Instagram Engagement Rate & Influencer Vetting

Score Instagram creators without a login: engagement rate measured from their recent Reels, compared against a published peer band for their audience size, plus reach rate, comment-to-like ratio, consistency, and named risk flags that each cite their own evidence.

The method is the product - so here it is in full

Derived-metric tools live or die on whether you trust the number. Every figure below is either measured or computed by a formula printed here. Nothing is a black box.

Engagement rate = (average likes + average comments) / followers, measured across the creator's most recent Reels (up to 12, reelsSampled tells you exactly how many).

Reach rate = average plays / followers - how far content travels relative to audience size.

Engagement per play = (average likes + average comments) / average plays - how compelling content is once seen, which is independent of audience size.

Peer bands. A flat "good ER" threshold mislabels large accounts, because engagement falls as audiences grow. Each creator is judged against its own band:

Band	Followers	Expected ER
nano	under 10k	2.0% - 9.0%
micro	10k - 100k	1.5% - 6.0%
mid	100k - 500k	1.0% - 4.5%
macro	500k - 1M	0.8% - 3.5%
mega	1M+	0.5% - 3.0%

Vetting score (0-100) starts from where the creator's ER sits inside its band, then adds for healthy cadence and consistent reach, and subtracts for each risk flag (high −14, medium −7, low −3) and for a thin sample (−8 under 3 Reels). Verdict maps the score: strong 70+, acceptable 50+, weak 30+, avoid below, plus low_confidence and insufficient_data.

Risk flags - each row carries riskFlagDetails with a written evidence string:

Flag	Raised when
engagement_below_peer_band	ER under the floor for that audience size
engagement_implausibly_high	ER more than 2.5× the band ceiling - pods or bought engagement
follow_back_pattern	10k+ followers with a near 1:1 following ratio
very_low_comment_ratio	under 1 comment per 1,000 likes - likes without conversation
erratic_reach	reach coefficient of variation above 1.5 - a few outliers carry the average
thin_posting_history	fewer than 12 posts published

What this actor deliberately does NOT claim

No "fake follower percentage." That figure cannot be honestly derived without inspecting the follower list, and Instagram does not expose follower lists to logged-out callers at all. Tools that print one without a login are guessing. This actor gives you evidence-backed flags instead, and says so.

Example output

adidas    29.6M followers   ER 1.683%   mega band   in band    score 69  acceptable   flags: none
leomessi  515M followers    ER 0.729%   mega band   in band    score 51  acceptable   flags: erratic_reach
nike      291M followers    ER 0.052%   mega band   below band score 29  avoid        flags: engagement_below_peer_band

What you get per creator

profileUrl · username · fullName · followersCount · followingCount · postsCount · isVerified · vettingScore · verdict · engagementRate · engagementRatePercent · peerBand · peerBandExpectedMinPercent · peerBandExpectedMaxPercent · withinPeerBand · riskFlags[] · riskFlagDetails[] · riskFlagCount · reelsSampled · avgPlays · medianPlays · avgLikes · avgComments · engagementPerPlay · commentToLikeRatio · reachRate · playsStdDev · playsCoefficientOfVariation · followerToFollowingRatio · recentPostsSampled · recentReelShare · biography · externalUrls[] · methodNote · scrapedAt

Input

{
  "usernames": ["natgeo", "adidas", "nike"],
  "minFollowers": 10000,
  "minVettingScore": 50,
  "maxResults": 100,
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }
}

Field	What it does
usernames	Creator handles - built for scoring a whole shortlist in one run
minFollowers	Audience floor, applied before any analysis work
minVettingScore	Return only creators scoring at least this - hands you a shortlist, not a table
skipPrivate	Skip private accounts (on by default - they publish nothing to measure)
maxResults	Cap. 0 = no limit

Honest limits

• The evidence base is the creator's recent Reels (up to 12, the logged-out ceiling). reelsSampled is on every row, and a sample under 3 lowers the score and returns low_confidence. An account with no Reels returns insufficient_data rather than a fabricated score.
• Posting cadence is not measured. The Reels tab does not carry timestamps, and fetching a date for every Reel would multiply the cost of a vetting run several times over. Rather than infer cadence from nothing, postsPerWeek is left out of the score. If you need per-Reel dates, use Instagram Reels Scraper.
• Engagement is measured on Reels, not on the whole feed. Reels are where Instagram's reach lives, and they are the only surface exposing play counts logged-out.
• Peer bands are a documented judgement, not a law of nature. They are printed above and on every row so you can re-band the data yourself.

Pricing (pay per event, no start fee)

Event	Price	What it covers
profileAnalysed	$0.03	One fully vetted creator: ER, peer band, reach rate, comment-to-like ratio, consistency, risk flags with evidence, and the 0-100 score

A single price for a complete analysis - two source requests, all the derived metrics, and the evidence behind them. Creators removed by minFollowers or minVettingScore are never billed.

Use with AI assistants (MCP)

Works as an LLM tool via the Apify MCP server - ask an assistant to "vet this influencer shortlist and drop anyone below 50" and it can call this actor directly.

Agent-ready: autonomous payments (x402 & Skyfire)

This actor is agent-ready — AI agents can discover it, run it, and pay for it autonomously, with no Apify account and no human in the loop. It uses pay-per-event pricing and limited permissions, so it qualifies for Apify's agentic-payment standards:

• x402 — an open, HTTP-native payment protocol. Agents pay per run in USDC on the Base network directly through the Apify MCP server — no account, no API key.
• Skyfire — agent-to-service payments for fully autonomous AI-agent workflows.

Building an AI agent, MCP tool, or autonomous data pipeline? This scraper is ready to plug in and pay as it goes.

Integrations

Make, Zapier, Slack, Google Drive, Airbyte, GitHub, the Apify API, Schedules and Webhooks.

FAQ

Do I need a login or cookies? No.

Why is a huge account scored "avoid"? Because engagement is judged against its own peer band. A 291M-follower account posting at 0.05% ER is genuinely underperforming for its size, and that is the signal a brand is paying to see.

Why insufficient_data? That creator published no Reels this actor could sample. It returns a null score rather than inventing one.

Can I change the bands? Every row carries peerBandExpectedMinPercent / peerBandExpectedMaxPercent and the raw engagementRate, so you can re-band downstream without re-scraping.

Related scrapers by scrapesage

• Instagram Profile Scraper - bulk profile stats and resolved bio links
• Instagram Reels Scraper - per-Reel play counts, view counts and dates
• Instagram Leads Scraper - turn vetted creators into contactable leads
• Instagram Hashtag Scraper - discover creators to vet