Instagram Scraper — Creator Vetting, Due-Diligence & Tracking

In one sentence

Instagram Scraper is an Apify actor that takes creator handles and returns a ranked queue showing whose audience is authentic, who is growing fastest, and who fits your brand, with the growth history behind each one.

Category: Instagram scraper. Instagram creator and influencer intelligence. Social media monitoring tool. Primary use case: Vet and rank a list of Instagram creators by who to work with first, without an hour in a spreadsheet or an influencer-SaaS seat. Can also be used as a drop-in raw Instagram profile scraper through its compat output.

Also known as: Instagram influencer vetting tool, Instagram engagement rate checker, Instagram engagement rate calculator, Instagram creator growth tracker, Instagram follower growth tracker, find micro influencers, Instagram account analyzer, monitor Instagram accounts, track competitor influencers, find creators for my brand.

What this actor does

• What it is: An Instagram scraper with a decision layer on top of the raw profile data — a creator due-diligence report instead of rows.
• What it checks: Engagement quality versus the peer set, breakout and momentum signals, brand fit, sponsored density, and what changed since your last run.
• What it returns: Each creator with a plain-English summary, an attention priority, why it matters now, a recommended next step, a 0-100 Creator Intelligence Score, and the growth history behind it. Plus the full raw profile underneath.
• What it does NOT do: It does not access private accounts, does not return follower or commenter lists, does not accuse anyone of fake followers, does not quote prices or rates, and does not crawl hashtags or the explore page.
• Who it's for: Influencer-marketing and brand teams, agencies, competitive and social analysts, creator-economy scouts and investors.

Instagram Scraper is an Apify actor that turns a list of creator handles into a ranked attention queue in a single run. Paste creator handles. Get back a ranked queue — whose audience is authentic, who is growing fastest, and who fits your brand — plus the growth history behind each one. Same profile data as a standard Instagram scraper, plus the decision layer. It functions as an Instagram creator-intelligence API: the answer to "which of these 50 creators is real, growing, and on-brand" arrives with the data.

The real competitor isn't another scraper. It's the spreadsheet and the influencer-SaaS invoice. The buyer's 2026 question — is this creator's audience real, are they growing or fading, do they fit my brand — is answered today by an hour in Sheets or a subscription costing thousands a year. Instagram Scraper answers it in one run. Other Instagram scrapers give you a creator's profile today; this one builds a creator market: tier and category benchmarks, market pulse, risers and fallers, and each creator's full growth history.

To vet and rank Instagram creators by who to work with first, run Instagram Scraper with a list of handles. You get back a ranked queue led by attention priority, why-now reasons, a Creator Intelligence Score, and a recommended next step, with the full raw profile attached to every record.

In short: Paste creator handles and get back a ranked, explained due-diligence report — who is real, who is growing, who fits your brand, and what changed — plus the raw profile data underneath.

What it is: An Instagram scraper with a built-in decision layer that vets, ranks, and explains creators. Who it's for: Influencer-marketing teams, agencies, competitor analysts, creator-economy scouts and investors. When to use it: When you have a list of creator handles and need to know which ones to work with, not just their stats.

What it does — Vets and ranks Instagram creators with a due-diligence read on top of the raw profile. Best for — Brand and influencer teams, agencies, competitor analysts, creator scouts and investors. Speed — First ranked results typically appear within the first minute of a run; full sets take longer at higher caps. Output — JSON, CSV, or Excel. Each record carries a summary, attention routing, a 0-100 score bundle, and growth history. Proxy — Residential proxies are required (default Apify Residential, US rotation).

Key limitation: This actor reads public Instagram profiles only. It does not access private accounts, follower lists, or hashtag and explore pages. What it is not: Not a follower-list exporter, not a fake-follower auditor, and not a replacement for legal or contractual review. Does not include: Private accounts, individual follower or commenter data, fake-follower verdicts, actual prices or rate quotes, or growth forecasts. Results may be incomplete when: an account is private, a creator has only a handful of recent posts, the tracked history is thin, or Instagram restricts automated access on shared IPs.

The five pillars

Creator intelligence in five jobs, every one running on the same public profile data:

• Vet — the due-diligence read: engagement quality versus the peer set, sponsored density, and a descriptive risk ledger. The SaaS-killer.
• Rank — the Creator Intelligence Score (CIS, the one hero number), deal-readiness, and the Attention Queue that opens every run.
• Track — name a watchlist, schedule the run, and get back only what changed: new breakouts, anomalies to vet, creators going quiet. Plus a Signal Feed for Slack and agents.
• Compare — lay 2 to 50 creators side by side with labeled bests, or build an export-ready campaign shortlist against a brand profile.
• Remember — Creator Memory and Creator Replay keep the growth and engagement history the live profile data can't give, plus tier-and-category market benchmarks.

What you get from one call

Input: { "mode": "profiles", "usernames": ["nasa", "natgeo", "bbcearth"], "rankBy": "breakoutPotential" } Returns:

• A ranked Attention Queue: the creators ordered by who to look at first this run.
• For each creator: an archetype (signalProfile), why-now reasons (whyNow), and a recommended next step (recommendedAction).
• A 0-100 score bundle led by the Creator Intelligence Score, plus deal-readiness, engagement-quality, breakout, brand-fit, momentum, and stability scores.
• The engagement-quality read: rate, percentile versus the peer set, and a descriptive band (strong / normal / low / anomalous).
• The growth history behind each creator (days tracked, follower and engagement trajectory), with firstSightFallback on first sight rather than a fabricated timeline.
• A run summary with a headline, a daily briefing, executive highlights, and a market snapshot.

