Instagram Influencer Analytics Scraper

Calculate Instagram engagement rate, posting cadence, content mix, sponsored posts, and top-performing content for any public creator profile. No login. No cookies. No proxies. Just paste a list of usernames and get decision-ready creator analytics in seconds.

Built for talent teams, brand marketers, influencer agencies, and growth analysts who need consistent influencer metrics at scale — not raw post dumps you have to clean up yourself.

Why use this Actor

• Engagement rate done right — separate engagement rates for feed posts (vs. followers) and Reels (vs. views), because mixing them produces meaningless numbers
• Sponsored content detection — see which brands a creator has already worked with before you send your outreach
• Authenticity signals — save-to-like and comment-to-like ratios catch fake or disengaged audiences that follower count alone misses
• Posting cadence and recency — instantly filter out creators who've gone dormant
• Top-performing posts surfaced — three highest-engagement posts with URLs, so you can reference them in your brief
• Batch processing — submit hundreds of usernames in one run; failed handles produce a single error record without stopping the rest
• Clean structured output — one JSON record per creator, ready for Google Sheets, Airtable, BI tools, or AI workflows

What you get

Every public Instagram username produces one dataset record with these sections:

• Profile snapshot — follower count, following count, post count, verified status, full name, bio link, profile picture URL
• Engagement metrics — engagement rate by followers, engagement rate by views, average likes per post, average comments per post, total interactions, interactions per 1,000 followers
• Posting cadence — last post date, days since last post, posts per week, posts per month
• Content mix — feed photos, feed videos, feed carousels, Reels count
• Quality ratios — save-to-like ratio, comment-to-like ratio
• Sponsored content — paid partnership count, ad keyword count, sponsored percentage, list of recent brand partners
• Topic signals — top hashtags and top @mentions (collab partners, brands, recurring themes)
• Top 3 posts — highest-engagement posts with URLs, captions, like and comment counts, view counts
• Coverage signals — data-quality flags so you know how reliable each metric is

Export to JSON, CSV, Excel, XML, or HTML directly from the Apify console.

Use cases

• Influencer vetting — calculate engagement rate, check authenticity signals, and see brand-deal history before reaching out
• Campaign planning — compare 50+ creators side-by-side with consistent metrics in one CSV
• Talent discovery and shortlisting — filter by posts-per-week, engagement rate, and Reels skew to find creators who match your brief
• Competitive intelligence — track how brand-aligned creators are posting, what they're tagging, and which competitors are sponsoring them
• Creator scorecards and reporting — build internal dashboards with standardized metrics across hundreds of accounts
• Data for AI agents and LLMs — clean structured JSON that drops directly into prompt context for outreach copy, scoring, or recommendations

How to use

1. Open the Actor and paste one or more public Instagram usernames into the Usernames field (with or without @)
2. Optionally adjust Feed posts sample size (default 72) and Reels sample size (default 36) — larger samples produce more reliable averages
3. Click Start
4. Open the Dataset tab once the run finishes — one record per username, ready to export

Private accounts and missing handles produce a { username, error } record so a single bad input never stops the rest of the batch.

