Apple search popularity: the 1–100 index, its top-500 lists, and autocomplete

Every 'search volume' number in ASO descends from one signal: Apple Search Ads' popularity index. Knowing how it is scaled, what Apple publishes and what it omits is the difference between reading demand and reading noise.

The 1–100 index

Apple scores search-term demand per storefront on a relative index from 1 to 100. Since August 2026 the official Apple Ads API publishes it directly (the search term popularity insights dataset): weekly, per storefront, with a second 1–100 score relative to the term's genre, the term's rank within that genre, and the coarse 1–5 tier the Apple Ads console has always shown. It is not a search count and the scale is steeply nonlinear: the gap between 70 and 80 represents far more searches than the gap between 20 and 30, and top generic terms dwarf everything mid-scale. Apple publishes no absolute volumes for it, which makes every third-party "searches per month" figure a model on top of this index, not a measurement.

What Apple leaves out

• Apple publishes only its top ~500 search terms per genre per storefront each week — about 7,500 terms in the US across 15 consumer genres — and only terms with at least 500 searches in the period. Everything below is simply absent, and that is exactly where keyword research lives: the long tail.
• Before the official dataset, the Apple Ads console clamped those terms to a floor value of 5 instead — on the order of 90% of real-world keywords sat there after a mass re-flooring in late 2025. The floor and the omission mean the same thing: below Apple's threshold, not zero demand. Two omitted keywords can differ by an order of magnitude in real searches.
• Coverage is Apple Ads coverage: roughly 90 of the ~175 App Store storefronts. In the rest — Nigeria and Venezuela among them, plus many smaller markets — Apple publishes no demand signal of any kind.
• Absence is information. A term Apple left out scores below the last entry of every full genre list for that storefront, which puts a hard ceiling on its demand — a fact any estimate for it should respect.

Autocomplete as the independent signal

App Store search suggestions are ordered by popularity, which makes autocomplete a measurable, per-storefront demand read that works in every market: probe the prefixes of a keyword (h, ha, hab, …) and record where the full term surfaces. Earlier and higher means more demand. openaso's volume tool blends that probe with rating mass of the top results, competitor count, and title saturation into a transparent estimate — and serves a hybrid: Apple's real index as source: "apple" where Apple published it, the estimate as source: "proxy" where Apple did not, capped under that storefront's cutoff so the estimate can never claim a demand Apple would have listed, and never silently mixing the two.

{
  "keyword": "habit tracker",
  "storefronts": [
    { "country": "US", "popularity": 46, "source": "apple",
      "applePopularity": 46, "floored": false, "estimate": 41 },
    { "country": "NG", "popularity": 23, "source": "proxy",
      "applePopularity": null, "floored": true, "estimate": 23,
      "components": { "autocomplete": 31, "ratings": 18,
        "competition": 24, "titleMatch": 12 } }
  ]
}

The components object is the estimate's whole model, exposed per call — when a proxy number surprises you, the per-signal scores say why, and the suggest tool shows the raw autocomplete lists the probe walked. estimate is always the uncapped independent number; popularity is what you should act on.

Reading popularity honestly

• Compare keywords within one storefront; the index is relative per market, not comparable across countries.
• Treat omitted keywords as below the cutoff, probably small and rank them with the proxy signals instead of discarding them — long-tail keywords with strong autocomplete presence are the classic underpriced targets.
• Demand is necessary, not sufficient: weigh popularity against competition and your realistic rank ceiling before spending metadata budget — the audit tool scores candidates on exactly that triad.

FAQ

Terms

• search popularity — Apple's relative 1–100 keyword demand index per storefront, from Apple Search Ads — the only demand signal Apple publishes, covering its top ~500 terms per genre each week.
• floored keyword — A keyword Apple omits from its published popularity lists (historically clamped to 5) because it falls below Apple's demand threshold — below the cutoff, not zero-demand.
• autocomplete probing — Measuring demand by walking a keyword's prefixes through App Store search suggestions and recording where the term surfaces.

markdown mirror: /reference/search-popularity.md · full corpus: /llms-full.txt