Typical time to first result: under a minute for the leading creators. Typical time to integrate: minutes — existing pipelines that read raw profile fields work unchanged through the compat output.

What makes this different

• A due-diligence report, not a row dump — every run opens on the Attention Queue: which creators to look at first, the engagement-quality read, why now, and a recommended next step, not raw profile order.
• Growth history nobody else keeps — the live profile data shows a creator today; Instagram Scraper remembers the trajectory across runs, so Creator Replay can show how a creator grew, peaked, or faded over time. A clone can't backfill history it never collected.
• Market benchmarks, not just one profile — engagement quality is read against a tier-and-category peer set ("top 8% of your peer set"), because a 10M account and a 10k account have different normal ranges.

If you were building this yourself, you would need to fetch the public profile substrate, compute per-creator and peer baselines, derive engagement-quality bands, score and rank by the right axis, store follower and engagement history across runs, and write the change-diff logic. Instagram Scraper ships that as one decision layer. It functions as an Instagram creator-intelligence API, producing ranked, explained creator records useful for vetting, discovery, and competitor monitoring.

Quick answers

What is it? An Instagram scraper that returns a ranked, explained due-diligence report on a set of creators — who is real, who is growing, who fits your brand — instead of raw profile rows you read by hand.

How do I check an Instagram creator's engagement rate and audience quality? Run profiles mode with rankBy: engagementQuality (or authenticity). Each creator carries an engagement rate, its percentile versus the peer set, and a descriptive band — strong, normal, low, or anomalous to vet — never a fake-follower verdict.

What makes it different? Every record carries a Creator Intelligence Score, an engagement-quality band against the peer set, a recommended next step, and the creator's growth history across runs. No other Instagram actor on the Store ships the decision layer.

What data sources does it use? Public Instagram profiles only — the same public profile data a logged-out visitor sees. No login, no private accounts, no follower or commenter lists.

How much does it cost? Pricing is per result, anchored to the value it replaces — an hour in a spreadsheet or an influencer-SaaS seat costing thousands a year — not to a raw-row scraper. Apify's free tier includes monthly credits to test with. Set a spending limit on any run.

At a glance

Quick facts:

• Input: A list of creator handles (or post URLs), plus an optional brand profile, watchlist name, and filters.
• Output: Ranked creator records with a Creator Intelligence Score, an engagement-quality read, brand fit, growth history, and a recommended next step. JSON, CSV, or Excel.
• Modes: profiles (default), posts, watchlist, historicalSnapshot.
• Rank axes: dealReadiness (default), breakoutPotential, engagementQuality, brandFit, momentum, followers, authenticity.
• Batch size: Up to 200 handles per run (up to 500 post URLs in posts mode).
• Proxy: Residential required (default Apify Residential, US).
• Watchlist: Set a name to get back only what changed on the next run.

Input → Output:

• Input: A list of creator handles.
• Process: Instagram Scraper reads the public profiles, reads engagement quality against the peer set, scores and ranks the creators, and remembers each one for next time.
• Output: A ranked Attention Queue plus the raw profile data, in JSON, CSV, or Excel.

Best fit: Vetting a list of creators before a campaign, finding emerging and micro creators, tracking a competitor or roster of creators week over week, and benchmarking a creator against its peer tier. Not ideal for: Exporting follower or commenter lists, finding creators by hashtag or the explore page, or any fake-follower verdict, contractual, or pricing judgement. Does not include: Private accounts, follower/commenter data, fake-follower verdicts, actual prices or rate quotes, or growth forecasts.

Problems this solves:

• How to tell whether an Instagram creator's audience is real before paying for a campaign.
• How to find emerging and micro-influencers in a niche from a handle list.
• How to rank a list of creators by who fits a specific brand.
• How to track a roster or competitor set week over week without diffing exports.

Data trust: All live fields come from public Instagram profile data the actor fetches in the run. Engagement-quality bands and percentiles return null when the peer set is too small to rank fairly, and history fields carry firstSightFallback: true on first sight rather than inventing a timeline. Private accounts are returned as isPrivate and skipped.

Common questions this actor answers:

• Is this creator's engagement authentic? The Engagement Quality / Vetting view — band, percentile versus peers, and the risk ledger.
• Who is breaking out in my list right now? The Breakout / Emerging view, ranked by velocity.
• Which of these creators fits my brand? The Brand Fit view, ranked by brandFit against your brand profile.
• What changed across my roster since last week? Watchlist mode, which leads with a change briefing.
• Is there an alternative to an influencer-SaaS seat for vetting? Yes — the Engagement Quality and Brand Fit views cover the core vetting job per run.

What is an Instagram creator-intelligence tool?

An Instagram creator-intelligence tool turns raw profile data into decisions: whether a creator's audience is authentic, whether they are growing or fading, and whether they fit a brand. Basic Instagram scrapers stop at the profile rows and leave the interpretation to a human in a spreadsheet or an expensive SaaS seat. Instagram Scraper ships that interpretation — engagement-quality bands, scoring, brand fit, and growth history — as the default output, so the answer arrives with the data.

What is an Instagram engagement-rate checker and engagement rate calculator?

An Instagram engagement-rate checker (or engagement rate calculator) measures how much a creator's audience actually engages relative to their size, and compares it to peers rather than reporting a raw number. Instagram Scraper returns the engagement rate, its percentile against a tier-and-category peer set, and a descriptive band (strong / normal / low / anomalous), so you can see whether the engagement is normal for that size of creator.