Sample output

{
  "username": "natgeo",
  "creator": {
    "id": 787132,
    "username": "natgeo",
    "fullName": "National Geographic",
    "followersCount": 269597381,
    "followsCount": 194,
    "verified": true,
    "postsCount": 31620,
    "profilePicUrl": "https://…",
    "external_url": "http://visitstore.bio/natgeo"
  },
  "engagement": {
    "overall_interactions": 1791003,
    "clips_engagement_rate_by_views": 5.95,
    "feed_avg_engagement_rate_by_followers": 0.03,
    "clips_avg_views": 2165395.5,
    "feed_avg_engagement": 84806,
    "clips_avg_engagement": 128888.5,
    "posts_contribution_pct": 67,
    "clips_contribution_pct": 33,
    "engagement_skew_clips_over_feed": 1.52,
    "avg_interactions_per_content": 99500.17,
    "interactions_per_1k_followers": 6.643
  },
  "cadence": {
    "last_post_at": "2026-05-08T19:09:25.000Z",
    "days_since_last_post": 0.4,
    "posts_per_week": 5.19,
    "posts_per_month": 22.26,
    "sample_window_days": 24.3
  },
  "content_mix": {
    "feed_photos": 4,
    "feed_videos": 7,
    "feed_carousels": 1,
    "reels": 6
  },
  "quality": {
    "avg_save_to_like_ratio": 0.0428,
    "avg_comment_to_like_ratio": 0.0077,
    "save_data_coverage": 0.333
  },
  "sponsored": {
    "paid_partnership_count": 1,
    "caption_ad_keyword_count": 1,
    "total_sponsored": 1,
    "sponsored_pct": 5.6,
    "recent_partners": ["rolex"]
  },
  "topics": {
    "top_hashtags": [
      { "tag": "tucciinitaly", "count": 2 },
      { "tag": "americasnationalparks", "count": 2 }
    ],
    "top_mentions": [
      { "handle": "disneyplus", "count": 9 },
      { "handle": "hulu", "count": 4 }
    ]
  },
  "top_posts": [
    {
      "url": "https://www.instagram.com/p/DYFBt6HAP1O/",
      "product_type": "clips",
      "taken_at": "2026-05-08T13:01:31.000Z",
      "like_count": 501273,
      "comment_count": 6320,
      "view_count": 5113029,
      "caption_excerpt": "Wishing a Happy Birthday to Sir David Attenborough…"
    }
  ],
  "coverage": {
    "total_items": 18,
    "clips_count": 6,
    "feed_count": 12,
    "clips_view_coverage": 1,
    "feed_view_coverage": 0.583
  }
}

Metric reference

Engagement metrics

Field	What it tells you
feed_avg_engagement_rate_by_followers	Industry-standard feed engagement rate (likes + comments per post ÷ followers, %)
clips_engagement_rate_by_views	Reels engagement rate using views as the denominator (the correct one for short-form video)
clips_avg_views	Average view count across the Reels sample — a key reach signal
engagement_skew_clips_over_feed	Reels-to-feed engagement ratio. Above 1.0 = Reels-dominant. Below 1.0 = feed-dominant.
interactions_per_1k_followers	Total interactions normalized per 1,000 followers — best for comparing creators of different audience sizes

Engagement rate benchmarks by tier (industry-standard):

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

A feed engagement rate well below the band for the creator's tier often indicates an inflated or disengaged audience.

Cadence

days_since_last_post is the recency check most marketers gate on first. Above 14 days usually means the creator has slowed down — filter these out before deeper analysis. posts_per_week and posts_per_month are derived from the timestamp range of the analyzed sample.

Quality ratios — the real authenticity signals

Follower count and even engagement rate can be inflated. Two ratios are much harder to fake:

• avg_save_to_like_ratio — share of likes that converted into saves. High ratios (>0.05) signal utility content the audience comes back to.
• avg_comment_to_like_ratio — share of likes that turned into comments. High ratios (>0.02) signal genuinely engaged audiences vs. passive likers.

A creator with strong save and comment ratios has a real audience. Use these alongside engagement rate, not in place of it.

save_data_coverage reports the share of analyzed posts that returned a save count — treat the save ratio with caution if coverage is below 0.5.

Sponsored content

• paid_partnership_count — posts using Instagram's official paid-partnership tag (is_paid_partnership: true or sponsor_tags)
• caption_ad_keyword_count — posts whose caption contains #ad, #sponsored, [ad], "paid partnership with", etc.
• total_sponsored — union of the two (deduplicated)
• sponsored_pct — share of analyzed sample that is sponsored content
• recent_partners — handles of brands tagged via Instagram's official paid-partnership system, ordered by frequency

A creator with sponsored_pct above ~30% is heavily monetized. Below 5% likely hasn't done many brand deals. The recent_partners list is the fastest way to vet brand fit and exclusivity conflicts.

