How to Connect Make to Google Sheets (4 Methods Compared)

The Problem With Getting Sheet Data In and Out of Make

You have a Google Sheet full of data — organization IDs, client accounts, user email lists — and you need it to talk to Make. Either you're pulling scenario metadata into the sheet for a report, or you're using the sheet as the source of truth for a bulk operation. Either way, the actual exchange of that data with Make's API is more friction than it looks.

Make is good at building visual automation workflows between apps. But Make itself is not easy to query from a spreadsheet. The default approach is to build a Make scenario that writes data somewhere you can then access — which is a bit like going around the barn to check the fence.

Below are the four common ways teams handle this. Only the last one scales.

Method 1: Manual Copy-Paste

The default. You log in to Make, navigate to the organization or team or scenario you need, and manually copy the values you're looking for — org IDs, team names, usage stats, pricing details — into your sheet by hand.

For a one-time lookup of three values, this is fine. But Make accounts at scale look different: a RevOps team managing 12 client organizations, a platform engineer keeping a provisioning checklist, a reseller tracking operations consumption across 15 clients. Every time the data changes — new org added, plan upgraded, team renamed — someone goes back to Make and does it again.

That's not a workflow. That's just administration that never ends.

Method 2: Make Scenarios

Make has its own API, and you can build a Make scenario to call it. Set up an HTTP module pointing at the Make API, map the response fields into a Google Sheets module, and you've got an automated pull.

Before you go further — do you know what a webhook trigger is? A JSON path expression? OAuth token management? If those feel like a foreign language, this path is probably not yours. Jump to Method 3 or 4 — the setup here assumes you're comfortable with Make's advanced modules, and if you're not, you'll hit a wall before you get the data.

For those still here: yes, this works. You authenticate the HTTP module with your Make API key, call the right endpoint, map each field to a column in the Sheets module. The flow runs on a schedule, and your sheet stays updated.

The structural ceiling is this: a trigger-per-run architecture isn't the same as a bulk query.

If you want operations data across 15 organizations, you're chaining 15 HTTP calls in an iterator, watching for rate limit errors, and debugging why org 8 returned a 422.

You probably just need the usage numbers for your client report. You probably have no idea why org 8's response is malformed, and you definitely don't have an afternoon to find out. So the scenario either goes to whoever on your team builds these things, or it sits unfinished in your Make account. If the builder's on a deadline of their own, you're waiting.

Once you need to filter, aggregate, or join data across multiple endpoints, you've also left the scenario's native capabilities behind. You'd need a data store, a custom function, or a second scenario feeding into the first.

Method 3: The Previous Generation — Connector Add-Ons

Until recently, the best option for repeatable spreadsheet ↔ API workflows was a category of add-ons that let you configure column mappings and saved query templates. You picked your endpoint, tagged your fields, saved a config, ran it.

That was genuinely better than doing it by hand. Outputs were consistent, configs were reusable, and the team didn't have to redo formatting every time.

But you were still responsible for everything: the endpoint selection, the field mapping, the schedule, the filter logic, the column naming. The tool moved the data, but every decision about which data to move was still on you. And the moment Make updated their API response shape, your saved config silently broke until someone noticed the columns were wrong.

That's the previous generation. It got data through. It didn't do the thinking.

The Easy Way: Using SheetXAI in Google Sheets

There is a different way entirely. SheetXAI is an AI agent that lives inside your Google Sheet. It reads the sheet, understands what you're looking at, and through its built-in Make integration it can push to or pull from Make for you. No scenario building, no field mapping, no debugging malformed responses. You just ask.

Example 1: Pull all Make organizations and teams into a structured inventory

List all Make organizations I have access to and write organization ID, name, and timezone into this sheet, then for each org list all teams and add them as rows below with org name, team ID, and team name

Every org and every team under it lands in the sheet. No iterator, no HTTP module, no chained calls.

Example 2: Fetch 30 days of usage data for every org ID in column A

For every organization ID in column A, fetch Make operations usage for the past 30 days and fill columns B through E with date, operations count, data bytes, and centicredits consumed

The pattern: instead of building a scenario to loop over the column and writing the results elsewhere, you ask for both the lookup and the fill in a single prompt. SheetXAI handles the per-row iteration inline.

Try It

Get the 7-day free trial of SheetXAI and open any Google Sheet with Make organization IDs or account data, then ask it to do one of the tasks above. The Make integration is included in every SheetXAI plan.