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    Apple Search Popularity Scores Don’t Predict Installs. Test Keywords

    Marketer testing a search term on smartphone

    Apple search popularity indicates interest in App Store search terms. Apple provides keyword popularity information, but the available data may not include every term. Treat Apple’s relative scores and your own App Analytics data as your priority indicators, then confirm every keyword bet with a controlled test before you commit.

    TL;DR:

    • Apple’s 1 to 100 popularity scores cover only a limited set of terms; estimates from other tools are proxies, not Apple’s actual search counts.
    • The keyword field holds 100 characters, so prioritize terms that describe the app before weighing popularity, conversion likelihood, and ranking difficulty.
    • App Analytics search impressions, conversion rates, downloads, and retention show whether a keyword attracts people who install, while popularity alone cannot predict results.
    • Localized keywords appear according to customers’ language settings, so compare page views, installs, and retention by territory before investing in a market.
    • Test one metadata change at a time over matching periods, then retain terms that improve results; daily rank tracking can support weekly reviews.
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    Table of Contents

    What Apple publishes about apple search popularity and its limits

    Apple does not hand developers a table of global search volumes. What exists is relative popularity information, scored 1 to 100, for a limited set of top terms. For the long tail, where most useful keywords live, there is no official number. Any “search volume” you see for those terms in third-party tools is an inferred proxy, and you should label it that way in your own notes.

    The constraint that shapes your decisions most is space. The keyword field is limited to 100 characters, with terms separated by commas. That forces a choice for every term you consider.

    • Relative scores: use them to rank candidates against each other, not to forecast installs.
    • Missing data: a keyword with no score is not a dead keyword, only an unmeasured one.
    • Character budget: every character spent on a weak term is a character a stronger term cannot use.
    • Third-party volume: useful for direction, never a fact about Apple’s actual search counts.

    Apple also notes that search results draw on text relevance and customer behavior, so popularity alone never decides who ranks.

    Where to find Apple’s popularity signals and how to access them

    Apple’s own tools give you partial but real data. Start with the ones tied to your app, then look at API-level access.

    1. App Store Connect and App Analytics. Check search impressions, conversion rates, and downloads for your own app. This is the closest thing to first-party demand data you will get.
    2. The Search Term Popularity Query. Apple documents a Search Term Popularity Query for programmatic access to popularity data. Read the documentation to see what it returns for your markets before you build anything around it.
    3. Localization settings. If you add metadata for a language, users with matching language settings see that localization, and localized keywords display in regions that support that language. Edit keywords per locale, not once for everyone.

    Together these show what users see, what they search, and what they do after they find you.

    Estimating popularity when Apple doesn’t publish raw volumes

    When raw numbers are missing, your own funnel becomes the best evidence. Search impressions tell you how often your listing surfaces, conversion rate tells you whether the people who see it want it, and installs close the loop. Apple points developers to App Analytics for discovery and conversion metrics, and that is where proxies should start.

    • Use relative scores where Apple provides them. They are the only official popularity signal.
    • Label third-party numbers as estimates. Write “inferred” next to them in your keyword sheet so nobody mistakes them for Apple data.
    • Test before you commit. Run metadata experiments and custom product pages to see whether a term drives conversions. Apple’s own advertising guidance says keyword suggestions show popularity based on App Store searches, which makes paid discovery a reasonable way to probe a term cheaply.
    • Read behavior, not just volume. A keyword with modest traffic and strong conversion can beat a popular term that attracts the wrong people.

    Pro Tip: When you cannot measure a keyword’s demand, measure what happens after you add it. A consistent measurement window with one change at a time is more useful than relying on an estimate.

    Our free tools are one way to compare inferred competition for candidates before you spend a test slot on them.

    How to use popularity in keyword choice and prioritization

    Popular terms bring volume and competition together. Apple describes this trade-off directly: high-popularity functional terms are competitive, while less common terms have lower traffic and less competition. The same guidance says to choose words users might use to find apps like yours and be specific about features. Relevance comes first, and popularity only matters once a term actually describes your app.