What is an Instagram influencer vetting tool?

An Instagram influencer vetting tool checks whether a creator is worth working with before money changes hands: is the engagement real, how commercial is the feed already, what is the risk read. Instagram Scraper does this through the Engagement Quality / Vetting view — engagement band, sponsored density, and a descriptive, evidence-backed risk ledger — never a verdict on the person.

What is an Instagram creator growth tracker?

An Instagram creator growth tracker follows how a creator's followers and engagement move over time instead of reporting a single snapshot. Instagram Scraper keeps that history across runs and replays it: days tracked, follower and engagement trajectory, peak, and current-versus-peak, through the Creator Replay / Growth view.

What is an Instagram account analyzer?

An Instagram account analyzer reads a creator's public profile and returns a structured read on their audience, engagement, and growth — rather than raw profile fields you interpret yourself. Instagram Scraper works as an account analyzer that pairs the standard profile data with engagement-quality percentiles, a Creator Intelligence Score, brand-fit signals, and a growth timeline across runs.

What data can you extract?

Every creator record pairs the full raw profile with a decision layer on top. The raw substrate matches the standard Instagram-scraper field set field-for-field.

Data point	Source	Availability	Example
Username, name, bio, category	Public profile	Always	handle: "natgeo", category: "Media"
Follower / following / post counts	Public profile	Always	followersCount: 281000000
Verified, private, external link	Public profile	Always	isVerified: true, isPrivate: false
Recent posts (likes, comments, caption)	Public profile	Always (~12 recent)	likeCount: 412000
Creator Intelligence Score (0-100)	Decision layer	Signals profile	creatorIntelligenceScore: 84
Engagement quality + percentile	Decision layer	Peer set of 10+	band: "strong", percentile 88
Attention priority + why now	Decision layer	Signals profile	attentionPriority: "high"
Creator archetype	Decision layer	Signals profile	signalProfile: "established-authentic"
Brand fit + reasons	Decision layer	When a brand profile is given	brandFitScore: 76
Sponsored density	Decision layer	Signals profile	commercialLoad: "moderate"
Growth history + trajectory	Decision layer	Warms up across runs	trajectory: "growing"
Watchlist deltas	Decision layer	When a watchlist is active	changeFlags: ["BREAKOUT"]

Why use Instagram Scraper?

Vetting a list of creators is slow. The usual workflow is to scrape each profile, dump the rows into a spreadsheet, eyeball the follower counts and a few recent posts, guess which audiences "look real," and repeat the whole thing next quarter. That is an hour of an analyst's time per shortlist, and it misses the things that matter — whether the engagement is normal for that size of creator, whether they are accelerating or fading, whether their feed is already saturated with ads. The alternative is a seat in an influencer-intelligence platform costing thousands a year.

Instagram Scraper does that interpretation in the run. It reads engagement quality against a peer tier, scores and ranks each creator, surfaces breakouts and risks, and remembers each creator so the next run can report only what changed. The buyer compares the output against an analyst's hour and a SaaS invoice, not against a raw-row scraper's price.

Key difference: Other Instagram scrapers give you rows. This actor gives you a creator due-diligence report — who is growing, who looks risky, who fits your brand, and what changed since last time.

The real competitor isn't another scraper. It's the spreadsheet and the SaaS invoice. A standard Instagram scraper, or a platform like a high-priced influencer-intelligence SaaS, either hands you raw rows to interpret yourself or charges thousands a year for the interpretation. Instagram Scraper ships the engagement-quality read, the scoring, the brand fit, and the growth history per run, on public profile data. This is not a price war against raw-row scrapers; it competes on the decision layer and the SaaS undercut.

Platform capabilities

• Scheduling — run a watchlist daily, weekly, or on any interval, and get back only what changed.
• API access — trigger from Python, JavaScript, or any HTTP client.
• Residential proxy rotation — required and built in, so the actor reaches public profiles reliably.
• Monitoring — Slack or email alerts when runs fail, through Apify integrations.
• Integrations — Zapier, Make, Google Sheets, webhooks, and any tool that reads an Apify dataset.

Features

Instagram Scraper ships four input modes and a single decision layer that sits on top of every one of them. The layer vets each creator against its peer set, scores and ranks the list, derives time-decaying signal events, and remembers creators across runs. Everything below is deterministic and present in the output you can sort, filter, and export. It detects breakouts and engagement anomalies across a list of creators and surfaces who to look at first.

Vet and score

• Creator Intelligence Score — the flagship 0-100 standing on every creator, the one number for sorting and leaderboards. Built from growth, engagement quality, consistency, momentum, and history confidence, with cisTrajectory (7- and 30-day change and market rank) once history exists.
• Engagement quality — the authenticity read: engagement rate, percentile versus the peer set, and a descriptive band (strong / normal / low / anomalous) with evidence. Cohort-relative and descriptive, never a fake-follower accusation.
• Score bundle — a sortable 0-100 set per creator: dealReadinessScore, engagementQualityScore, breakoutScore, brandFitScore, momentumScore, stabilityScore, plus postingConsistency and contentVolatility, with a machine-readable scoreEvidence snapshot. Turn on explainScores for each score's components and weights.
• Sponsored density and risk ledger — how commercial a feed already is (rate, signals, light/moderate/heavy load, saturation), and a descriptive riskLedger (healthy / watch / review / high_uncertainty) with evidence — never a verdict on the person.

