# ASO Insights — AI App Store Optimization from Any Scraper (`fuze/aso-insights`) Actor

Point it at any App Store / Google Play scraper's dataset (your app + competitors) and get AI ASO advice: keyword gaps, title/subtitle/description rewrites, category positioning and what top-ranked competitors do differently.

- **URL**: https://apify.com/fuze/aso-insights.md
- **Developed by:** [Fredrik Hansson](https://apify.com/fuze) (community)
- **Categories:** AI, SEO tools
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $154.00 / 1,000 aso reports

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## ASO Insights — AI App Store Optimization from Any Scraper

Already scraping the App Store or Google Play? Turn listings into a ranking plan. Point this at **any app-store scraper's dataset** (your app + competitors) and get AI ASO advice.

![ASO Insights — AI App Store Optimization from Any Scraper — input and sample output](https://datatools-hub.vercel.app/actor-shots/aso-insights.png)

### 🔗 Chain it after your scraper

Already scraping with **[Apple App Store Scraper (`automation-lab/apple-app-store-scraper`)](https://apify.com/automation-lab/apple-app-store-scraper)**, **[App Store Scraper (`epctex/appstore-scraper`)](https://apify.com/epctex/appstore-scraper)** or **[Google Play Data Extractor (`epctex/google-play-scraper`)](https://apify.com/epctex/google-play-scraper)**? Pipe the dataset straight in — paste its dataset ID (your app plus a few competitors) and get keyword gaps, title/subtitle/description rewrites and category positioning. Works with any App Store or Google Play scraper's output.

### What you get

- **Keyword gaps** — valuable terms competitors use that you're missing
- **Title & subtitle** rewrite suggestions
- **Description advice**
- **Category positioning** and **what top competitors do differently**
- Prioritized **recommendations**

### How to use

1. Run any App Store / Google Play scraper on Apify for your app and a few competitors.
2. Copy its **dataset ID**.
3. Run this actor with that `datasetId` (and your app name).

```json
{ "datasetId": "YOUR_APPS_DATASET_ID", "yourApp": "My Budget App" }
```

### Pricing

Pay per ASO report — one cost-effective AI pass over the listings.

Actively maintained.

### Example output

```json
{
  "yourApp": "MyBudget",
  "appsAnalyzed": 3,
  "summary": "To improve your app's visibility and rank higher against competitors like Mint and YNAB, focus on incorporating missing keywords into your…",
  "keywordGaps": [
    "money management",
    "financial planning",
    "savings goals",
    "…"
  ],
  "titleSuggestions": [
    "MyBudget — Smart Expense Tracker & Financial Planner",
    "MyBudget: Simple Money Management and Spending Tracker"
  ],
  "subtitleSuggestions": [
    "Track Your Expenses and Savings Goals",
    "Effortless Budgeting and Bill Tracking"
  ],
  "descriptionAdvice": [
    "Incorporate key features such as money management, savings goals, and financial planning to attract users looking for comprehensive soluti…",
    "Highlight ease of use and user-friendly design in your description to appeal to your target audience.",
    "Include information on how MyBudget can help users achieve their financial goals more effectively than competitors."
  ],
  "competitorEdge": [
    "Your app currently emphasizes simplicity, which is a strong edge over competitors who may offer complex features.",
    "Focus on user experience; consider better reviews on ease of use compared to Mint and YNAB."
  ],
  "…": "…"
}
```

# Actor input Schema

## `datasetId` (type: `string`):

The dataset ID from any App Store / Google Play scraper's run — ideally your app and a few competitors. The actor auto-detects title, subtitle, description, category and rating fields.

## `yourApp` (type: `string`):

If set, the advice is written for this app vs the others in the dataset.

## `maxApps` (type: `integer`):

Cap on how many app listings to read.

## `model` (type: `string`):

gpt-4o-mini is the cost-effective default.

## Actor input object example

```json
{
  "maxApps": 30,
  "model": "gpt-4o-mini"
}
```

# Actor output Schema

## `results` (type: `string`):

All rows in the default dataset.

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("fuze/aso-insights").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("fuze/aso-insights").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 '{}' |
apify call fuze/aso-insights --silent --output-dataset

```

## MCP server setup

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

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/5ILCpPnd7JDGO1Qfc/builds/huoQTL5gvXUSNU4r0/openapi.json