Which Apify actor should you actually build next? The Store rewards the few wedges where demand is real and the incumbents are weak — and quietly punishes the hundreds of builders who ship the 200th Google Maps clone into a fortress. This report ranks the winnable wedges so you spend your build days where a new actor can still take runs.
Below is a free sample — four winnable wedges, in full. The paid report ranks 20+ wedges with per-wedge creator-portfolio analysis (who already owns the lane, how concentrated it is, and where the gap is).
| Wedge | Public demand (Store users / actors) | Incumbent strength | Price band ($/result) | One-line build brief |
|---|---|---|---|---|
| Domain → clean lead records contacts/email extraction lane |
388k users across 246 actors | WEAK — beatable | $0.00001–0.25 | Turn a list of company domains into scored, contactable records. Most incumbents sell raw contacts and stop; add a qualification score + outreach angle + key pages. Public sites only, so no login/ToS fragility. |
| Hiring-signal decision layer jobs/hiring lane |
261k users across 369 actors | WEAK at the decision layer | $0.00001–0.60 | Raw job-post scrapers dominate; the "who to contact + why now" decision-layer actors are tiny (≤58 users). Ship rows that say who's hiring, the decision-maker, and the commercial reason — not just listings. |
| ATS-native hiring feed Greenhouse / Lever / Ashby |
proven anchor at ~5.9k users | THIN — few serious actors | aligns to jobs lane | Pull durable, ToS-safe job data straight from public ATS JSON — no login fragility, no upstream scraper to break. The buyer who got burned by a LinkedIn actor wants exactly this. |
| Company-data enrichment layer firmographics / tech / fit |
53k users across 90 actors | MODERATE | up to $0.30 | Sit on top of the scrapers instead of competing with them: enrich a domain into firmographics + tech stack + a scored fit signal. Sells as the layer buyers add after extraction. |
How to read demand: the figures are public Apify Store user counts (stats.totalUsers) — a demand proxy, not revenue. Actor revenue is not public and is not asserted here. Wedges were surfaced from a scan of 1,044 corridor actors and clustered by lane.
Half the value of the report is the lanes it stops you from wasting a week on. Three that look tempting and aren't:
| Lane | Why it looks good | Why it isn't winnable now |
|---|---|---|
| Maps / local | 574k users — huge demand | Category leaders already own it; concentrated, off-corridor. A new entrant takes ~0 runs. |
| LinkedIn profile | 64k users, high $/result | Fortress creators own the lane end-to-end. Hard to dislodge, ToS-fragile. |
| Leads aggregator (Apollo/ZoomInfo clones) | 43k users, prices up to $8 | 154 actors already price-competed to ~$1–3 / 1k. High maintenance, low margin. Reject. |
Indie Apify actor builders, automation and scraper developers, and no-code + AI tool builders deciding what to ship next — people who'd rather spend two build days on a wedge that can take runs than launch into a fortress and get zero. If you already know your lane, the enrichment and ATS-native briefs alone will sharpen it.
Built by QualifyOps — a portfolio of production actors on the Apify Store. The report is the same market scan we run on our own builds. Demand figures are public Store data; revenue is never asserted.