Rank and route

• Attention queue — every creator carries an attention block: priority (high / medium / low / none), whyNow reasons, a recommendedAction, and a respond-within window. Recommended actions are prioritisation steps only (Review, Shortlist, Vet, Track, Compare, Add to watchlist), never outreach or transaction steps.
• Reranking by axis — rankBy reorders by dealReadiness, breakoutPotential, engagementQuality, brandFit, momentum, followers, or authenticity. Each record shows its native rank, its reranked rank, and every axis value at once.
• Creator archetype and lifecycle — signalProfile (emerging, breakout, established-authentic, engagement-anomaly, dormant, declining, niche-pivoting, unclassified) plus a history-based creatorLifecycle (emerging / growing / peak / mature / declining / dormant).

Track, compare, remember

• Watchlist deltas — set a watchlistName on any mode to track a roster across runs. The run leads with a change briefing, then returns per-creator deltas, state transitions, and change flags.
• Compare and shortlist — intent: compare lays 2 to 50 creators side by side with labeled bests (best for awareness, best niche fit, best value vs risk, most volatile, needs more history); intent: campaign_shortlist with a brand profile builds an export-ready ranked shortlist with fit reasons and exclusions.
• Creator Memory and Replay — a historical store banks public profile metrics on every creator a run touches, so records carry history, contentMomentum, authenticityHistory, communitySignals, and a creatorReplay growth story. These warm up with use and are labelled across tracked creators, never "all of Instagram."
• Market benchmarks — marketBenchmarks places a creator across the tracked market by tier, category, and geo, with honest cold-start until a slice has enough creators.
• Drop-in compat — outputProfile: compat returns the exact standard profile-plus-posts field set, including the error-code taxonomy, for migration and raw ingestion.

Use cases for Instagram creator intelligence

Best for vetting creators before a campaign

Use when you have a shortlist and need to know which audiences are real before paying. Run profiles mode with intent: vet_creators (or rankBy: engagementQuality) and read the Engagement Quality / Vetting view. Used by brand and influencer-marketing teams to filter recommended from avoid. Key outputs: engagementQuality, sponsoredDensity, riskLedger, confidence.

Best for finding emerging and micro-influencers

Use when you need rising creators in a niche before they are expensive. Run profiles mode with rankBy: breakoutPotential and read the Breakout / Emerging view, ranked by the Emerging-Creator Radar. Key outputs: signalProfile, breakoutScore, radarRank, scoreEvidence.

Best for matching creators to a brand

Use when you need to rank a list against a specific brand. Supply a brandProfile (themes, values, audience) and read the Brand Fit view. Key outputs: brandFit, brandFitScore, creatorShape, scores.

Best for tracking a roster or competitor set

Use when you track a roster or competitor set week over week. Run any mode with a watchlistName on a schedule. The run leads with a change briefing and flags who broke out, who is fading, and who went quiet. Key outputs: watchlist, riskLedger, changeStory, scores.

Best for benchmarking a creator's growth

Use when you need a creator's growth story, not a single snapshot. Run profiles mode and read the Creator Replay / Growth view. Key outputs: history, contentMomentum, creatorReplay, cisTrajectory.

How to Monitor Instagram Accounts and Track Competitor Influencers

Set a watchlistName on any run and reuse it on a schedule. After the first run, only what changed comes back — new breakouts, engagement anomalies to vet, creators going quiet, and a plain-English change briefing at the top. Add a brand profile to also see whether tracked creators are drifting closer to or further from your positioning.

Common monitoring jobs:

• Track a roster of signed or shortlisted creators week over week
• Monitor a competitor's creator set to spot who they are activating
• Watch emerging-creator radar picks to catch rising accounts before they get expensive
• Get a change briefing delivered to Slack or email via Apify's webhook and Zapier integrations

How it works: Pass the same watchlistName on each scheduled run. Instagram Scraper reads each creator, compares against what it last saw, and returns only the delta — so you are not diffing two CSV exports by hand.

When to use Instagram Scraper

Best for: vetting a list of 10 to 200 creators before a campaign, weekly or daily roster and competitor monitoring, finding emerging and micro creators from a handle list, and benchmarking a creator against its peer tier. Not ideal for: exporting follower or commenter lists (not available by design), finding creators by hashtag or the explore page (login-walled, so discovery is via handle lists and similar-creator suggestions), or any fake-follower verdict, contractual, or pricing judgement — none of those ship here.

How to vet Instagram creators with Instagram Scraper

1. Enter your creator handles — pick profiles mode (the default) and paste handles, with or without @. The default run analyses nasa, natgeo, and bbcearth.
2. Set how to rank — dealReadiness is the default and puts who to look at first at the top. Switch to engagementQuality to vet, breakoutPotential to find emerging creators, or brandFit with a brand profile.
3. Run the actor — click Start. The leading ranked creators land within about a minute; larger lists take longer.
4. Read or download results — open the Attention Queue view in the console, or export JSON, CSV, or Excel from the Dataset tab.

First run tips

• Start with the default — { "mode": "profiles", "usernames": ["nasa", "natgeo", "bbcearth"], "rankBy": "breakoutPotential" } returns a ranked queue in one run and shows the actor's shape.
• Open the Attention Queue view first — the dataset has many views; the default Attention Queue is the 5-second read. The full record set is always there for analysts.
• Set a watchlist name to unlock monitoring — without it you get a one-shot ranking. With it, the next run returns only what changed. History warms up over time, so start it on day one.
• Give a brand profile for brand fit — brandFit and the Brand Fit view need a brandProfile; without one those fields are null.
• Private accounts are skipped — a private creator is returned as isPrivate with an error code, not as empty data. This is by design (public profiles only).

