The Scenario
You are a customer success analyst. Churn is up 8% this quarter. Your VP asked for an event-level view of what your top 50 high-value customers were doing in Klaviyo over the last 6 months — specifically "Placed Order" and "Viewed Product" events — to look for behavioral signals before they churned. The customer emails are in a Google Sheet in column A. The event history is in Klaviyo. Getting those two things into the same spreadsheet is the problem.
The bad version:
- Log into Klaviyo, search for the first customer email, navigate to their profile, scroll to the activity log, and manually note the events you care about. Repeat for 49 more profiles.
- After two hours, you have a hand-entered table in a spreadsheet with enough transcription errors that you do not fully trust it.
- The VP asks for the full event log, not just a count — you have to go back into Klaviyo and start over.
You are supposed to be analyzing churn, not transcribing activity logs. The signal you are looking for might be right there in the data. But the data is two hours of manual work away.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the customer email list and pulls event history from Klaviyo for each profile — writing every event as its own row in the sheet.
Pull all Klaviyo events for profiles listed in column A of this sheet and write each event's metric name, timestamp, and value into a new row in the "Events" sheet
What You Get
- For each of the 50 emails in column A, Klaviyo's event history is queried and each event becomes a separate row in the "Events" sheet.
- Each row contains the profile email, metric name (e.g., "Placed Order"), event timestamp, and any associated value (e.g., order revenue).
- The full event log — not just counts — is ready for analysis without a single manual lookup.
What If the Data Is Not Quite Ready
You only want the two specific event types, not the full activity log
For each email in column A, pull only "Placed Order" and "Viewed Product" events from Klaviyo for the last 6 months, and write profile email, event name, timestamp, and revenue value into a new row in the "Events" sheet
You need aggregated event counts per customer, not individual events
For each email in column A, count how many "Placed Order" events occurred in Klaviyo over the last 6 months and write the email and order count into columns A and B of the "Summary" sheet
You need the most recent event timestamp per customer to identify recency
For each email in column A, find the timestamp of the most recent "Placed Order" event in Klaviyo and write the email and last order date into columns A and B
Full churn signal analysis in one pass
For each email in column A, pull "Placed Order" and "Viewed Product" events from Klaviyo for the last 6 months; write all individual events to the "Events" sheet with email, event name, and timestamp; then write a summary to the "Churn Analysis" sheet showing email, total orders, total product views, days since last order, and days since last product view — sorted by days since last order descending
The churn analysis gets behavioral data from Klaviyo without a single manual profile lookup.
Try It
Get the 7-day free trial of SheetXAI and open the customer email list your CS team is tracking, then ask it to pull the full Klaviyo event history for all 50 profiles in one pass. Also check out how to pull metric aggregates if you need aggregate event trends rather than individual event records.