    Rank candidates in this order: relevance, then relative popularity, then expected conversion, then localization fit. A simple scoring checklist keeps the team honest:

    • Relevance: does the term describe what the app does, in the words users would pick?
    • Popularity signal: Apple’s relative score if it exists, a labeled proxy if it does not.
    • Conversion likelihood: would someone searching this term plausibly install?
    • Localization priority: is there a market where this term matters more?
    • Ease of ranking: how crowded are the top results?

    Score each from one to five, add them up, and ship the top few. The numbers are crude on purpose. Their job is to end debates, not to predict outcomes. For a deeper walkthrough, our keyword research process covers each step in more detail.

    Localization and market differences in search popularity

    Popularity signals differ across three markets

    A keyword that works in one territory can fall flat in another, even within the same language. Apple shows localized metadata based on each user’s language settings, so your keyword field is effectively a different asset in every locale.

    Apple’s localization guidance explains that App Analytics can be filtered by territory to compare Product Page Views, App Units, and Active Devices across markets. Use that to decide where translation pays off.

    • Look for demand you already have. Territories with page views and installs from an unlocalized listing are natural first picks.
    • Check retention, not just downloads. A market that installs and leaves is a weak bet.
    • Never copy keywords across locales. Translate for how people search, not word for word.
    • Expect uneven results. Popularity is not uniform across the globe, and your plan should not assume it is.

    Our localization guide goes deeper on multi-market planning.

    Monitoring popularity and measuring impact

    Keyword choices only matter if you can see whether they worked. Pick a small set of metrics and review them on a fixed schedule.

    1. Search impressions, conversion rate, downloads, and retention. These are the core indicators, and App Analytics reports discovery and conversion metrics for most of them.
    2. Daily rank tracking with weekly reviews. Let a tracker watch positions every day, then sit down once a week to decide what to keep, drop, or retest.
    3. A consistent measurement window. After a metadata change, compare the same length of time before and after, and avoid stacking other changes on top.
    4. Attribution where possible. Use A/B tests or staged rollouts so a lift can be tied to the change rather than to seasonality.

    Actionable workflow: from popularity signals to keywords you ship

    This is the loop we recommend for turning partial signals into shipped changes.

    1. Gather signals. Pull search impressions and conversion data from App Analytics, and check Apple’s relative popularity where the Search Term Popularity Query covers your terms.
    2. Score and shortlist. Rate candidates on relevance, relative popularity, and likely conversion, using the checklist above, and keep the list short enough to test.
    3. Run controlled tests. Use custom product pages, A/B tests, or keyword field updates, and change one thing at a time so results stay readable.
    4. Iterate and localize. Keep what wins, drop what does not, and carry winners into your highest-priority markets.

    Pro Tip: Keep a running log of every keyword change with its date and result. Over time, it becomes your own private popularity dataset, built from your actual users.

    If you want the finished checklist for the shipping step, our listing optimization checklist covers it.

    Why I would rather test than chase volume

    Apple’s data is partial, and no workaround changes that. I have seen teams lose weeks arguing over estimated volume numbers that nobody could verify. The teams that gain ground ship small changes often, measure each one, and keep what the data supports. Popularity scores tell you where to look first. Your own results tell you what is true.

    — Samuel

    How we help you act on App Store popularity signals

    We built appXL to run this workflow for you. We monitor keywords, rewrite metadata, localize listings into multiple languages, and track rankings daily, then ship the changes straight to App Store Connect, so the testing loop does not depend on someone finding spare hours. You can start with our free tools, see our Starter, Growth, and Scale plans, or try appXL and let us handle the next round of keyword updates.

    Appxl

    FAQ

    What does Apple search popularity mean for ASO?

    It means how often users search a keyword in the App Store. Apple shares it mainly as relative information for a limited set of terms, not as raw counts for every keyword.

    Does Apple publish exact search volumes for keywords?

    No. Apple documents a Search Term Popularity Query for popularity data, but exact volumes for most long-tail terms are not public. Third-party volume figures are inferred.

    How many characters can I use for App Store keywords?

    The keyword field holds 100 characters, with terms separated by commas. Spend those characters on relevant terms with the best mix of popularity and ease of ranking.

    Not by default. Popular terms bring traffic but face heavy competition, so relevance comes first. Test a mix of popular and specific terms, then keep what converts.

    Sources

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