Input parameters

Parameter	Type	Required	Default	Description
mode	string	No	profiles	One of profiles, posts, watchlist, historicalSnapshot.
usernames	string[]	For profiles/watchlist	["nasa","natgeo","bbcearth"]	Handles with or without @, or profile URLs. Up to 200.
rankBy	string	No	dealReadiness	dealReadiness, breakoutPotential, engagementQuality, brandFit, momentum, followers, authenticity.
posts	string[]	For posts mode	—	Instagram post URLs or shortcodes. Up to 500.
intent	string	No	—	A job preset: vet_creators, find_emerging, track_roster, brand_match, campaign_shortlist, compare. Anything you set explicitly still wins.
compareUsernames	string[]	For compare	—	2 to 50 handles to compare side by side.
brandProfile	object	No	—	Themes, values, audience for the brand-fit engine, plus optional mustInclude / avoid terms. Matched against public profile signals only.
outputPack	string	No	raw	raw, brand, agency, analyst, scout, campaign, portfolio. agency / campaign / portfolio emit client-ready deliverables.
watchlistName	string	No	—	Set a name to enable cross-run monitoring on any mode.
filters	object	No	—	Public profile attributes only: followerTier, verified, category, language. No follower/commenter filters.
alerts	object	No	—	Tune the Signal Feed and Signal Cards: minAttentionScore, onlyNewSinceLastRun, breakoutMinMultiple, flagAnomalies, severity.
enableCreatorMemory	boolean	No	true	Keep the growth and engagement history that powers trajectories and benchmarks. Turn off to opt this run out of the shared history.
explainScores	boolean	No	false	Add each score's components and weights to every record.
taskPack	string	No	none	A curated, product-shaped summary record for a specific job (e.g. engagement-authenticity, emerging creators).
date	string	For historicalSnapshot	—	YYYY-MM-DD: reconstruct the market as of this date from tracked history.
category	string	No	—	Niche/category to slice on for snapshots and benchmarks.
tier	string	No	—	Follower tier (nano / micro / mid / macro / mega) for snapshots and benchmarks.
geo	string	No	—	Geo tag for benchmarks and the historical snapshot.
changeWindowDays	integer	No	—	Produce a "what changed" read over this many days from tracked history.
maxRecentPostsPerProfile	integer	No	12	Recent posts used per creator for the engagement read. Max 50.
maxPostsDeep	integer	No	0	Optionally pull deeper post history (more runtime and proxy cost). Max 300.
outputProfile	string	No	signals	signals (full decision layer), compat (standard field set), minimal (IDs + URLs).
proxyConfiguration	object	No	Residential US	Residential proxies required.

Input examples

• Vet a shortlist before a campaign (the canonical first run):

{ "mode": "profiles", "usernames": ["nasa", "natgeo", "bbcearth"], "rankBy": "breakoutPotential" }

• Track a roster on a schedule:

{ "mode": "watchlist", "usernames": ["natgeo", "nasa"], "watchlistName": "science-creators", "rankBy": "momentum" }

• Rank a list against a brand:

{ "mode": "profiles", "usernames": ["natgeo", "bbcearth"], "intent": "brand_match", "brandProfile": { "themes": ["nature", "science"], "values": ["education"], "audience": "curious adults" } }

Input tips

• Start with defaults — profiles mode plus breakoutPotential covers most first runs.
• Batch in one run — 200 handles in one run is more efficient than 200 single-profile runs.
• Use compat for raw ingestion — set outputProfile: "compat" when you only need the standard profile field set for an existing pipeline.

Output example

A trimmed signals-profile record (the default outputProfile: "signals"), with invented illustrative values:

{
  "recordType": "creatorDueDiligence",
  "entityType": "creator",
  "entityId": "787132",
  "handle": "natgeo",
  "summary": "Large, steady creator with engagement above its peer tier.",
  "whyNow": [
    "Engagement rate in the 88th percentile of its follower tier.",
    "Posting cadence steady over the last 90 days."
  ],
  "recommendedAction": "Shortlist for review",
  "attention": {
    "attentionPriority": "high",
    "whyNow": ["Engagement holding above the peer-tier median."],
    "deprioritizationReasons": [],
    "recommendedAction": "Shortlist for review",
    "respondWithinDays": 5
  },
  "signalProfile": {
    "label": "established-authentic",
    "strength": 0.79,
    "version": "1.0",
    "evidence": ["Engagement at or above cohort", "Steady posting cadence"]
  },
  "creatorLifecycle": "mature",
  "scores": {
    "creatorIntelligenceScore": 84,
    "dealReadinessScore": 81,
    "engagementQualityScore": 88,
    "breakoutScore": 22,
    "brandFitScore": 76,
    "momentumScore": 41,
    "stabilityScore": 90,
    "postingConsistency": 93,
    "contentVolatility": 12
  },
  "engagementQuality": {
    "engagementRate": 0.021,
    "vsCohort": 88,
    "band": "strong",
    "evidence": ["Median likes high for follower tier", "Comment-to-like ratio healthy"]
  },
  "sponsoredDensity": {
    "rate": 0.08,
    "signals": ["brand tags"],
    "commercialLoad": "light",
    "sponsoredPosts30d": 1,
    "organicPosts30d": 11,
    "saturation": "low"
  },
  "riskLedger": {
    "riskState": "healthy",
    "riskReasons": [],
    "safeLanguage": true
  },
  "history": {
    "daysTracked": 0,
    "firstSightFallback": true,
    "trajectory": "flat"
  },
  "confidence": {
    "overall": 0.7,
    "grade": "medium",
    "drivers": ["12 recent posts available"],
    "limitations": ["No prior history yet — first sight"]
  },
  "scoreEvidence": {
    "recentPostsUsed": 12,
    "medianLikes": 412000,
    "engagementRate": 0.021,
    "cohortPercentile": 88,
    "historyDays": 0
  },
  "substrate": {
    "username": "natgeo",
    "fullName": "National Geographic",
    "userId": "787132",
    "biography": "Taking our understanding of the planet further.",
    "followersCount": 281000000,
    "followingCount": 142,
    "postsCount": 31200,
    "isVerified": true,
    "isPrivate": false,
    "category": "Media",
    "externalUrl": "https://on.natgeo.com/instagram",
    "profilePicUrl": "https://instagram.example/natgeo.jpg",
    "posts": [
      { "postId": "C9xExample01", "shortcode": "C9xExample01", "caption": "Dawn over the Serengeti.", "likeCount": 412000, "commentCount": 1840, "timestamp": "2026-06-17T09:12:00Z", "isVideo": false }
    ]
  }
}

