# App Store keyword research & Google Play ASO keyword ideas (`petersutarik/aso-keyword-finder`) Actor

ASO keyword tool for App Store and Google Play keyword research: turn seed keywords or any app into keyword ideas with keyword popularity (Apple's own Search Popularity on iOS), keyword difficulty and an opportunity score. Built by the team behind trysonar.app.

- **URL**: https://apify.com/petersutarik/aso-keyword-finder.md
- **Developed by:** [Peter Šutarík](https://apify.com/petersutarik) (community)
- **Categories:** SEO tools, Developer tools, Marketing
- **Security:** Limited permissions
- **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$20.00 / 1,000 keyword idea with popularity & difficulties

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## App Store keyword research & Google Play ASO keyword ideas

An **ASO keyword tool** for **App Store and Google Play keyword research**: turn a few **seed keywords**, or **any app** — yours or a competitor's — into a list of **keyword ideas**, each with **keyword popularity**, **keyword difficulty** and an **opportunity score**. No account, no API key, no setup: enter seeds or an app ID, run, and sort by opportunity.

Built by the team behind [Sonar](https://trysonar.app), the ASO keyword tool for indie iOS and Android developers. It runs on the same production data the tool itself uses, and on iOS that includes Apple's own Search Popularity.

### What does this ASO keyword research tool give you?

| Field | What it tells you |
|-|-|
| **Keyword ideas** | Your seeds plus the store's own autocomplete suggestions for them — the phrases people actually type |
| **Popularity** (5–100) | How much the keyword is searched. On iOS it's Apple's own Search Popularity wherever Apple reports one |
| **Difficulty** (0–100) | How hard it is to reach the top results, from the strength of the top 10 apps |
| **Opportunity** (0–100) | Low difficulty weighted by popularity — sort by this to find keywords worth targeting |
| **Est. downloads at #1** | Rough downloads/day the #1 app gets from the keyword (iOS, real Apple popularity only) |
| **Title matches / beatable** | How many top-10 apps have the keyword in their title, and whether a top-3 slot looks winnable |
| **Where it came from** | The seed, suggestion or app each idea came from |

### How to find App Store and Google Play keywords for your app

1. **Add seed keywords** (up to 20) — words that describe your app, like `meditation` or `sleep sounds`.
2. **Or add apps** (up to 10) — your own app or a competitor's. The actor reads each app's name and description, removes the noise ("https", "subscription", stopwords), and uses the strongest terms as seeds. Use the App Store ID (`571800810`), the bundle ID or Android package name (`com.calm.android`), or just paste the store URL.
3. **Pick the store and country** — App Store, Google Play or both, in any of 72 markets.
4. **Run, then sort by `opportunity`.** High popularity with low difficulty floats to the top.

Each seed returns up to 10 ideas (the seed itself plus up to 9 suggestions). For more long-tail ideas from the same seeds, set **depth 2**: the actor then searches the best suggestions too, best opportunity first, until it reaches your maximum.

Use **minimum popularity** and **maximum difficulty** to keep only the keywords you'd target. Keywords outside your filters are not stored and not charged.

### Use cases

- **Pre-launch keyword research** — find the keywords to put in your title, subtitle and keyword field before you ship
- **Competitor keyword mining** — enter a competitor's app ID and see which of its terms are searched and which are winnable
- **Cross-store research** — use your iOS app's metadata to seed Google Play research, or the other way round
- **Localization** — run the same seeds in another country to see which keywords carry over
- **AI agents & pipelines** — call it via the Apify API and get clean, typed JSON rows

### Input example

```json
{
    "seedKeywords": ["meditation", "sleep sounds"],
    "appIds": ["571800810"],
    "store": "ios",
    "country": "us",
    "maxKeywords": 50,
    "depth": 1,
    "seedsPerApp": 5,
    "minPopularity": 0,
    "maxDifficulty": 100
}
```

With `store: "both"`, each store gets its own list of up to `maxKeywords` ideas, and app seeds are used in both stores.

