The Scenario
It's mid-quarter and you're staring at a product roadmap meeting scheduled for next week. Your job is to walk the team through which pages are working and which ones users are bouncing off before they hit the CTA. You have a list of forty product pages in a Google Sheet — URLs in column A, nothing else filled in yet. You know Clarity has scroll depth and session data for all of them. You've been meaning to pull it for two weeks, and now you have four days.
The bad version:
- Open Clarity, switch to the Pages view, manually read off the average scroll depth for each of your forty URLs, and type the numbers into column B — then realize you also need session counts and repeat the entire process for column C.
- Decide to export instead, download the CSV, open it, discover it has thirty-two columns you don't need and that your forty pages are spread across four separate date range exports because Clarity caps the export size.
- Spend an hour stitching the exports together, then manually classify each page as high/medium/low engagement because there's no conditional column in the raw export.
You're supposed to be drawing conclusions from this data, not wrangling it into shape. The meeting is Thursday and the stakeholders want the chart, not the story of how you built it.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads your existing data — the URLs already in column A — connects to Microsoft Clarity, and writes back the behavioral metrics you ask for. You describe what you need and it handles the retrieval and the classification logic in a single pass.
With your product page URLs already in column A, open the SheetXAI sidebar and paste:
Fetch Microsoft Clarity export data for the last 7 days and write page URL, sessions, engagement score, and scroll depth into this Google Sheet — add a column that classifies each page as 'high engagement', 'medium engagement', or 'low engagement' based on scroll depth thresholds of 60% and 30%
What You Get
- Column B fills with session counts for each URL
- Column C receives the Clarity engagement score
- Column D receives average scroll depth as a percentage
- Column E gets the classification — 'high engagement', 'medium engagement', or 'low engagement' — based on the 60%/30% thresholds you specified
- The classification runs on the data as it arrives, not as a second formula step you add afterward
What If the Data Is Not Quite Ready
Some pages have almost no traffic and are skewing the benchmark
When you're setting engagement benchmarks, a page with twelve sessions shouldn't pull the average down. Filter it out:
Export Clarity session and scroll depth data for the past 60 days for all pages with more than 100 sessions, write URL, sessions, scroll depth, and average time on page into columns B–E, and classify each page as 'high', 'medium', or 'low' engagement using scroll depth thresholds of 60% and 30% — skip pages below the session threshold entirely
I need to compare this week against last week
Two-period comparisons are where the manual approach collapses — double the exports, double the reformatting. One prompt handles it:
Pull Clarity scroll depth and session data for the past 7 days and for the 7 days before that, write both periods' scroll depth into columns C and D with headers 'Scroll Depth (This Week)' and 'Scroll Depth (Last Week)', and in column E write 'improving', 'declining', or 'stable' based on the difference
My sheet only has some of the URLs and I want Clarity to fill in the rest
Export all pages from Clarity for the past 60 days that had more than 50 sessions, write page URL, session count, scroll depth, click count, and engagement classification into columns A–E starting at row 2 — use scroll depth thresholds of 60% and 30% for the classification column
Build the full benchmark and flag CTA drop-off pages in one shot
Export Clarity data for all pages over the past 60 days, write URL, session count, average scroll depth, average time on page, and click count into columns A–E, classify each page as 'high engagement', 'medium engagement', or 'low engagement' in column F using scroll depth thresholds of 60% and 30%, and in column G write 'CTA risk' for any page where average scroll depth is below 40% and session count is above 200
The approach: ask for the data, the classification, and the CTA risk flag in one instruction so the analysis is done when the data arrives.
Try It
Get the 7-day free trial of SheetXAI and open the Google Sheet you use for product page performance — then ask it to pull Clarity's scroll depth data for all your pages and classify them before Thursday's roadmap meeting. For related tasks, see Export Microsoft Clarity Rage Click Data Into a Google Sheet or the Microsoft Clarity integration overview.