A compat record (outputProfile: "compat") — the exact standard Instagram-scraper shape, no decision fields:

{
  "username": "natgeo",
  "fullName": "National Geographic",
  "userId": "787132",
  "biography": "Taking our understanding of the planet further.",
  "followersCount": 281000000,
  "followingCount": 142,
  "postsCount": 31200,
  "isVerified": true,
  "isPrivate": false,
  "category": "Media",
  "externalUrl": "https://on.natgeo.com/instagram",
  "profilePicUrl": "https://instagram.example/natgeo.jpg",
  "posts": [
    { "postId": "C9xExample01", "shortcode": "C9xExample01", "caption": "Dawn over the Serengeti.", "likeCount": 412000, "commentCount": 1840, "timestamp": "2026-06-17T09:12:00Z", "isVideo": false, "viewCount": null }
  ]
}

Output fields

Field	Type	Description
recordType	string	creatorDueDiligence, summary, comparison, shortlist, leaderboard, signalCard, event, signalFeed, marketSnapshot, creatorReplay, coverage, or error. Omitted on compat profile rows.
entityType	string	creator or post.
entityId	string	Stable Instagram user/post ID — the cross-run dedup key.
handle	string	Creator handle, normalised without @.
summary	string	One-line plain-English read of the record.
whyNow	string[]	Up to three lines on why this creator is worth a look this run.
recommendedAction	string	A prioritisation instruction (Review, Shortlist, Vet, Track, Compare, Add to watchlist), never an outreach or transaction step.
attention	object	attentionPriority, whyNow, recommendedAction, and respondWithinDays.
signalProfile	object	Creator archetype with evidence.
creatorLifecycle	string	Growth stage from tracked history: emerging / growing / peak / mature / declining / dormant.
scores	object	0-100 bundle led by creatorIntelligenceScore, plus deal-readiness, engagement-quality, breakout, brand-fit, momentum, stability, posting consistency, content volatility.
engagementQuality	object	Engagement rate, percentile versus the peer set, a band, and evidence. Descriptive, never a fake-follower verdict.
sponsoredDensity	object	How commercial the feed is: rate, signals, commercial load, sponsored vs organic posts, saturation.
riskLedger	object	Descriptive, evidence-backed risk read (healthy / watch / review / high_uncertainty). Never a verdict on the person.
brandFit	object	Fit to the supplied brand profile: a 0-100 score and reasons. Null when no brand profile is given.
history	object	Creator timeline from tracked history. firstSightFallback: true on first sight, never a fabricated timeline.
cisTrajectory	object	The Creator Intelligence Score's 7- and 30-day change and market rank, from tracked history.
marketBenchmarks	object	Where this creator sits across the tracked market by tier, category, and geo. Honest cold-start.
watchlist	object	What changed since last run, when a watchlist is active.
substrate	object	The full raw profile and recent posts (the standard field set).
errorCode	string	On error records: stable code (NOT_FOUND, PROFILE_PRIVATE, INSUFFICIENT_HISTORY, BOT_PROTECTION, and more).

Dataset views

The dataset is organised as progressive disclosure: the default view is a 5-second read, and deeper views hold the detail. Open the one that matches your job.

1. Attention Queue (default) — which creators to look at first, their deal-readiness, archetype, why now, and next step.
2. Ignore Queue — the "skip these" read: creators with deprioritization reasons.
3. Engagement Quality / Vetting — engagement band and percentile, sponsored density, and the risk ledger. The brand/agency money-saver.
4. Breakout / Emerging — who is breaking out and emerging, by velocity, with the radar rank.
5. Brand Fit — creators ranked by fit to your brand profile, with reasons.
6. Creator Replay / Growth — per-creator growth story: history, content momentum, and the replay timeline.
7. Creator Comparison — 2 to 50 creators side by side with labeled bests.
8. Campaign Shortlist — export-ready ranked creators with fit reasons and exclusions.
9. New Since Last Run — what changed since the previous watchlist run, by change severity.
10. Signal Feed — the day's events by importance and severity, for Slack, Zapier, and agents.
11. Compat Export — the standard profile-plus-posts field set, no decision fields, for migrators.
12. Coverage & Errors — run coverage plus failures with a stable error code.
13. Summary — run-level rollup: headline, daily briefing, executive highlights, market snapshot, movers, and the time-saved estimate.

