Creator Stats: multi-platform influencer stats from one handle list

Get followers, engagement, growth, earnings estimates and contact emails for creators across 19 platforms in a single run. Creator stats and influencer analytics come back as one tidy row per platform and handle, merged field by field from every source that answers, so you can rank, vet and outreach without opening twenty tabs.

What you get

• One dataset row per (platform, handle) with platform, handle, display_name, followers, following, posts_count, videos_count, engagement_rate, growth, earnings_estimate, audience_quality, contact_email, source_name, sources, fetched_at and status
• Coverage across YouTube, Instagram, TikTok, Twitch, X, Kick, Telegram, Reddit, Snapchat, Bluesky, Mastodon, Discord, Substack, Medium, Gab and VK
• Field-level merge: when several sources answer, the strongest source wins each field and the row lists every source that ran
• Second-index corroboration from public stats providers, so a single thin profile is not your only signal
• Contact emails pulled from bios and profile pages when the creator published one
• Earnings or income bands and audience-quality grades where a source carries them
• A clear status on every row (ok, partial, blocked, not_configured, not_found, error) so a quiet platform never looks like a zero
• Per-source notes on the row, including missing API keys and upstream limits

No API keys are required for the core run. Optional keys unlock a few official APIs and are skipped cleanly when absent.

Why scrape creator stats

Influencer platforms sell seat licences and metered lookups. If you vet fifty creators a week across six networks, you are paying enterprise money for what is, at heart, a public profile read. The numbers also disagree: a TikTok follower count on the profile page, on a stats site and inside a media kit can all differ, and you only find out when the campaign report lands.

Pulling creator stats yourself fixes both problems. You choose the handles, you keep the raw fields, and you can line up several sources on the same profile to see where the story is consistent. That is the difference between "she has about a million followers" and "she has 1.02M on the profile, 1.09M on the stats index, engagement around 8%, income band mid-five figures, contact email on the bio".

Agencies run this before a pitch. Brands run it to qualify inbound. Analysts run it to build a market map of a niche. In every case the job is the same: turn a list of handles into a comparable table, fast, without a login wall on your time.

Input

Field	Type	Required	Description
handles	array	one of handles / handle	List of {platform, handle} objects. A bare string is resolved on every known platform.
handle	string	one of handles / handle	Single handle, resolved on platforms or on every known platform.
platforms	array	no	Platform keys for the single-handle form.
include_stubs	boolean	no	Also emit stub rows for platforms that need a real browser. Default false.
sources	array	no	Source-name filter (for example socialblade, speakrj, reddit_web). Empty runs every source that covers the platform.

Platform keys: youtube, instagram, facebook, tiktok, twitch, x, telegram, threads, reddit, kick, snapchat, truth_social, bluesky, mastodon, rumble, substack, medium, gettr, gab, discord, vk, lemon8, pinterest, linkedin.

Handles are normalised for you: a leading @, a full profile URL or a channel URL all resolve to the same handle.

{
  "handles": [
    { "platform": "youtube", "handle": "@LinusTechTips" },
    { "platform": "instagram", "handle": "pewdiepie" },
    { "platform": "tiktok", "handle": "khaby.lame" },
    { "platform": "telegram", "handle": "durov" }
  ]
}

Output

One row per platform and handle. Fields a source did not publish stay null rather than becoming 0.

{
  "platform": "instagram",
  "handle": "pewdiepie",
  "display_name": "PewDiePie",
  "followers": 19300000,
  "following": 560,
  "posts_count": 1800,
  "videos_count": null,
  "engagement_rate": 8.65,
  "growth": null,
  "earnings_estimate": { "band": "mid-five figures", "source": "speakrj" },
  "audience_quality": { "source": "socialblade", "grade": "B+" },
  "contact_email": null,
  "source_name": "imginn",
  "sources": ["imginn", "socialblade", "speakrj"],
  "fetched_at": "2026-09-24T15:16:11+00:00",
  "status": "ok",
  "notes": ["socialblade: social blade letter grade, not a fraud score"]
}

The run also writes OUTPUT, summary and errors to the default key-value store. OUTPUT carries itemCount, errorCount, targetCount, statusCounts and free_tier_remaining.

Use cases

Agency shortlisting. Paste fifty handles from a campaign brief, pull the table, sort on engagement rate and contact email presence. The shortlist for a client call takes minutes and every number is one you can re-run next week to see what moved.

Inbound qualification. A creator emails a media kit. Run the handle across their claimed platforms before you answer. Follower counts that do not line up with the kit, or a missing profile on a claimed network, change the conversation.

Market mapping. List the top voices in a niche on one platform, then fan each handle out across the others. The overlap shows who is actually multi-platform and who is a one-network specialist, which is the input your pricing model needs.

Monitoring and CRM enrichment. Schedule a weekly run over a fixed handle list and diff the follower and engagement columns into your CRM. Trend direction matters more than a single snapshot, and the growth field carries history where a source publishes it.

How it compares

	This actor	Single-platform profile scrapers	Influencer SaaS seats
Platforms per run	19 keys, one row each	1	varies, usually capped
API keys needed	none for the core run	none to several	account
Multi-source merge	yes, field level	no	yes, closed
Contact email	when published on the profile	rarely	yes, often gated
Pricing	pay per row	pay per row or free	$250-500/mo
Raw dataset	yes	yes	export, sometimes metered

Single-platform scrapers are cheaper per row and deeper on their one network. They do not reconcile a creator across the other eighteen. Influencer SaaS gives you a polished UI and a database; you pay for the seat and for every lookups quota they set. This actor sits in between: a wide, comparable table, priced per row, with the raw JSON in your dataset.

Pricing

$0.007 per creator row delivered to the dataset. All pricing is pay-per-event: you only pay for results you receive. No actor-start fee, no per-compute-unit charges.

Limits and gotchas

• Free-plan runs receive at most 10 rows per run. Split large lists across runs, or upgrade, to get past the cap.
• A row with status: blocked or not_found is still a row: the platform was checked and did not answer or does not have that handle. It is not a zero.
• Official-API sources (YouTube Data API, Twitch Helix, SparkToro and similar) return not_configured until you attach their keys as actor environment variables. The rest of the run is unaffected.
• include_stubs: true adds rows for platforms that need a real browser. Those rows come back blocked with the reason named. Leave the flag off unless you want the coverage map.
• Some public stats sources rate-limit under burst. If notes mentions a limit, lower concurrency by splitting the input.
• Lifetime post and comment counts are not published on every platform. Those fields stay null where the number is not public.
• Medium support depends on an optional extra being present in the run environment. When it is missing, only that one source degrades; the other sources still run.
• Cold start is a few seconds. A 20-handle fan-out typically finishes well inside two minutes.

FAQ

Can I get creator stats without an API key? Yes. The core of this actor is keyless. A handful of official-API sources skip themselves when their keys are missing and say so in notes, and the row still fills from the other sources.

How do I scrape influencer stats across several platforms at once? Pass a list of {platform, handle} objects, or one handle and let it fan out. One row comes back per platform and handle, so the output is already in the shape of a comparison table.

Does this return engagement rate and earnings estimates? It returns engagement_rate and earnings_estimate whenever a source publishes them. Not every platform exposes both publicly; the fields stay null when they do not, and raw_sources shows which source said what.

Where does the contact email come from? From the profile or bio when the creator published one. This actor does not bypass a login wall or a private field, so a hidden email stays hidden.

What happens when a platform blocks the lookup? The row comes back with status: "blocked" and a note. The run still succeeds, and the rest of the rows are unaffected. Raise this with us if one platform is consistently blocked for you.

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