Topics

• top_hashtags — most-used hashtags across the sample. Reveals niche, ongoing campaigns, and themed content series.
• top_mentions — most-tagged @ handles. Reveals collab partners, recurring brand relationships, and the creator's network.

Top posts

Three highest-engagement posts in the sample, ranked by likes + comments. Each entry has the post URL, product type, timestamp, raw counts, and a caption excerpt — useful when briefing creators ("we noticed your Reel about X performed exceptionally well").

Coverage signals

Read this before citing the metrics:

• clips_view_coverage — share of Reels for which view data was returned (0–1). Below 1 means the Reels engagement rate was computed on partial view data.
• feed_view_coverage — share of feed posts with view data. Often 0 because Instagram does not consistently expose feed view counts. This is expected behavior, not a bug.

FAQ

Do I need an Instagram account or login? No. The Actor works on public profile data only — no Instagram account, cookies, or login required.

How do I check if my audience or competitor's audience is real? Run their handle through this Actor and look at three things together: feed_avg_engagement_rate_by_followers (compared to the tier benchmarks above), avg_comment_to_like_ratio (>0.02 is healthy), and avg_save_to_like_ratio (>0.05 signals utility content). All three low = likely fake or disengaged followers.

Can this calculate Instagram engagement rate at scale? Yes. Submit hundreds of usernames in a single run. Each produces one row, so the dataset CSV opens directly as a creator leaderboard.

Does it work for private accounts? No. Private profiles return an error record. The Actor only analyzes public Instagram data.

Can it detect sponsored or branded content? Yes — both Instagram's official paid-partnership tag and caption keywords (#ad, #sponsored, [paid partnership], etc.). See the sponsored section of the output for partner handles and counts. Note that undisclosed sponsored content cannot be detected by any tool.

How fresh is the data? Live — every run hits Instagram's current public data. Engagement metrics reflect the most recent feed posts and Reels in the sample window, not lifetime account performance.

Can I use this output with AI agents or LLMs? Yes. The structured JSON output drops cleanly into prompt context for outreach generation, creator scoring, or recommendation pipelines. Each creator is one self-contained record.

How many posts does it analyze per creator? Up to 72 feed posts and 36 Reels by default. Both are configurable per run — larger samples produce more reliable averages but cost more.

What input formats are supported? A list of Instagram usernames, with or without the @ prefix. Whitespace and case are normalized automatically.

Do I get the post URLs? Yes — the top_posts section includes the full Instagram URL for each highest-engagement post, ready to share in a brief or pitch deck.

Tips for getting the most out of results

• Compare feed_avg_engagement and clips_avg_engagement to decide which format to brief a creator for
• Use interactions_per_1k_followers when comparing creators across very different audience sizes
• Treat clips_engagement_rate_by_views with caution if clips_view_coverage is below 0.5
• Filter out creators with days_since_last_post above your acceptable cutoff before deeper analysis
• High save-to-like AND high comment-to-like ratios is the strongest signal of an authentic, engaged audience
• Check recent_partners before pitching — if a competitor brand appears, your offer may need to address exclusivity
• Test on a small batch of 3–5 usernames before scaling to a large list

Limitations

• Only public Instagram profiles can be analyzed — private accounts return a logged failure record
• Metrics are computed from the most recent feed posts and Reels in the sample window, not lifetime account performance
• Instagram does not expose view counts on most feed posts, so feed_view_coverage is typically 0
• Save count data is only sometimes returned for older posts — save_data_coverage reports availability
• Sponsorship detection works on captions and Instagram's official paid-partnership tag — undisclosed sponsored content cannot be detected by any tool

Support

For bugs, feature requests, or custom output shapes, use the Issues tab on this Actor's page.