Vet Instagram creators using the API

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("ryanclinton/instagram-scraper").call(run_input={
    "mode": "profiles",
    "usernames": ["nasa", "natgeo", "bbcearth"],
    "rankBy": "breakoutPotential"
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    if item.get("recordType") == "creatorDueDiligence":
        eq = (item.get("engagementQuality") or {}).get("band")
        print(f"{item['handle']}: {item['attention']['attentionPriority']} — engagement {eq} — {item['summary']}")

JavaScript

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "YOUR_API_TOKEN" });

const run = await client.actor("ryanclinton/instagram-scraper").call({
    mode: "profiles",
    usernames: ["nasa", "natgeo", "bbcearth"],
    rankBy: "breakoutPotential"
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
for (const item of items) {
    if (item.recordType === "creatorDueDiligence") {
        const band = item.engagementQuality?.band;
        console.log(`${item.handle}: ${item.attention.attentionPriority} — engagement ${band} — ${item.summary}`);
    }
}

cURL

curl -X POST "https://api.apify.com/v2/acts/ryanclinton~instagram-scraper/runs?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{ "mode": "profiles", "usernames": ["nasa", "natgeo", "bbcearth"], "rankBy": "breakoutPotential" }'

curl "https://api.apify.com/v2/datasets/DATASET_ID/items?token=YOUR_API_TOKEN&format=json"

How Instagram Scraper works

Mental model: Handles → public profiles → engagement-quality read against the peer set → scoring and ranking → growth history → structured output.

Read public profile data

Instagram Scraper reads public Instagram profiles over required residential proxies, with no login and no private-account access. The raw record matches the standard Instagram-scraper field set exactly, so the compat output is a true drop-in. Private accounts are returned as isPrivate and skipped.

Read engagement quality against the peer set

Each creator's engagement is read relative to its peer tier, because a 10M account and a 10k account have different normal ranges. The result is a descriptive band and a percentile, never a verdict — engagement_anomaly flags both unusually low and unusually high engagement for a creator to vet, not a "fake" judgement.

Score, rank, and route

Each creator gets the Creator Intelligence Score and the supporting bundle, an archetype, and an attention priority with a recommended next step. The list is reordered by the axis you chose, with the reason attached to each record.

Remember across runs

Public profile metrics are remembered across runs, so records carry growth history, content momentum, and benchmarks. First sight is reported honestly with firstSightFallback, never invented.

Tips for best results

1. Lead with the right rank axis. engagementQuality or authenticity to vet, breakoutPotential for emerging creators, brandFit (with a brand profile) for matching, momentum for roster tracking.
2. Run watchlists on a schedule. The change briefing and deltas are most useful as a recurring feed, and history sharpens with each run.
3. Size the list for peer stats. Engagement-quality percentiles need a peer set of at least 10; add more handles in the same tier and niche for a fairer read.
4. Give a brand profile to unlock brand fit. Without a brandProfile, brandFit and the Brand Fit view are null.
5. Use output packs for deliverables. Set outputPack to agency, campaign, or portfolio for a client-ready record instead of raw data.
6. Combine with downstream actors to push the shortlist into a CRM or sheet (see below).

Combine with other Apify actors

Actor	How to combine
HubSpot Lead Pusher	Push the ranked creator shortlist into HubSpot for campaign tracking.
Website Contact Scraper	Take the creators' bio links and pull contact details from their sites.
Company Deep Research	Research the brands behind sponsored creators surfaced in a list.
Trustpilot Review Analyzer	Cross-check brand sentiment for products a creator promotes.
Website Change Monitor	Pair watchlist monitoring with website monitoring for a fuller competitor view.

Limitations

• Public profiles only. The actor reads public Instagram profile data and does not log in, access private accounts, or attempt to bypass access restrictions. Private accounts are returned as isPrivate and skipped.
• No follower or commenter data. It returns aggregate public profile metrics only, never individual follower or commenter lists or personal data.
• No hashtag or explore discovery. Instagram's hashtag and explore pages are login-walled, so discovery is via handle and URL lists plus store-backed similar-creator suggestions and the Emerging-Creator Radar, not hashtag crawling. This is an honest limitation, surfaced rather than faked.
• Engagement quality is descriptive. Bands and the risk ledger are cohort-relative reads with evidence, never a fake-follower verdict on a person or account.
• Recent posts by default. The public profile data returns roughly a dozen recent posts; deeper history via maxPostsDeep costs more runtime and proxy.
• History warms up. Cross-run history, benchmarks, and market views are thin until the actor has seen a creator over time; first sight is reported honestly, never fabricated.
• Residential proxies required. Instagram restricts automated access from datacenter IPs; the actor halts after repeated block responses and reports it through botProtection rather than returning silent empty rows.

Integrations

• Zapier — send a daily watchlist briefing to Slack or email.
• Make — route the Attention Queue into a campaign-planning board.
• Google Sheets — export ranked creators and the vetting read to a shared sheet.
• Apify API — trigger runs and pull the dataset from any client.
• Webhooks — fire on run completion to push the Signal Feed downstream.
• LangChain / LlamaIndex — feed the structured decision layer into an AI agent.

