App Store Keyword Difficulty & Search Volume, Explained
Quick answer: Search volume estimates how many people search a keyword; keyword difficulty estimates how hard it is to rank for that keyword against the apps already competing for it. You need both: a high-volume term you can't win is a waste, and a winnable term nobody searches is a waste. The best targets are relevant keywords with real volume and low-to-moderate difficulty. And one honest caveat up front — no ASO tool has perfect volume data, so treat every number as directional.
Last updated: June 2026.
Two numbers sit next to every keyword in every ASO tool: volume and difficulty. They are the most important — and most misunderstood — numbers in App Store Optimization. This guide explains what each one actually measures, how it's calculated (the honest version, including what no tool can know), and how to use the two together to pick keywords you can win.
What is app store search volume?
Search volume is an estimate of how many users search a given keyword in an app store over a period of time, usually expressed as a relative score (often 0–100) rather than an absolute count. It answers a simple question: if I ranked #1 for this term, how much traffic could it send me? A high-volume term has the potential to move installs; a near-zero-volume term, however perfectly it fits your app, can't.
The key word is estimate. Which leads to the part most tools won't say out loud.
How search volume is actually measured (the honest version)
Neither Apple nor Google publishes true organic search volume. So every "volume" number you've ever seen is reconstructed from indirect signals. Here's where it comes from, and how much to trust it:
- Apple Search Ads popularity index. Apple exposes a 1–100 keyword "popularity" score inside its ads platform. It's the closest thing to an official iOS demand signal — but it's tied to advertising, scoped to terms where ads have served, and not a clean organic volume. Useful as a relative gauge, not a literal count.
- Autocomplete position. How early a keyword surfaces in store autocomplete (and how many completions it generates) correlates with how often people search it. A strong proxy.
- Result density and chart presence. How many apps compete for a term, and whether they chart, hints at demand.
- Google Ads web-search data (Android). For Google Play, web-search volume from Google's own ads tooling is a usable proxy — but it's web search demand, not Play Store demand. Every credible tool uses this proxy; the honest ones say so.
The takeaway: iOS organic volume in particular is a multi-signal estimate, not a number Apple hands out. That's not a flaw in any one tool — it's the reality of the platform. The difference between tools is whether they tell you, or hide it behind a confident-looking score. We think you should know, which is why we're upfront that volume is directional and you should validate your most important terms against your own App Store Connect and Play Console data.
What is keyword difficulty?
Keyword difficulty is an estimate of how hard it is to rank on the first page for a keyword, given the apps already competing for it. It's usually a 0–100 composite, where higher means harder. Difficulty answers the other half of the question: even if this term has volume, can I realistically win it?
A new app with a handful of ratings will not out-rank a 4.8-star incumbent with millions of reviews for "photo editor," no matter how good its metadata is. Difficulty quantifies that wall.
How keyword difficulty is calculated
There's no official difficulty score either — tools build a composite from the signals that actually predict how hard a term is. A good difficulty model weighs:
- Title and metadata match among the top results. If the top-ranking apps all have the keyword in their title, the term is contested by committed competitors.
- Ratings strength of the top results. Many high-rated, high-review-count apps competing for a term means a steep climb.
- App age and authority. Established apps with long histories and strong install velocity are harder to displace.
- Chart and category presence. If the top results are also category-chart apps, you're fighting heavyweights.
- Competitor density. How crowded the term is overall — how many relevant apps target it in their metadata.
ASOScan combines several of these signals into a single difficulty score, and we keep the methodology visible rather than asking you to trust a black box. You can see it in action on any app through keyword intelligence.
How to use volume and difficulty together
Plot every candidate on two axes — volume and difficulty — and four zones appear.
| Volume / Difficulty | What it is | What to do |
|---|---|---|
| High volume, low difficulty | The dream — and rare | Target immediately; these are gold |
| High volume, high difficulty | Head terms, heavily contested | Long-term goal; don't lead with these as a new app |
| Low volume, low difficulty | Easy wins, modest traffic | Take a bundle of them — they add up and build authority |
| Low volume, high difficulty | Bad trade | Skip |
The practical strategy for most apps: win a cluster of relevant, low-to-moderate-difficulty long-tail terms now, build ratings and install velocity on them, and let that authority make the harder head terms reachable later. We cover the long-tail approach in keyword research.
Search volume and difficulty for every tracked keyword, side by side.
Relevance is the third axis nobody plots
Volume and difficulty are the famous two, but relevance is the silent third. A high-volume, low-difficulty term that doesn't truly match your app is a trap: you might rank, but the traffic won't convert or retain — and weak conversion and retention now feed back into your rankings (a shift we cover in the 2026 ranking signals). Always filter candidates through "does this honestly describe my app?" before you weigh volume and difficulty.
Why "estimated" is a feature, not an apology
It's tempting to want one confident number. But a tool that presents estimated volume as if it were Apple's own data isn't more accurate — it's just less honest. The professional move is to:
- Treat volume as directional. Use it to compare terms against each other, not as a literal forecast.
- Validate your top terms. Cross-check your most important keywords against your own console data and your read of the market.
- Don't bet the listing on one number. Diversify across a cluster of terms so no single estimate carries your whole strategy.
That's how experienced ASO practitioners actually work, and it's why transparency about data sources matters more than a falsely precise score.
Frequently asked questions
Is app store search volume accurate?
It's an estimate, not an exact count — neither Apple nor Google publishes true organic search volume, so every tool reconstructs it from signals like the Apple Search Ads popularity index, autocomplete, and (on Android) web-search data. Volume is reliable for comparing keywords against each other; treat it as directional rather than literal, and validate your most important terms.
What is a good keyword difficulty score?
For a new or smaller app, target keywords in the low-to-moderate difficulty range and avoid the highest-difficulty head terms until you've built ratings and install velocity. There's no universal cutoff — difficulty is relative to your app's current authority. A score that's "easy" for an established app can be "hard" for a brand-new one.
Should I target high-volume or low-difficulty keywords?
Both, in balance. Start by winning relevant, low-to-moderate-difficulty terms that you can realistically rank for now — including long-tail phrases — then use the authority you build to reach for higher-volume, higher-difficulty terms over time. Leading with unwinnable head terms is the most common new-app mistake.
Why do different ASO tools show different volume numbers?
Because each tool estimates volume from a different blend of signals, and none has Apple's true organic data. Differences between tools are expected. What matters is that the numbers are internally consistent (so comparisons hold) and that the tool is honest about being an estimate.
How is keyword difficulty calculated?
It's a composite of signals that predict competition: how many top-ranking apps have the term in their title, the ratings strength and age of those apps, chart presence, and overall competitor density for the term. There's no official score, so the methodology — and whether the tool shows it to you — is what separates a trustworthy difficulty number from a black box.