### Output example

One dataset row per keyword idea:

```json
{
    "type": "keyword",
    "keyword": "meditation timer",
    "store": "ios",
    "country": "us",
    "source": "suggestion",
    "seed": "meditation",
    "appId": null,
    "appName": null,
    "popularity": 37,
    "popularitySource": "apple",
    "popularityApple": 37,
    "popularityProxy": null,
    "difficulty": 44,
    "opportunity": 15,
    "estDownloadsAt1": 170,
    "resultsCount": 200,
    "titleMatches": 6,
    "beatable": false,
    "measuredAt": "2026-10-28T01:12:49.373Z",
    "stale": false,
    "checkedAt": "2026-10-28T10:55:41.264Z"
}
```

| Field | Meaning |
|-|-|
| `source` | `seed` = one of your keywords, `app` = a term from an app's metadata, `suggestion` = store autocomplete |
| `seed` | The search that found the keyword (the keyword itself for seeds) |
| `appId`, `appName` | The app whose metadata the seed came from, else `null` |
| `popularity` | Search popularity, 5–100 |
| `popularitySource` | `apple` = Apple's own reading, `proxy` = Sonar's estimate (always the case on Google Play) |
| `popularityApple` | Apple's own reading on iOS; `5` means below Apple's threshold. `null` on Google Play |
| `popularityProxy` | Sonar's estimate for a keyword Apple reports as 5 |
| `difficulty` | How hard it is to reach the top results, 0–100 |
| `opportunity` | `(100 − difficulty) × (popularity / 100)^1.3`, 0–100. The exponent keeps easy keywords nobody searches from ranking first |
| `estDownloadsAt1` | Estimated downloads/day for the #1 app — a rough order of magnitude, iOS only, `null` without a real Apple reading |
| `resultsCount` | How many apps the store returns for the keyword |
| `titleMatches` | How many of the top 10 apps have the keyword in their title |
| `beatable` | `true` when a top-3 slot looks winnable |
| `measuredAt` | When the store search behind `difficulty` was read |
| `stale` | `true` when the values are 7 or more days old (they're refreshed in the background) |
| `error` | Only on keywords that couldn't be measured in this run — these rows are not charged |

### Pricing (pay per event)

| Event | Price | Meaning |
|-|-|-|
| `keyword-idea` | $0.02 | One keyword idea with popularity, difficulty and opportunity |

You pay only for the keyword ideas the run stores — no platform usage on top, so the event price is the whole bill.

**Example:** 2 seed keywords on the App Store at depth 1 return about 15–20 ideas, so about $0.30–0.40. The default maximum of 50 ideas per store costs at most $1.00; with `store: "both"`, at most $2.00.

Not charged: keywords outside your filters, app-name suggestions the actor skips, duplicates, and keywords returned with an `error`. The run respects your maximum charge: once it's reached, the run stops and nothing beyond it is stored or charged.

### Related actors

- [App Store & Google Play ASO keyword rank tracker + popularity](https://apify.com/petersutarik/aso-keyword-intel) — use it once you've picked your keywords: it checks where your app and your competitors rank for each one, and on a daily schedule it builds a ranking history.
- [App Store top charts & Google Play top charts scraper](https://apify.com/petersutarik/app-store-top-charts) — use it to see which apps lead the top free, paid and grossing charts in your category, with daily movement.

### FAQ

**Where does the popularity score come from?** From [Sonar](https://trysonar.app). On iOS it's Apple's own Search Popularity — the same number Apple shows advertisers — wherever Apple reports a real value. Apple reports every keyword below its lowest real reading as 5; for those keywords `popularityApple` is 5 and `popularity` is Sonar's estimate inside that hidden band, so you can still tell a long-tail keyword with some searches from one nobody types. On Google Play, popularity is Sonar's estimate from store autocomplete and the strength of the top apps.

**How is this different from autocomplete scrapers?** Autocomplete tells you which phrases exist. This actor adds how much each one is searched, how hard it is to rank for, and an opportunity score, so you can decide which keywords to target instead of guessing.

**Why do some ideas look like app names?** App Store autocomplete also suggests app titles. The actor skips the ones with title punctuation ("sleep sounds: calm rain, white noise, nature, fan") and doesn't charge for them. Turn on **Include app-name suggestions** to keep them.

**Why did I get fewer keywords than my maximum?** Each seed returns up to 10 ideas, and filters and duplicates remove some. Add more seeds, add an app, or set depth 2.

**Why does a keyword come back with an `error`?** A keyword Sonar has never measured is computed during the run. The run waits for it (up to about 3 minutes); if it still isn't ready you get a row with `error` set and no charge, and the next run returns its values.

