Apify SOCIAL_MEDIA: 3 Platforms Take 66% of Demand
Across 1,213 tracked SOCIAL_MEDIA actors (May 2026), Instagram + TikTok + LinkedIn capture 66% of demand. LinkedIn has 43% of actors but only 21% of demand. Instagram has 12% of actors but 33% of demand — 3× the per-actor density. Targeting predicts economics.
The Apify Store’s SOCIAL_MEDIA category held 6,780 actors as of 2026-05-16. 1,213 of those have continuous data history sufficient for measurement on the Signal Census pulse tracker. The other ~5,500 are either newly published, abandoned, or below the demand-tracking threshold.
Across the tracked subset, three platforms dominate both supply and demand. Instagram + TikTok + LinkedIn account for 63.5% of catalog and 66.1% of 30-day active users. The remaining seven major platforms split a long tail.
The composition matters. Catalog share and demand share do not line up across the three leaders, and the gap between them reveals which targeting choices produce viable per-actor economics.
Where the SOCIAL_MEDIA catalog actually points
The three asymmetries
The catalog-vs-demand mismatch resolves into three distinct patterns when sorted by per-actor density.
| Target | Actors | % catalog | Demand | % demand | Demand / actor |
|---|---|---|---|---|---|
| 146 | 12.0% | 76,079 | 33.0% | 521 | |
| 87 | 7.2% | 30,732 | 13.3% | 353 | |
| TikTok | 99 | 8.2% | 28,632 | 12.4% | 289 |
| YouTube | 57 | 4.7% | 18,821 | 8.2% | 330 |
| 29 | 2.4% | 6,489 | 2.8% | 224 | |
| Twitter / X | 79 | 6.5% | 13,134 | 5.7% | 166 |
| 525 | 43.3% | 47,704 | 20.7% | 91 | |
| Other / multi-platform | 191 | 15.7% | 9,155 | 4.0% | 48 |
The per-actor demand density spread is 10x from top to bottom: Instagram’s 521 users per actor versus the multi-platform “other” segment’s 48. The three platforms with the highest per-actor density (Instagram, Facebook, YouTube) all have fewer than 150 listings each. The platform with the most listings (LinkedIn, 525) has by far the lowest per-actor density of any single-platform target.
This explains the LinkedIn-no-cookies dynamic documented in the Q1 2026 lead-extractors census. LinkedIn is the most-crowded segment with the lowest per-actor returns. Publishers competing there have to differentiate harder — the “No Cookies” naming convention is the most-cited example — just to clear a per-actor demand floor that other platforms reach automatically.
What the catalog distribution implies about buyer behaviour
The asymmetries point at two distinct buyer populations on the SOCIAL_MEDIA category.
The “consumer marketing” buyer goes to Instagram and TikTok. These buyers are usually agencies, brands, or growth-stage SaaS teams scraping content for trend analysis, influencer outreach, competitive intelligence, or paid-media targeting. The use case rewards comprehensive coverage of a single platform, and the buyer pool is large enough that a small number of well-built actors can each serve thousands of users.
The “B2B sales” buyer goes to LinkedIn. These buyers are sales operations, lead-gen consultancies, and outbound-focused B2B teams. The use case requires very specific extraction shapes (profiles, company employees, posts, sales-nav results), the legal landscape is more contested, and the cookie-vs-no-cookie distinction is load-bearing. The market is fragmented across many use-case-specific actors.
The “consumer marketing” pattern produces a small number of high-density actors. The “B2B sales” pattern produces a large number of medium-density actors that fragment a similar-sized demand pool. Both patterns are visible in the May 16 catalog snapshot.
Facebook, YouTube, and Twitter sit between the two patterns at smaller scale. Reddit has unusually low actor count given the recent prominence of Reddit data deals — 29 tracked Reddit-targeting actors is a small population for a target the size of Reddit.
What this means for publishers
For publishers choosing a SOCIAL_MEDIA target to ship against in 2026, the three asymmetries imply three different strategic positions.
Instagram is the “high-density, hard-to-enter” position. 146 existing actors split 76,079 users — implying a per-actor average of 521. The category is well-served and the leaders are entrenched (the top movers data shows Apify’s own Instagram suite as the dominant publisher). Shipping a new Instagram actor against this competition requires either a very specific use case the leaders do not cover or a meaningfully better extraction quality / price than the established options.
LinkedIn is the “low-density, crowded” position. 525 existing actors split 47,704 users — implying a per-actor average of 91. The category is over-supplied, the average is low, and the leaders win on narrow positioning (no-cookies, email-finder, company-employees, post-comments). Shipping into LinkedIn means competing on positioning specificity, not on coverage breadth.
The smaller-platform positions (TikTok, Facebook, YouTube) are the “medium-density, mid-difficulty” middle ground. 87-99 actors each, hundreds of users per actor, and reasonable room for a credible new entrant to capture some share. These are the categories where a focused publisher operating against a specific extraction shape can realistically build to category-leader status in a quarter or two.
The right question for a SOCIAL_MEDIA publisher is not “which platform is most scraped” but “where does per-actor economics actually pay”. The 10× density spread between targets answers it.
Sources
- Signal Census pulse: pulse_details.json + store_pulse.json (data window 2026-05-16; 1,213 tracked SOCIAL_MEDIA actors of 6,780 total in category)
- Signal Census Q1 2026 lead and contact extractors census
- Signal Census: Reddit’s $60mn Google Deal Was a Floor
- Signal Census: Apify’s Long Tail — 57% under 10 users