Instagram Followers Scraper & Related Profile Expansion

Instagram Scraper — Followers, Related Profiles and Audience Overlap

Instagram Followers Scraper & Related Profile Expansion collects real followers for one or more seed Instagram profiles, then discovers each seed's related/suggested profiles and computes a genuine shared-audience percentage — how much of a related profile's own follower sample also follows the seed. It's built for influencer marketing teams vetting lookalike creators, agencies mapping competitive audiences, and researchers who need real overlap data instead of a guessed similarity score.

What is Instagram Followers Scraper & Related Profile Expansion?

Instagram Followers Scraper & Related Profile Expansion is an Apify Actor that collects a seed profile's followers and, optionally, discovers and audience-fit-scores its related/suggested profiles. An Instagram sessionid cookie is optional but recommended for better success rates. Key capabilities:

• Collect real followers for one or many seed profiles in a single run
• Discover each seed's related/suggested profiles via Instagram's own related-profiles data
• Sample each related profile's own followers and compute a real sharedAudiencePct — the percentage that also follows the seed
• Rank related profiles by shared-audience percentage, descending
• Tune scoring depth with per-seed and per-related-profile sample-size caps

What data can I extract with Instagram Followers Scraper & Related Profile Expansion?

Field	Example Value	Use Case
username / full_name	"cristiano_fanpage" / "CR7 Fan Page"	Identify the follower or related-profile account
type / sourceType	"related_profile" / "related_profile"	Distinguish a plain follower row from a scored related-profile row
relatedToUsername	"cristiano"	See which seed profile this related profile is scored against
sharedAudiencePct	18.0	The core differentiator — real percentage of sampled followers shared with the seed
audienceOverlapTier	"medium"	Quick bucket for prioritizing related profiles (high/medium/low)
followerSampleSize / overlapCount	50 / 9	See exactly how the percentage was computed
is_verified / is_private	false / false	Filter to verified or public-only accounts
followed_by	null on related-profile rows	Present only on genuine follower rows
profile_pic_url / profileUrl	CDN image URL / profile link	Visual and direct-link reference
scrapedAt	"2026-07-26T14:02:11+00:00"	Record when the row was collected
success	true	Confirm the row completed without error

Shared-audience scoring

sharedAudiencePct is a real, computed metric, not an estimate: for each related/suggested profile discovered for a seed, the Actor samples up to relatedFollowerSampleSize of that related profile's own followers, then checks how many of those sampled follower IDs also appear in the seed's own collected follower set. overlapCount is the raw number of matches, followerSampleSize is exactly how many followers were sampled, and sharedAudiencePct = overlapCount / followerSampleSize × 100. audienceOverlapTier buckets that percentage into high/medium/low so results can be triaged at a glance, and every scored related-profile row is tagged type: "related_profile" so it's never confused with a genuine follower row in the same dataset.

Seed targeting and scoring depth

targetProfiles accepts one or many seed profiles in the same run. maxFollowersPerProfile caps how many followers are collected per seed. enableRelatedProfileScoring toggles the entire discovery-and-scoring pipeline on or off; when on, maxRelatedToScore caps how many related profiles per seed get scored, and relatedFollowerSampleSize controls how deep each related profile's own follower sample goes.

Why not build this yourself?

Instagram's Graph API has no endpoint for pulling an arbitrary profile's follower list, its related/suggested profiles, or any cross-profile audience-overlap metric — none of that exists in any form for third-party access. Building an equivalent tool yourself means implementing Instagram's mobile-web followers pagination, the related-profiles discovery edge, a second-pass follower sample for every related profile you want to score, and the set-intersection math to turn two raw ID lists into a genuine overlap percentage. All of that is already implemented in this Actor's source.

How to use data extracted from Instagram?

Influencer marketing and lookalike vetting

Run a target creator's targetProfiles with scoring enabled to get a ranked list of related creators by sharedAudiencePct — the ones with genuinely high shared audience are the most defensible lookalike candidates for a similar-audience partnership, rather than accounts that merely appear in Instagram's suggestion algorithm without real audience overlap.

