What percentage of Instagram followers are typically fake?

Industry studies suggest 10-25% of followers on an average Instagram account are fake or inactive. Accounts that have used growth services, follow-for-follow tactics, or been targeted by bot campaigns may have significantly higher percentages. Influencer accounts are often targeted by bot follow campaigns, sometimes reaching 30-40% fake followers.

Will removing fake followers hurt my account?

No — removing fake followers actually helps your account. Your engagement rate (likes and comments divided by followers) improves because you are removing followers who never engaged. Better engagement rates lead to better algorithmic visibility. Brands evaluating you for partnerships also prefer authentic follower bases over inflated numbers.

Can I prevent bots from following me in the future?

Setting your account to private is the most effective prevention, but it limits your growth. For public accounts, avoid follow-for-follow groups, do not purchase followers, and be cautious with engagement pods. Regularly auditing your followers using this process catches new bot waves before they significantly affect your metrics.

How is this different from finding ghost followers?

Ghost followers are real accounts that are inactive — they followed you at some point but no longer use Instagram or engage with content. Fake followers are bot or spam accounts that were never real users. The detection methods overlap (both have low post counts), but ghost followers typically have normal-looking profiles while bots show multiple red flags simultaneously.

Updated Feb 2026

How to Detect and Remove Fake Followers on Instagram

Export your follower list, use data patterns to identify bot accounts and fake followers, and clean up your audience for better engagement rates and authentic growth.

Intermediate

20 minutes

7 steps

Before You Start

Google Chrome browser (desktop)
An Instagram account (logged in via web browser)
Instagram Followers Exporter Pro installed from the Chrome Web Store
A spreadsheet application (Excel, Google Sheets, or similar)

Export your followers to CSV

Install Instagram Followers Exporter Pro and navigate to your Instagram profile. Click the floating PlugMonkey button, select "Followers," and click "Start." Wait for the export to complete — the extension captures Username, Display Name, Bio, Follower Count, Following Count, Post Count, Verified Status, and Profile URL for every follower. Click "Download CSV" when finished.

Instagram Followers Exporter Pro exporting follower data

Screenshot the exporter panel with the Followers option selected, showing the progress bar during export.

Open the CSV and add analysis columns

Open the CSV in Google Sheets or Excel. Add three new columns to the right of the existing data: "Follower Ratio" (Follower Count / Following Count), "Posts Score" (a simple indicator based on post count), and "Fake Score" (a composite flag we will build in the next steps). These calculated columns will help you systematically identify suspicious accounts.

Spreadsheet with exported Instagram data and new analysis columns

Screenshot the spreadsheet with the original data columns plus three new empty columns labeled Follower Ratio, Posts Score, and Fake Score.

Flag accounts with zero posts

Accounts with 0 posts are one of the strongest bot indicators. In the Posts Score column, use a formula like: =IF(PostCount=0, "RED", IF(PostCount<3, "YELLOW", "GREEN")). Zero-post accounts are almost never real engaged followers — legitimate users who have never posted anything are unlikely to be discovering and following your content. Flag these as high-priority suspicious accounts.

Important

Not every zero-post account is a bot — some are lurkers or new accounts. Use this as one signal among several, not as a sole disqualifier.

Spreadsheet showing post count analysis with color-coded flags

Screenshot the spreadsheet with the Posts Score column populated, showing RED flags for 0-post accounts highlighted with conditional formatting.

Analyze follower-to-following ratios for bot patterns

Calculate the Follower Ratio column (Follower Count / Following Count). Legitimate accounts typically have ratios between 0.2 and 10. Bot patterns to flag: (1) Following 7,500 accounts (Instagram's limit) with very few followers — classic mass-follow bot. (2) Ratio below 0.05 — following thousands but almost nobody follows back. (3) Following 0 accounts but with followers — could be a scraper bot or inactive account. Use a formula like: =IF(OR(FollowingCount>7000, AND(Ratio<0.05, FollowingCount>500)), "SUSPICIOUS", "OK").

Spreadsheet showing follower-to-following ratio analysis

Screenshot the spreadsheet with the Follower Ratio column, sorted to show suspicious accounts with extreme ratios at the top.

Check for empty or generic bios and display names

In the Bio column, look for patterns common among fake accounts: completely empty bios, bios consisting of only emojis, or generic spam text (e.g., "DM for promo," "Follow for follow," "Check my link"). Use SEARCH or FIND functions to count bio length: =LEN(BioCell). Accounts with empty bios AND zero posts AND extreme following ratios are very likely bots. Also check display names for random character strings — names like "asjkd2847" or "user38291847" are common bot naming patterns.

Pro Tip

Create a combined Fake Score by adding up the individual flags: 1 point for zero posts, 1 point for suspicious ratio, 1 point for empty bio. Accounts scoring 3/3 are almost certainly fake. Accounts scoring 2/3 are likely fake. Accounts scoring 1/3 warrant manual review.

Bio analysis showing empty and generic bios flagged as suspicious

Screenshot the spreadsheet filtered to show accounts with empty bios, highlighting the correlation with zero posts and suspicious ratios.

Calculate your fake follower percentage

Count the accounts flagged as suspicious (Fake Score of 2 or 3) and divide by your total follower count to get your fake follower percentage. Industry averages suggest 10-25% of Instagram followers are fake or inactive across most accounts. If your percentage is significantly higher, your account may have been targeted by bot follow campaigns or you may have engaged with follow-for-follow groups in the past. Use COUNTIF to tally: =COUNTIF(FakeScoreColumn, ">=2") / COUNTA(UsernameColumn).

Summary showing fake follower percentage calculation

Screenshot showing a summary section with total followers, flagged accounts, and the calculated fake follower percentage displayed prominently.

Remove fake followers from your account

Instagram allows you to remove followers individually: go to a follower's profile, tap the three dots, and select "Remove follower." For bulk removal, sort your spreadsheet by Fake Score (descending) and work through the highest-scoring accounts first. Instagram does not currently offer a bulk remove feature, so this must be done one account at a time. Focus on the accounts that scored 3/3 — these are the most confident detections and will have the biggest impact on your engagement rate.

Important

Remove followers at a moderate pace — removing hundreds in a single session could trigger Instagram's automated systems. Aim for 50-100 removals per day spread across multiple sessions.

Instagram interface showing the Remove Follower option on a profile

Screenshot the Instagram profile view with the three-dot menu open and the Remove Follower option highlighted.

Summary

You have completed a data-driven audit of your Instagram followers. By exporting your follower list and analyzing key signals — zero posts, extreme follower-to-following ratios, empty bios, and generic display names — you can identify fake and bot accounts with high confidence. Removing these accounts improves your engagement rate (since bots never engage with your content), gives you a more accurate picture of your real audience size, and improves your account's appeal to brands and partners who evaluate follower quality. Run this audit quarterly to catch new bot waves early. Instagram Followers Exporter Pro makes the data extraction effortless — the spreadsheet analysis takes just 15-20 minutes and can be templated for future reuse.

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