Instagram comments are one of the few honest signals left on the platform: real people, telling you in their own words what they think of a post, a product, or a giveaway. The problem is that Instagram gives you no way to get them out — no export button, no download option, nothing but endless thumb-scrolling. This guide shows the complete workflow for getting every comment from any public Instagram post or Reel into Google Sheets, where you can actually sort, filter, count, and analyze them. It takes about two minutes, works on posts you don't own, and needs no Instagram password.
Why Google Sheets is the right destination for comment data
You could read comments in the app forever, but the moment you need to answer a real question — Which commenter mentioned sizing issues? How many people asked about shipping? Who commented on all three of our launch posts? — you need the data in a table. Google Sheets is the natural home for it because it is free, shareable by link, and already where most marketing teams keep campaign trackers and content calendars. A comment export drops into that ecosystem instantly: share the sheet with a client, connect it to Looker Studio for a live dashboard, or feed it into an Apps Script automation. Unlike a CSV sitting in your downloads folder, a sheet is a living document your whole team can work in at once.
The catch: Google Sheets cannot pull Instagram comments by itself. The scraping formulas people try first — IMPORTXML, IMPORTHTML, IMPORTDATA — fetch pages as anonymous requests without running JavaScript. Instagram renders its comments client-side and aggressively blocks anonymous scraping, so those formulas come back empty. The workflow that actually works is two steps: export to CSV first, import to Sheets second.
Step 1: Export the Instagram comments to CSV
Copy the URL of the post or Reel you want — from the browser address bar, or via the share icon → Copy Link in the app. Any public post works: your own, a competitor's, an influencer you're vetting, a viral post in your niche. Then paste the link into the Instagram comment exporter. The tool counts the comments first and shows you the total, so you know exactly what you're getting before you download anything. The first exports are free and need no signup or Instagram login — the exporter reads the same public comments anyone can see, so your account is never involved and never at risk.
Download the result as CSV (Sheets' native import format). Each row is one comment with columns for the text, username, display name, like count, reply count, timestamp, and detected language. If you prefer, you can also grab Excel or JSON — but for the Google Sheets workflow, CSV is the frictionless choice. For a deeper look at the export side, including replies and bulk export across up to 50 posts, see our guide to exporting Instagram comments to Excel — the download step is identical.
Step 2: Import the CSV into Google Sheets
In a new or existing spreadsheet, go to File → Import → Upload and drop in your CSV. Google's import documentation covers the options, but the defaults are right for comment data: import location "Insert new sheet(s)", separator "Detect automatically", and — one setting worth checking — "Convert text to numbers, dates, and formulas" left ON so like counts arrive as numbers and timestamps as dates you can sort.
Two small clean-ups make the sheet pleasant to work in:
- Freeze the header row (View → Freeze → 1 row) so column names stay visible while you scroll ten thousand comments.
- Add a filter (Data → Create a filter) to get sortable, filterable dropdowns on every column instantly.
That's the whole pipeline. From Instagram post to working spreadsheet in two steps. Everything below is what you can do once the data is there — which is where it gets interesting.
Seven things to do with Instagram comments in Google Sheets
1. Surface the top comments by likes
Sort the like-count column descending. The top 20 rows are your post's greatest hits — the jokes, questions, and objections that resonated hardest. These are ready-made material: pin the best ones, reply to the top questions, and screenshot standouts for stories.
2. Count keyword mentions
A single formula answers "how many people mentioned X": =COUNTIF(C:C, "*shipping*") counts every comment containing "shipping" (assuming comment text in column C). Build a small block of these for your recurring themes — price, sizing, availability, a competitor's name — and you have a poor-man's topic tracker that updates the moment you paste in a new export.
3. Find your repeat commenters
Insert a pivot table (Insert → Pivot table) with the username as rows and a count of comments as values, sorted descending. The people at the top are your true fans — they show up on post after post. These are exactly the accounts to reply to, feature, and recruit for UGC. If audience identity matters more than volume, our guide on analyzing Instagram comments goes further into commenter-level analysis.
4. Extract every @mention
Giveaways that ask entrants to "tag a friend" produce comments full of @mentions. A formula like =REGEXEXTRACT(C2, "@[A-Za-z0-9._]+") pulls the first mention out of each comment into its own column — a growing list of warm, referred accounts.
5. Build an hourly engagement histogram
Add a column with =HOUR(F2) on the timestamp, then pivot by hour. The histogram shows exactly when your audience is active — which is the honest, data-driven answer to "when should I post?" for your specific followers rather than a global average.
6. Chart comment velocity
Pivot by date and chart the counts. Comment velocity — how fast engagement decays after posting — tells you whether a post had a long tail (saves, shares, recommendation traffic) or died in a day. Comparing velocity curves across posts reveals which content formats keep working after the initial push.