Agencies mapping competitive audiences

Score a client's competitors as seed profiles and compare audienceOverlapTier distributions across them to see which competitor's audience most closely mirrors the client's own, informing where to focus competitive campaign spend.

Market and audience research

Track how sharedAudiencePct changes for a brand's related-profile set over repeated scheduled runs to see whether the brand's audience is converging with or diverging from its category peers over time.

AI agents and automated pipelines

An agent can call this Actor to pre-qualify lookalike accounts before triggering an outreach workflow — filtering on audienceOverlapTier to only surface related profiles with a defensible, real audience overlap.

🔼 Input sample

Parameter	Required	Type	Description	Example Value
targetProfiles	No	array	Seed profile URLs or usernames to collect followers and related profiles for	["https://www.instagram.com/cristiano/"]
maxFollowersPerProfile	No	integer (1-100,000)	Max followers to collect per seed profile	100 (default)
enableRelatedProfileScoring	No	boolean	Toggle the related-profile discovery + scoring pipeline	true (default)
maxRelatedToScore	No	integer (1-50)	Cap on related profiles scored per seed	10 (default)
relatedFollowerSampleSize	No	integer (10-200)	Followers sampled per related profile for overlap scoring	50 (default)
instagramSessionId	No	string (secret)	Instagram sessionid cookie; optional but recommended	"(your session cookie)"
proxyConfiguration	No	object	Proxy settings; auto-escalates on repeated blocks	{"useApifyProxy": true}

{
  "targetProfiles": ["https://www.instagram.com/cristiano/"],
  "maxFollowersPerProfile": 500,
  "enableRelatedProfileScoring": true,
  "maxRelatedToScore": 15
}

Common pitfall: maxRelatedToScore and relatedFollowerSampleSize both add extra requests per seed (one discovery request plus one follower-sample request per related profile checked) — a high value on both, across many seeds, multiplies run time and request volume quickly.

🔽 Output sample

Output is typed, normalized JSON — one row per follower or scored related profile (exportable as JSON, CSV, or Excel).

{
  "pk": "9871234567",
  "type": "related_profile",
  "sourceType": "related_profile",
  "username": "cristiano_fanpage",
  "full_name": "CR7 Fan Page",
  "is_verified": false,
  "is_private": false,
  "followed_by": null,
  "relatedToUsername": "cristiano",
  "sharedAudiencePct": 18.0,
  "audienceOverlapTier": "medium",
  "followerSampleSize": 50,
  "overlapCount": 9,
  "profile_pic_url": "https://scontent.cdninstagram.com/...",
  "profileUrl": "https://www.instagram.com/cristiano_fanpage/",
  "pk_id": "9871234567",
  "id": "9871234567",
  "fbid_v2": "",
  "third_party_downloads_enabled": 0,
  "strong_id__": "9871234567",
  "profile_pic_id": "",
  "has_anonymous_profile_picture": false,
  "account_badges": [],
  "latest_reel_media": 0,
  "is_favorite": false,
  "scrapedAt": "2026-07-26T14:02:11+00:00",
  "success": true
}

All 27 fields shown above are the Actor's real dataset columns — this is the full output shape, not a subset.

How do you filter and target specific profiles?

targetProfiles is the core scope control — supply one or many seed profiles to process in the same run. enableRelatedProfileScoring is the category switch: off, you get a plain follower collection; on, every seed also produces scored related-profile rows. Quality thresholds come from audienceOverlapTier/sharedAudiencePct after the fact — filter your exported dataset to audienceOverlapTier: "high" for only the strongest lookalike candidates. Volume is controlled by three separate caps: maxFollowersPerProfile for the seed's own follower collection, maxRelatedToScore for how many related profiles get scored, and relatedFollowerSampleSize for how deep each related profile's own follower sample goes — tune the last two down first if you need faster, cheaper runs across many seeds.

{ "targetProfiles": ["nike"], "maxFollowersPerProfile": 1000, "enableRelatedProfileScoring": true, "maxRelatedToScore": 20 }

{ "targetProfiles": ["cristiano", "nike"], "enableRelatedProfileScoring": true, "relatedFollowerSampleSize": 100 }

{ "targetProfiles": ["https://www.instagram.com/nike/"], "enableRelatedProfileScoring": false, "maxFollowersPerProfile": 5000 }

▶️ Want to try other Instagram scrapers?