What this actor does NOT do

Honest scope, stated up front:

• No private accounts. Public profiles only; private accounts are returned as isPrivate and skipped, with no login or auth circumvention.
• No follower or commenter data. No follower/following lists, no commenter harvesting, no individual PII.
• No fake-follower verdicts. Engagement quality and the engagement-anomaly signal are descriptive cohort-relative bands with evidence, never an accusation that an audience is bought.
• No hashtag or explore crawling. Discovery is via handle and URL lists and store-backed similar-creator suggestions.
• No outreach or transaction steps. Recommended actions are prioritisation only (Review, Shortlist, Vet, Track, Compare), never Contact, DM, Hire, or Pay; no contact data is returned.
• No prices or rate quotes. rateCardProxy is a relative market-position band with evidence, never a dollar figure or a quote.
• No forecasts. Breakout, momentum, and valuation describe current and historical signals; the actor never predicts a future event or date.
• No minors targeting, private content, or biometric inference.

Responsible use

• Instagram Scraper reads publicly available Instagram profile data. It does not bypass authentication, CAPTCHAs, or access restricted content, and it does not access private accounts or follower lists.
• Users are responsible for ensuring their use complies with applicable laws and platform terms, including data protection regulations in their jurisdiction.
• Do not use extracted data for spam, harassment, or unauthorized purposes.
• For guidance on web scraping legality, see Apify's guide.

FAQ

What is the difference between an Instagram scraper and Instagram Scraper's decision layer? A basic Instagram scraper returns profile rows you read yourself. Instagram Scraper returns those rows vetted, scored, and ranked — whose audience is authentic, who is growing, who fits your brand — so the answer arrives with the data.

Can I use this to check for fake followers on an Instagram account? Not as a verdict, no — Instagram Scraper is not a fake-follower detector and does not make that accusation. What it does is an engagement authenticity check: it measures each creator's engagement rate against their peer tier, surfaces anomalous-engagement flags with evidence, and gives you a descriptive band (strong / normal / low / anomalous to vet). That is the right input for an informed vetting call, not an automated fake-follower judgement.

How do I find creators for my brand on Instagram? Supply a brandProfile with your brand's themes, values, and target audience in the input. Instagram Scraper ranks every creator on the list by brand fit, returns a brandFitScore and plain-English fit reasons for each one, and optionally builds a campaign_shortlist of ranked candidates with exclusion reasons for the ones that do not fit.

Is Instagram Scraper an Instagram follower growth tracker? Yes, across runs. It stores each creator's public follower count and engagement metrics every time a run touches them, so subsequent runs can show the trajectory — growing, peaking, mature, declining, or dormant — rather than a single snapshot. The Creator Replay view shows the full history of what was recorded across all runs.

What does Instagram Scraper give me as an Instagram account analyzer? For each handle you submit, it returns: a raw public profile (followers, posts, bio, verified status), an engagement-quality read against a peer set (rate, percentile, band), a Creator Intelligence Score, an attention priority and recommended next step, brand-fit signals if you give a brand profile, and the creator's growth history across runs. That is the standard "account analysis" job without a SaaS seat or a spreadsheet.

How do I check if an Instagram creator's engagement is authentic? Run profiles mode with rankBy: engagementQuality or authenticity and read the Engagement Quality / Vetting view. Each creator carries an engagement rate, its percentile versus the peer set, and a descriptive band — strong, normal, low, or anomalous to vet. It is a cohort-relative description, never a fake-follower verdict.

How do I find micro-influencers and emerging creators? Run profiles mode with rankBy: breakoutPotential and read the Breakout / Emerging view. It ranks small-to-mid creators who are rising early, with a radar rank, ahead of the already-obvious accounts.

How do I rank creators for a specific brand? Supply a brandProfile with themes, values, and audience, then read the Brand Fit view. Each creator gets a brandFitScore and plain-English fit reasons, matched against public profile signals only.

How do I track competitor or roster creators over time? Set a watchlistName and reuse it on a schedule. After the first run, the actor returns only what changed — new breakouts, anomalies to vet, creators going quiet — and leads with a change briefing.

What does this actor return that a raw Instagram scraper doesn't? A Creator Intelligence Score, an engagement-quality band against the peer set, a recommended next step, brand fit, sponsored density, a risk ledger, and the creator's growth history across runs.

Can I migrate from a standard Instagram scraper without changing my code? Yes. The inputs are handles and URLs as usual, and outputProfile: "compat" returns the exact standard profile-plus-posts field set, including the error-code taxonomy, so existing downstream code works unchanged.

Can I find creators by hashtag? No. Instagram's hashtag and explore pages are login-walled, so this actor does not crawl them. Discovery is via handle and URL lists plus store-backed similar-creator suggestions and the Emerging-Creator Radar.

Does it download photos, videos, or access private accounts? No. It reads public profile data only, returns no media files, and skips private accounts as isPrivate.

Does it tell me what to pay a creator? No. It returns a relative market-position band with evidence (rateCardProxy), never an actual price or rate quote.

Is it a practical alternative to an influencer-intelligence SaaS for vetting? For the core vetting job — engagement quality against peers, sponsored density, brand fit, and growth history per run — yes, on public profile data and at a per-result cost. It is not a full managed platform, and it does not return private-audience demographics.

Is it legal to scrape Instagram with this actor? It reads only public profile data and does not bypass authentication or access private accounts. Whether your use is permitted depends on your jurisdiction and intended use, including data-protection and platform-terms considerations; consult legal counsel for your specific case.

Help us improve

If you encounter issues, you can help us debug faster by enabling run sharing in your Apify account:

1. Go to Account Settings > Privacy
2. Enable Share runs with public Actor creators

This lets us see your run details when something goes wrong, so we can fix issues faster. Your data is only visible to the actor developer, not publicly.

Support

Found a bug or have a feature request? Open an issue in the Issues tab on this actor's page. For custom solutions or enterprise integrations, reach out through the Apify platform.