Apify Store Market Analyzer

Analyze public Apify Store Actor data for competitive intelligence, pricing research, category demand, ratings, growth signals, and marketplace gaps. The Actor collects comparable Store records and can generate an SEO opportunity report for deciding what to build next.

Features

• Collects public Actor metadata from the supported Apify Store API
• Uses stable 1,000-record pagination, retries, and Actor-ID deduplication
• Supports full-store, category, top-performer, eligibility, and idea-discovery modes
• Filters Actors by total users, total runs, pricing model, and opportunity score
• Extracts pricing, categories, ratings, bookmarks, usage, and developer information
• Generates a separate SEO opportunity report with recent-demand niches, title keywords, phrases, and growth signals
• Provides focused dataset views and a STATS run summary

Use Cases

• Actor opportunity research: identify demand with limited quality supply
• Competitive intelligence: compare products, adoption, pricing, and ratings
• Store SEO research: discover recurring terms used by successful Actors
• Pricing strategy: compare monetization models across relevant categories
• Portfolio planning: prioritize Actor ideas using structured marketplace evidence

Input

{
  "mode": "byCategory",
  "categories": ["AI", "AUTOMATION"],
  "maxActors": 500,
  "minTotalUsers": 10,
  "includeAnalytics": true
}

Output

Each standard dataset row represents one public Actor record:

{
  "name": "example-actor",
  "title": "Example Actor",
  "username": "developer",
  "categories": ["AI", "AUTOMATION"],
  "stats": {
    "totalRuns": 25000,
    "totalUsers": 1400,
    "totalUsers30Days": 95
  },
  "currentPricingInfo": {
    "pricingModel": "PAY_PER_EVENT"
  },
  "actorReviewRating": 4.7,
  "actorReviewCount": 18,
  "bookmarkCount": 72,
  "isWhiteListedForAgenticPayments": true
}

When analytics are enabled, SEO_REPORT contains a separate report:

{
  "_type": "SEO_OPPORTUNITY_REPORT",
  "generated_at": "2026-07-11T10:00:00+00:00",
  "top_niches_to_build_in": [],
  "high_volume_low_competition_keywords": [],
  "fastest_growing_new_actors": [],
  "summary_stats": {
    "total_actors_analyzed": 500,
    "total_users": 100000
  }
}

How to Use

1. Open the Actor and click Try for free.
2. Choose an analysis mode and relevant categories.
3. Keep maxActors: 50 for a quick test.
4. Enable analytics when you need opportunity scoring.
5. Start the run and inspect the Actor records view.
6. Open SEO_REPORT from the Output tab for the derived market analysis.

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('scraper_guru/apify-store-analyzer').call({
  mode: 'findNewIdeas',
  maxActors: 500,
  includeAnalytics: true,
});
const report = await client
  .keyValueStore(run.defaultKeyValueStoreId)
  .getRecord('SEO_REPORT');

Pricing

This Actor uses pay-per-event pricing, so platform usage is included. You pay for each Actor record saved to the dataset, plus a tiny start charge of $0.00005 per run. The optional SEO report adds one dataset item and is also available in the key-value store.

Examples on the Free plan: the default 50-Actor run costs about $0.25; a 500-Actor category scan about $2.50; a complete Store snapshot (maxActors: 0, roughly 25,000 Actors) about $125. Filter by categories, minTotalUsers or pricingModels to collect only the slice you need. Apify shows the exact plan-adjusted price before each run.

FAQ

Where does the data come from?
The Actor queries the public search index used by the Apify Store. It does not access private account or billing data.

Why can Store totals change between runs?
Actors, pricing, usage, and publication status change continuously. Each run is a current snapshot.

What does the opportunity score mean?
It is a bounded comparative heuristic. Niche scores compare winsorized 30-day demand share with supply share. Keyword scores combine recent demand, relative Store demand, supply, and observation confidence. It is not a revenue guarantee.

How is growth calculated?
Growth compares the 7-day user run rate with the 30-day window, then compares 30-day users with the preceding 60-day monthly average. This measures recent momentum instead of dividing lifetime users by Actor age.

Can a full-Store run be expensive?
Yes. maxActors: 0 can produce tens of thousands of dataset rows. With pay-per-result pricing, use a smaller limit unless you specifically need a full-market export.

How much memory does a full-Store run need?
At least 2 GB (the default). A complete scan holds about 90,000 Actor records. With less memory, the run stops at the start with a clear message instead of crashing midway.

Can I track changes over time?
Yes. Schedule the Actor and preserve each dataset or export results into your own database.

Does eligibility mean an Actor is profitable?
No. Eligibility is a platform attribute; it does not prove demand, revenue, or profitability.

For Store-index changes or report issues, open the Issues tab on this Actor.

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