Scraper Name	What it extracts
Instagram Following Scraper: Related Profiles List	Following lists plus related-profile expansion
Instagram Related Person Scraper With Profile Enrichment	Related/lookalike networks for a given account
Instagram Followers: With Bot Profile checker	Follower/following lists with quality/authenticity scoring
Instagram Followers Count Scraper	A lightweight follower-count-only lookup
Instagram Profile Scraper & Account Privacy Checker	Full profile details plus privacy-status checking
LinkedIn Company Employees Scraper With Growth Tracker	Comparable audience-composition data for LinkedIn companies

How to extract Instagram data programmatically

Every run is a standard Apify Actor call — one API request with your token, JSON input, JSON results back.

Python example

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_API_TOKEN>")

run_input = {
    "targetProfiles": ["https://www.instagram.com/cristiano/"],
    "maxFollowersPerProfile": 500,
    "enableRelatedProfileScoring": True,
}

run = client.actor("<YOUR_USERNAME>/instagram-followers-scraper-related-profile-expansion").call(run_input=run_input)

for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    if row.get("type") == "related_profile":
        print(row["username"], row["sharedAudiencePct"], row["audienceOverlapTier"])

Export to spreadsheets or CRM

Export the dataset directly as CSV or Excel, then map username/profileUrl to your CRM's contact fields and sharedAudiencePct/audienceOverlapTier to a scoring column for prioritizing lookalike outreach.

Is it legal to scrape Instagram followers and related profiles?

Follower usernames, full names, and profile pictures are personal data, so GDPR and CCPA obligations apply to storing and using this data. Public Instagram follower and related-profile lists are visible to any logged-out visitor on the profile itself, but downstream storage for research or vetting purposes should follow applicable data-protection rules. Consult legal counsel for commercial applications involving bulk storage of personal data.

❓ FAQ

How is sharedAudiencePct actually calculated?

It's a real, computed set-intersection: the Actor samples a related profile's own followers, checks how many of those sampled IDs also appear in the seed's own collected follower list, and divides overlap count by sample size. It is not an estimate or a similarity guess — overlapCount and followerSampleSize are shown alongside the percentage so you can verify the math yourself.

Can I get related profiles without also collecting the seed's followers?

No — the seed's own follower list is collected first and used as the comparison set for scoring, so seed follower collection always runs when enableRelatedProfileScoring is on. Set maxFollowersPerProfile low if you want to minimize that cost.

How many related profiles can be scored per seed?

maxRelatedToScore (1-50, default 10) caps this. Each scored related profile costs one extra follower-sample request, so higher caps mean longer, costlier runs.

Do I need an Instagram account to use this?

No, but it's recommended — supplying your Instagram sessionid cookie via instagramSessionId improves success rates; the Actor still runs without one.

Does Instagram Followers Scraper & Related Profile Expansion work with Claude, ChatGPT, and AI agent frameworks?

It has no dedicated MCP server registration in this Actor's current setup, but it is callable as a standard Apify API endpoint by any agent framework that can make an authenticated HTTP request and parse JSON.

How does this compare to other Instagram related-profile scrapers?

No independently verifiable competitor listing could be confirmed at the time of writing, so no specific comparison is made here. This Actor's distinguishing feature is the real, sampled shared-audience percentage rather than just a list of Instagram's suggested profiles.

What does audienceOverlapTier mean exactly?

It's a bucket derived from sharedAudiencePct — high, medium, or low — that lets you triage related profiles at a glance without reading raw percentages for every row.

Can I use this without any Instagram credentials?

Yes — instagramSessionId is optional. The run will attempt without it, though Instagram may block requests more often.

Conclusion

Instagram Followers Scraper & Related Profile Expansion turns a seed profile into both a real follower list and a ranked set of related profiles scored by genuine shared audience — computed overlap, not a guessed similarity score. It's built for influencer marketing teams, agencies, and researchers who need defensible lookalike data before committing outreach budget. Start a run with your seed profiles and scoring enabled to see which related accounts actually share the seed's audience.