**Which countries are supported?** Sonar's 72 keyword-research markets — the US, UK, Canada, Australia, most of Europe, Japan, Korea, India, Brazil, Mexico and more (Google Play: all except China).

**How fresh is the data?** Values measured in the last 7 days are returned as they are, older ones come back with `stale: true` and are refreshed in the background, and keywords Sonar has never seen are measured during the run.

**Can I track where my app ranks for these keywords?** Yes — feed the keywords you pick into the [App Store & Google Play ASO keyword rank tracker](https://apify.com/petersutarik/aso-keyword-intel) and put it on a schedule. For alerts, competitor tracking and an MCP server for AI agents, see [Sonar](https://trysonar.app).

**Can I use it from the API or an AI agent?** Yes, like any Apify actor: start a run via the API and read the dataset as JSON or CSV.

**Something not working?** Open an issue in the Issues tab — this actor runs on our own product's data, so it's actively maintained.

# Changelog

This Actor's version history is a separate document: https://apify.com/petersutarik/aso-keyword-finder/changelog.md

# Actor input Schema

## `seedKeywords` (type: `array`):

Words that describe your app, to start the keyword research from (up to 20). Each seed is searched on the store: you get the seed itself plus the store's autocomplete suggestions for it, each with popularity, difficulty and an opportunity score. Add seed keywords, app IDs, or both.

## `appIds` (type: `array`):

Find keywords from an app's listing — your own or a competitor's (up to 10). The actor reads each app's name and description, keeps the strongest terms as extra seeds, and researches them like seed keywords. Use the numeric App Store ID (571800810), the iOS bundle ID or Android package name (com.calm.android), or the store URL. An App Store app can seed Google Play research and vice versa.

## `store` (type: `string`):

Which store to research. With Both, each store gets its own keyword list (up to the maximum below per store).

## `country` (type: `string`):

The storefront to research. Covers Sonar's 72 keyword-research markets (Google Play: all except China).

## `maxKeywords` (type: `integer`):

The most keyword ideas to store (and charge) per store. Each seed yields up to 10 ideas; use depth 2 or more seeds to reach larger numbers.

## `depth` (type: `integer`):

1 = your seeds and their suggestions. 2 = also search each suggestion for its own suggestions (best opportunity first) until the maximum is reached — more long-tail ideas from the same seeds.

## `seedsPerApp` (type: `integer`):

How many terms to take from each app's metadata as seeds. Noise (stopwords, URL fragments, boilerplate like "subscription") is removed first.

## `minPopularity` (type: `integer`):

Only keep keywords with at least this popularity (0–100). Keywords below it are not stored and not charged. Keywords with unknown popularity are dropped once this is above 0.

## `maxDifficulty` (type: `integer`):

Only keep keywords with at most this difficulty (0–100). Keywords above it are not stored and not charged.

## `includeAppNames` (type: `boolean`):

App Store autocomplete also suggests app titles, like "sleep sounds: calm rain, white noise, nature, fan". They're skipped (and not charged) by default because nobody targets them as keywords. Turn this on to keep them.

## Actor input object example

```json
{
  "seedKeywords": [
    "meditation",
    "sleep sounds"
  ],
  "store": "ios",
  "country": "us",
  "maxKeywords": 50,
  "depth": 1,
  "seedsPerApp": 5,
  "minPopularity": 0,
  "maxDifficulty": 100,
  "includeAppNames": false
}
```

# Actor output Schema

## `overviewDatasetUrl` (type: `string`):

Keyword ideas — keyword, popularity, difficulty, opportunity and where each came from.

## `datasetUrl` (type: `string`):

Every field per keyword idea, incl. Apple's own popularity reading, estimated downloads at #1 and difficulty details.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "seedKeywords": [
        "meditation",
        "sleep sounds"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("petersutarik/aso-keyword-finder").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "seedKeywords": [
        "meditation",
        "sleep sounds",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("petersutarik/aso-keyword-finder").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "seedKeywords": [
    "meditation",
    "sleep sounds"
  ]
}' |
apify call petersutarik/aso-keyword-finder --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,petersutarik/aso-keyword-finder"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/C6XPxMi5qpbPHwyO7/builds/OzZ5o07ZUd9gykcgI/openapi.json