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Export Instagram Followers to Google Sheets (and Actually Use the List)

3 min read

Key takeaways

  • Import is the easy part. File → Import → Upload, comma separator, done. The work is the analysis layer you build on top.
  • Filter bios for intent. A column filter on the bio text surfaces the followers who match your niche — the ones worth engaging or pitching.
  • Flag likely bots. No profile picture, no full name, and a generic username together are a strong bot signal you can filter out in one pass.
  • Segment by account type. The private and verified flags, plus whether a bio has a link, let you split personal accounts from business/creator accounts cleanly.
  • Get it out of Sheets when you're done. The point of a clean list is to act on it — re-follow, DM a shortlist, or push to a CRM. Sheets is the workbench, not the destination.

Importing a follower list into Google Sheets takes two minutes. The reason to do it is everything that happens after — turning a raw list of usernames into something you can act on.

Get the CSV in

Export your followers to CSV first (the four ways to do that). Then:

  1. In Google Sheets: File → Import → Upload, and drop the CSV.
  2. Separator type: Comma. Import location: Replace current sheet.
  3. Import data.

You now have one row per follower and columns for username, full name, user ID, and — depending on the tool — profile URL and the private/verified flags. What each column means.

Build the analysis layer

This is where the list earns its keep. A few passes that take minutes each:

Filter bios for intent. If your export includes bio text (a per-profile lookup, not the basic list), add a filter on that column for the words your niche uses — "founder", "coach", "UGC", "dropship", whatever fits. What's left is the subset of your audience actually in your market.

Flag likely bots. Create a helper column:

=IF(AND(D2="", C2=""), "check", "")

where C is full name and D is profile picture URL. Rows with neither, especially with a random-string username, are almost all fake. Filter them out before you count "real" reach or before any outreach.

Segment by account type. The verified and private flags split your audience immediately. A bio that contains a URL is a strong "business or creator" signal even without a full lookup. Sort by these and you can see, at a glance, how much of your following is personal accounts versus other businesses.

Dedupe and sort. Data → Data cleanup → Remove duplicates on the username column. Then sort by full name to skim for people you recognise, or by user ID (roughly chronological) to see your oldest followers first.

Then get it out of Sheets

A clean, filtered list is a workbench output, not an end state. Depending on the goal:

  • Re-follow or engage a shortlist — copy the top slice of usernames and work down it, at a human pace.
  • DM a targeted few — not the whole list. Bulk DMs to an exported list breach Instagram's terms and are the fastest way to a restriction.
  • Push to a CRM — HubSpot, Pipedrive, Apollo and the rest all take a CSV. Only do this with contact data people actually chose to make public or share with you.

A note on doing this at scale

Building this from your own followers is straightforward and low-risk. Running per-profile lookups across thousands of accounts to harvest emails for cold outreach is a different activity, with both Instagram's automated-collection terms and — if you then email people — data-protection law in play. ListLift's detailed lookup is paced and honest about yield (public email and website exist only on business/creator accounts that chose to publish them), but the responsibility for how the list gets used sits with you.

FAQ

Questions this comes up with

Skip the manual work — use ListLift

Follower & Following Exporter — see the real count before you export.