7. Share it as a live report
Because it's Sheets, the analysis is the report. Share the link with view access, or connect the sheet to Looker Studio for a dashboard the client can check anytime. No more screenshots of the Instagram app pasted into slide decks.
Keeping a sheet updated over time
Comments keep arriving after your first export, especially on Reels that the algorithm resurfaces for weeks. The pragmatic update loop:
- Re-export the same post URL (a fresh export always contains all comments to date).
- Import into a new tab of the same spreadsheet.
- Use the timestamp column to filter for rows newer than your previous import's latest comment, and append them to the master tab.
For most campaigns a weekly re-export is plenty — comment velocity on a normal post collapses within days. For an always-on tracker across many posts, the same CSV-to-Sheets flow can be automated: a scheduled Apps Script can fetch a CSV from a URL with UrlFetchApp and paste it into a tab on a timer, turning the manual import into a hands-off refresh.
Why not the Instagram API?
Developers sometimes ask why not pull comments straight from Meta's official Instagram Platform API. You can — if you have a Business or Creator account, a registered Meta app, an access token, and you only need comments on your own media. The API does not serve comments from arbitrary public posts you don't own, which rules out competitor research, influencer vetting, and giveaway monitoring on partner accounts. For the spreadsheet workflows this guide covers, an exporter that works on any public URL — with no app registration and no tokens — gets you to the same CSV in a fraction of the effort.
Common problems and fixes
- Emoji look broken after import. This is an encoding issue that hits Excel more than Sheets — Google Sheets reads UTF-8 CSVs correctly by default. If you see mangled characters, re-import the original CSV rather than a copy that Excel has re-saved.
- Timestamps imported as text. Check that "Convert text to numbers, dates, and formulas" was on during import. If not, re-import — it is faster than converting a text column by hand.
- The post has zero comments in the count. Verify the account is public and the URL is a post, Reel, or IGTV link. Instagram Stories don't have public comments — story replies go to DMs — so they can't be exported.
- Very large exports feel slow in the browser. Sheets handles hundreds of thousands of rows, but filters get snappier if you split mega-exports into one tab per post and keep a summary tab of pivot results.
Google Sheets vs Excel for comment data
Both open the same CSV, so the choice is about what happens after the import. Sheets wins on collaboration and distribution: simultaneous editing, view-only share links for clients, version history without file copies, and free access for everyone on the team. It also wins on automation for this workflow — Apps Script and time-driven triggers are built in, no add-ins required. Excel wins on heavy lifting: hundreds of thousands of rows stay snappy, Power Query handles repeated multi-file merges elegantly, and its pivot engine is faster on very large tables. A practical split that many teams land on: Excel for the one-off deep dive on a monster export, Sheets for anything a client or teammate will ever need to open. If you're on the Excel side of that split, the Excel version of this workflow covers its import quirks — encoding, emoji, and leading-zero usernames.
Building a competitor benchmark sheet
The workflow gets disproportionately more valuable the moment you add a second account's posts, because now the sheet answers comparative questions. A simple benchmark structure:
- One tab per account — yours plus two or three competitors. Export each account's five most recent posts (bulk export takes all five URLs in one job) and import each account's CSV into its tab.
- A summary tab with one row per account: total comments, average comments per post, percentage of comments that are questions (count of "?" divided by total), and top three keywords by COUNTIF.
- A monthly re-run. Same URLs plus the new posts; the summary tab becomes a trendline of share-of-conversation in your niche.
This is the poor-man's social listening dashboard — and for a single niche it is often better than the enterprise tools, because you chose exactly which posts define the comparison instead of relying on keyword sampling. When a competitor's post suddenly triples its usual comment count, the comments themselves — already sitting in your sheet — tell you why: a giveaway, a controversy, a product drop, or a format worth copying. Our guide on building a social listening report from real comments turns this structure into a client-ready deliverable.
From spreadsheet to AI analysis
Formulas count words; they don't read meaning. Once your comments are in a sheet you can go one step further and classify them — sentiment, purchase intent, questions vs praise vs complaints — either by feeding the CSV to an AI comment analysis tool or by running the exported file through the built-in AI comment analysis at export time and importing the scored file instead. The scored version adds columns like sentiment and topic to every row, which turns your pivot tables from "how many comments" into "how many negative comments about shipping, this month vs last". For teams reporting to clients, that one extra column set is usually the difference between a data dump and an insight.
The takeaway
Instagram will not give you your comment data, but that doesn't mean you can't have it. Export the post to CSV with the Instagram comment exporter, import it into Google Sheets, and two minutes after copying a URL you have a sortable, filterable, shareable dataset of everything your audience said. The same workflow powers competitor research, giveaway winner picking, influencer vetting, and monthly reporting — and if you also work on TikTok, the identical flow is covered in our TikTok comments to Google Sheets guide.