "habit tracker widget" is formed from words across the name and subtitle, so it does not need its own entry. Before submitting, run each target phrase through the free App Store keyword checker to see its popularity, difficulty and the current top 10.

Step 7: Track and iterate

Track every target keyword daily from release. After two to four weeks, keep the words that moved you into the top 10 or top 20, and swap out words that did nothing. You can spot-check any keyword and country for free with the App Store rank checker; daily tracking shows the trend.

Common mistakes

• Treating 5 as zero. Since the 2025 change, a 5 hides plenty of real demand. Estimate it instead of discarding it.
• Chasing head terms first. A new app with a few hundred ratings rarely ranks for the category's biggest word. Win specific phrases, collect downloads and ratings, then move up.
• Repeating words. Apple tells developers not to repeat words from the name and subtitle in the keyword field. Repeats waste bytes.
• Using competitor brand names. Apple's keyword field rules say names of other apps or companies aren't allowed, and brand searchers rarely convert anyway.
• Researching only one storefront. Every country has its own popularity and its own competitors, and many storefronts search more than one localization. See App Store localization for extra keyword space per country.
• Changing everything at once. If you swap all your keywords in one release, you cannot tell which change helped.

How Searvia handles App Store keyword research

Searvia runs this workflow for you. Keyword research pulls Apple's search suggestions for a seed word, shows what a competitor ranks for and lifts phrases from competitor listings; every row comes with popularity (Apple's official score when you connect Apple Ads, otherwise a labeled estimate), difficulty and opportunity, and you can filter to golden keywords and track them in one click. Tracked keywords are checked daily, so after each release you can see which words actually moved. Start with the free keyword checker, then create a free account when you want the history.