📊 Instagram Influencer Engagement Scraper

Turn Instagram handles into decision-ready creator intelligence — no spreadsheets, no manual work.

Feed this Actor one or more public Instagram usernames. It returns a clean, structured engagement profile for each creator: follower snapshot, content performance across feed and Reels, engagement rates, and quality coverage signals — all in a single dataset record per creator.

Built for marketing teams, talent agencies, and growth analysts who need reliable creator data at scale, not just follower counts.

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✦ What This Actor Actually Delivers

Most scrapers dump raw post data and leave the analysis to you. This Actor does the work upstream.

For every username you submit, it:

1. Fetches the public profile — followers, following, post count, verified status, external URL
2. Collects up to 72 feed posts and 36 Reels/clips — the two content types Instagram treats differently
3. Calculates engagement separately for each format — because mixing feed and Reels into one rate produces meaningless numbers
4. Reports coverage signals — so you know how much of the sample had usable view data before trusting the metrics
5. Packages everything into one clean dataset record — ready to export, query, or plug into a dashboard

The result is a creator intelligence snapshot, not a pile of raw API output.

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🎯 Who This Is For

Use Case	What You Get
Influencer vetting	Engagement rates and content skew before you reach out
Campaign planning	Compare multiple creators side-by-side with consistent metrics
Competitor monitoring	Track content strategy and engagement trends over time
Creator scorecards	Build internal benchmarks with standardized output
AI & reporting workflows	Clean JSON structure that feeds directly into downstream tools

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📦 Output Structure Explained

Each processed username returns one dataset record with three sections.

creator — Profile Snapshot

The public account data captured at run time.

"creator": {
  "id": "123456789",
  "username": "creator_handle",
  "fullName": "Creator Name",
  "followersCount": 250000,
  "followsCount": 420,
  "verified": true,
  "postsCount": 812,
  "profilePicUrl": "https://...",
  "external_url": "https://..."
}

Field	What It Tells You
followersCount	Audience size at time of run
followsCount	Following count — useful for audience-to-following ratio checks
verified	Whether the account holds a Meta verification badge
postsCount	Total lifetime posts on the account
external_url	Link in bio — often reveals brand affiliations or personal sites

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engagement — Performance Metrics

The core of the dataset. Every metric is computed from the actual content sample retrieved, not estimated.

"engagement": {
  "overall_interactions": 125912,
  "clips_engagement_rate_by_views": 3.28,
  "feed_avg_engagement_rate_by_followers": 0.41,
  "clips_avg_views": 24500.2,
  "feed_avg_engagement": 1015.1,
  "clips_avg_engagement": 2674.5,
  "posts_contribution_pct": 60,
  "clips_contribution_pct": 40,
  "engagement_skew_clips_over_feed": 2.635,
  "avg_interactions_per_content": 1678.826667,
  "interactions_per_1k_followers": 503.648
}

Metric-by-Metric Breakdown

overall_interactions The raw sum of all likes and comments across every feed post and clip in the sample. Think of this as the total engagement volume — a signal of the creator's absolute reach and activity level, before any rate calculations.

feed_avg_engagement_rate_by_followers (%) Average engagement per feed post, divided by follower count, expressed as a percentage. This is the industry-standard feed engagement rate. Benchmark it against typical ranges for the creator's tier:

• Nano (< 10K followers): 3–6%
• Micro (10K–100K): 1–3%
• Macro (100K–1M): 0.5–1.5%
• Mega (1M+): 0.1–0.5%

A rate below these ranges can indicate an inflated or disengaged audience.

clips_engagement_rate_by_views (%) Average engagement per Reel, divided by view count — not followers. This is the correct denominator for Reels because views are the primary distribution unit on that surface. A rate above 2% is generally considered strong for Reels.

clips_avg_views Average views per Reel across the sample. A key reach signal for Reels-first creators. High views with low engagement rate can indicate passive viewers rather than an engaged community.

feed_avg_engagement Average raw interactions (likes + comments) per feed post. Useful for understanding content resonance without follower-count distortion, especially when comparing creators with similar follower counts.

