Apify Store Opportunity Finder: Lead Gen Edition

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Find profitable Apify Actor ideas before building another generic lead-gen scraper.

This Actor searches public Apify Store listings, normalizes Actor metadata, classifies lead-gen niches, and generates opportunity reports based on demand, saturation, ratings, weak positioning, and public usage signals.

What It Does

• Searches Apify Store with your keywords.
• Exports normalized Actor rows.
• Detects platforms like LinkedIn, Twitter/X, Instagram, Facebook, YouTube, Google Maps, Trustpilot, and Glassdoor.
• Detects use cases like lead generation, contact extraction, monitoring, reviews, jobs, ecommerce, ads, and enrichment.
• Groups Actors into niches.
• Scores demand, weakness, saturation, and opportunity.
• Writes a markdown summary to SUMMARY.md.

Who It Is For

• Apify Actor developers
• scraping agencies
• indie hackers
• data product builders
• lead-gen operators deciding what scraper to build next

Input

{
"searchTerms":["lead generation","linkedin scraper","google maps leads"],
"maxActorsPerTerm":200,
"analysisMode":"market_analysis",
"sortBy":"popularity",
"includeRawActors":true,
"includeNicheReports":true
}

Dataset Output

Actor rows use record_type: "actor":

{
"record_type":"actor",
"search_term":"lead generation",
"actor_id":"example/linkedin-people-search",
"title":"LinkedIn People Search Scraper",
"developer":"Example",
"pricing_model":"PAY_PER_EVENT",
"rating":3.2,
"review_count":6,
"total_users":3000,
"monthly_users":180,
"detected_platforms":["linkedin"],
"detected_use_cases":["lead_generation","contact_extraction"],
"quality_flags":["high_usage_low_rating"]
}

Niche rows use record_type: "niche_report":

{
"record_type":"niche_report",
"niche":"linkedin lead generation",
"actors_found":12,
"total_users_sum":18400,
"median_rating":3.6,
"low_rating_high_usage_count":3,
"demand_score":274.13,
"weakness_score":42,
"saturation_score":58.7,
"opportunity_score":257.43,
"recommended_actor_angle":"LinkedIn lead generation with enrichment, monitoring, and reliability proof"
}

Opportunity Score

The score is a directional ranking, not a promise of profit.

It favors:

• visible demand from public usage and reviews
• weak competitors with poor ratings or weak Store positioning
• niches that are not completely saturated

It penalizes:

• heavy crowding
• strong single-actor dominance
• weak public demand signals

Monetization Notes

Use Apify Pay Per Event when publishing. This Actor pushes dataset rows with the store-result event name, so the simplest setup is one event charged per returned row.

Suggested starting price:

store-result: $0.001 per dataset row

Do not manually charge an Actor-start event in code. Apify provides the synthetic start event for new PPE Actors.

Limitations

• Uses public Apify Store metadata only.
• Does not guarantee demand outside Apify Store.
• Does not scrape private data.
• Does not use LLMs in v1; classification is deterministic keyword matching.
• Scores are a compass for inspection, not financial advice.

Local Development

npminstall
npmtest
npm run lint
npm start

For local runs, Apify SDK writes results into the local storage/ directory.