How to Connect Microsoft Clarity to Google Sheets (4 Methods Compared)

The Problem With Getting Sheet Data In and Out of Microsoft Clarity

You have a Google Sheet full of data — page URLs, session benchmarks, click counts from a previous audit, UX fix priorities. You need Clarity's behavioral data pushed into it, or your existing sheet data used to cross-reference what Clarity is flagging, in a way that doesn't eat your afternoon every time.

Clarity is good at showing you where users rage click, where they stop scrolling, and which pages are quietly bleeding engagement. But the gap between "I can see it in the Clarity dashboard" and "I have it in a spreadsheet my team can act on" is wider than it looks. The usual flow is: export what you can from the Clarity UI, copy the numbers by hand, reformat the columns, and paste them somewhere that approximates what you actually needed.

Below are the four common ways teams close that gap. Only the last one scales.

Method 1: Manual Copy-Paste

The default. Open Clarity, filter to the date range you care about, read off the numbers for each page — rage clicks, dead clicks, scroll depth — and type them into your sheet by hand.

For a site with five pages, that's manageable. For forty pages, it means forty trips between tabs, forty chances to transpose a number, and a formatting job at the end when you realize Clarity showed percentages and your sheet wants decimals.

The specific grind with Clarity data is that the numbers change every time you look. A weekly behavioral report means doing this whole dance every Monday, for the same pages, with slightly different numbers. By the third week you start wondering why you work in a field that requires this.

Method 2: Zapier or Make

Both platforms have Microsoft Clarity connector options. You can set up a trigger on a schedule, call the Clarity API, and write the response back into your sheet row by row.

Before you read further — do you know what a webhook trigger is? A field mapping schema? An API authentication token? If those aren't second nature, this path is going to put you in front of documentation you weren't planning to read today. Skip to Method 3 or 4 and save yourself an hour.

If you're still here: the setup is real work. You pick your trigger cadence, authenticate the Clarity API connection, map each response field to a column in your sheet, and test until the data lands in the right shape. When it works, it works.

But a schedule-triggered automation pulls one result set at a time — it doesn't aggregate, rank, or filter across pages the way your actual report needs. You're getting the raw data, and the thinking about which pages matter most is still your job.

You probably just need the rage click counts sorted by page, and you have no idea why building that requires a trigger, a data mapping step, and a Zap history full of partial runs. So you hand it to the person on your team who understands automations. Now you're waiting for them to have a free hour, and your UX backlog meeting is Thursday.

Method 3: The Previous Generation — Connector Add-Ons

Until recently, the best repeatable option for pulling Clarity data into a spreadsheet was a category of add-ons that let you configure column mappings and run them on demand. You picked your date range, tagged your fields, saved a config, and ran it.

That was a genuine improvement. You didn't have to export and reformat by hand. The column structure stayed consistent. Your team could reuse the same template week over week.

But you still had to define every field mapping yourself. You still had to decide which columns to pull, what the sort order should be, and how to flag the pages that needed attention. The data got through, but every decision about what to do with it was still on you. And if Clarity changed a field name or you added new pages to track, your config broke until someone went back in and rebuilt it.

This is the previous generation. Functional, but it asked a lot of the person running it.

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 are looking at, and through its built-in Microsoft Clarity integration it can pull behavioral data from Clarity for you. No field mapping, no automation plumbing, no re-exporting the same numbers each week. You just ask.

Example 1: Build a rage click priority list for the dev team

Export Microsoft Clarity data for the past 30 days and write each page URL, session count, rage click count, dead click count, and average scroll depth into columns A–E of this sheet — sort by rage click count descending

The result lands in the sheet in one pass: URLs down column A, all five metrics in order, sorted so your highest-friction pages are already at the top. Your dev team has a backlog they can act on without asking you what it means.

Example 2: Classify engagement health across all pages

Fetch Clarity data for the last 60 days and write page URL, sessions, average scroll depth, and click count into this sheet — add a column F that classifies each page as 'high engagement', 'medium engagement', or 'low engagement' based on scroll depth thresholds of 60% and 30%

The classification logic runs inline. Instead of pulling raw numbers and then writing a formula to bucket them, you get the bucket and the number together, in one operation.

Try It

Get the 7-day free trial of SheetXAI and open any Google Sheet you use for UX tracking or site audits, then ask it to pull this week's Clarity data and rank your pages by friction. The Microsoft Clarity integration is included in every SheetXAI plan.