clips_avg_engagement Average raw interactions per Reel. Compare this against feed_avg_engagement to immediately see which format drives more interaction for this creator.

posts_contribution_pct / clips_contribution_pct The percentage of the content sample made up by feed posts versus Reels. A creator with 80% clips contribution is primarily a Reels-first account — important context for campaign format decisions.

engagement_skew_clips_over_feed The ratio of clips average engagement to feed average engagement. A value above 1.0 means Reels outperform feed posts. A value below 1.0 means feed is stronger. In the example above, 2.635 means Reels drive 2.6× more engagement per piece of content than feed posts.

Use this to answer: "Should I brief this creator for a Reel or a static post?"

avg_interactions_per_content Average interactions across all content types combined — feed and clips pooled. A format-agnostic engagement volume signal useful for quick cross-creator comparisons.

interactions_per_1k_followers Total interactions across the sample, normalized per 1,000 followers. This is the most useful single number for comparing creators across different audience sizes. Higher is always better.

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coverage — Data Quality Signals

Before trusting any metric, check coverage. It tells you how much of the sample had usable data.

"coverage": {
  "total_items": 111,
  "clips_count": 36,
  "feed_count": 75,
  "clips_view_coverage": 1,
  "feed_view_coverage": 0
}

Field	What It Tells You
total_items	Total content pieces in the sample (feed + clips)
clips_count	Number of Reels retrieved
feed_count	Number of feed posts retrieved
clips_view_coverage	Share of clips with available view data (0–1). 1 = full coverage, 0 = no views returned
feed_view_coverage	Share of feed posts with view data. Often 0 — Instagram does not consistently expose feed view counts

A clips_view_coverage of 0 means the clips engagement rate was calculated on a limited sample — treat that metric with more caution. A feed_view_coverage of 0 is expected and normal.

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🚀 How to Run It

1. Open the Actor in Apify Console and go to the Input tab
2. Add one or more Instagram usernames to the usernames array — no @ prefix needed
3. Click Start
4. The Actor validates access before scraping begins
5. Open the Dataset tab to review and export results

Input format:

{
  "usernames": ["natgeo", "nasa", "bulebarbie_official"]
}

Free plan: 1 username per day, returns 1 engagement result.
Paid plan: Full username list, runs until complete or spending limit is reached.

Export formats: JSON · CSV · Excel · XML · HTML

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💡 Tips for Getting the Most Out of Results

• Compare feed_avg_engagement vs clips_avg_engagement side by side to determine the creator's strongest format before deciding on deliverable type
• Use interactions_per_1k_followers as your primary comparison metric when evaluating creators of different sizes — it removes audience-size bias
• Check clips_view_coverage before citing clips_engagement_rate_by_views — a coverage of 0.3 means only 30% of clips had view data, making the rate less reliable
• Watch engagement_skew_clips_over_feed — a value above 2.0 signals a Reels-dominant creator; a value below 0.8 signals a feed-first creator
• Submit your highest-priority usernames first if you're on the free plan
• Start small on paid runs — test with 5–10 accounts, validate the output matches your needs, then scale

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💰 Pricing

Cost scales with the number of usernames and the volume of content each profile has. Free users get one username per day. Paid users can run the full list within their spending limit.

Start small, validate output quality, then scale. The Actor is designed to be cost-efficient by fetching only the content needed to compute reliable engagement metrics.

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⚠️ Disclaimers

• This Actor processes public Instagram profiles only. Private accounts are not accessible and will produce a logged failure record in the dataset.
• You are responsible for using output in compliance with applicable laws, Instagram's Terms of Service, and your organization's data policies.
• Metrics are computed from sampled content. Results reflect the sample window, not all-time account performance.
• View data availability on feed posts is limited by Instagram's API — feed_view_coverage of 0 is expected behavior, not a bug.

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🛠 Support

For questions, bugs, or feature requests, use the Apify Actor Issues tab on this Actor's page.

If you need a custom output shape, different metric definitions, or a tailored workflow built on this Actor, that option is available — reach out via the Issues tab.