Instagram Follower Count Scraper

Want to know how big an Instagram account really is without opening the app and squinting at the profile? Type in a handle and this scraper hands you the follower count, who they follow, how many posts they've shared, their engagement rate, and the average likes and comments per post. Check one creator or paste a whole list of handles and get a clean row for each. Good for sizing up influencers, tracking competitors, or building a dataset of accounts you care about.

What you get

Every handle you submit turns into one tidy row, and the rows all share the same shape. When a value isn't available it comes back as null rather than disappearing, so your columns line up when you load the data into a spreadsheet or database. Each row carries:

• Account identity — handle, fullName, profileLink
• Reach — followerCount, followingCount, postCount
• Engagement — engagementPercent, avgLikes, avgComments
• Run metadata — collectedAt, errorMessage

Quick start

1. Click Try for free and open the input form.
2. Type one handle into Single handle, or paste several into Handle list (leave off the @).
3. Set a Result cap if you want to limit the run, and adjust the Request timeout if needed.
4. Hit Start, then download the results as JSON, CSV, Excel, or XML once it wraps up.

Use cases

• Influencer vetting — confirm a creator's real follower count and engagement before you pay for a post
• Competitor tracking — log rival brand accounts over time and watch how their reach moves
• Agency reporting — pull follower and engagement stats for a roster of client accounts in one run
• Lead research — qualify accounts by size and activity before you reach out
• Trend spotting — measure which accounts in a niche are growing and which are flat

Input

Field	Type	Required	Description
profileHandle	string	One of profileHandle or profileHandles	A single Instagram handle to check, without the @. Example: natgeo.
profileHandles	array of strings	One of profileHandle or profileHandles	A list of Instagram handles to pull in one run, each without the @.
resultsLimit	integer	No	Most handles to process per run. Default 50.
timeoutSeconds	integer	No	Seconds to wait on each request before giving up. Default 45.

Example input

{
    "profileHandle": "natgeo",
    "profileHandles": ["natgeo", "nasa"],
    "resultsLimit": 50,
    "timeoutSeconds": 45
}

Output

Each handle you submit produces exactly one row, and every field is always present — values that couldn't be read come back as null so the dataset stays rectangular.

Example output

{
    "handle": "natgeo",
    "fullName": "National Geographic",
    "followerCount": 281000000,
    "followingCount": 158,
    "postCount": 31420,
    "engagementPercent": "0.12%",
    "avgLikes": 142500,
    "avgComments": 980,
    "profileLink": "https://www.instagram.com/natgeo/",
    "collectedAt": "2026-06-29T12:00:00.000000+00:00",
    "errorMessage": null
}

Output fields

Field	Type	Description
handle	string	The Instagram handle that was looked up
fullName	string	Public display name shown on the profile
followerCount	integer	Number of accounts following this handle
followingCount	integer	Number of accounts this handle follows
postCount	integer	Total posts shared on the profile
engagementPercent	string	Engagement rate as a percentage string, such as 0.12%
avgLikes	integer	Average likes per recent post
avgComments	integer	Average comments per recent post
profileLink	string	Direct URL to the Instagram profile
collectedAt	string	ISO 8601 timestamp marking when the row was captured
errorMessage	string	Reason a handle could not be processed; null on success

Tips for best results

• Start with a few handles. Run three or four before a big batch so you can confirm the output fits your pipeline.
• Drop the @ sign. Handles are read without it; natgeo works, and @natgeo gets trimmed for you anyway.
• Use the result cap to control spend. Set resultsLimit low for test runs, then raise it for the full list.
• Raise the timeout if requests stall. Bump timeoutSeconds toward 60 if you see slow responses.
• A handle that errors still returns a row. Failed lookups come back with the fields as null and a filled errorMessage, so nothing silently drops.

How can I use Instagram follower data?

How can I use the Instagram Follower Count Scraper to vet influencers? Paste the handles of the creators you're considering and read back their follower count, engagement rate, and average likes and comments. Compare those numbers side by side to see who actually drives interaction versus who just has a big audience, before you spend on a partnership.

How can I track Instagram competitor follower counts over time? Build a list of competitor handles and run the scraper on a schedule. Each run writes one row per account with the current followerCount, postCount, and engagement figures, so you can stack the exports and chart how each account grows week over week.

How can I pull Instagram follower stats for a list of accounts at once? Drop your accounts into profileHandles and set resultsLimit to cover the batch. Every handle comes back as a single row with reach and engagement data, turning a plain list of usernames into a structured dataset you can export to CSV or feed into a report.

Is it legal to scrape data?

Our actors are ethical and do not extract any private user data, such as email addresses or private contact information. They only extract what the user has chosen to share publicly. We therefore believe that our actors, when used for ethical purposes by Apify users, are safe.

However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.

You can also read Apify's blog post on the legality of web scraping.

Support

Questions, feature requests, or a field you'd like added? Reach out at data.apify@proton.me and we'll get back to you.