The Scenario
You set up a Zapier trigger six months ago that pipes Payhip paid event webhooks into a Google Sheet. It did exactly what it was supposed to — column B of the "Raw Events" tab now has hundreds of rows of JSON payloads, each one a raw Payhip paid event object. You have the data. What you don't have is anything you can show anyone.
Someone from the finance team asked for a revenue breakdown last Tuesday. You told them it was in progress. It's Thursday.
The bad version:
- Open a row in column B, read the JSON, figure out which fields map to date, product name, buyer email, and gross amount.
- Manually extract those four values and type them into the next empty row of the "Revenue Log" sheet.
- Repeat for every row in "Raw Events" — all 340 of them — pausing whenever the JSON structure looks slightly different from the previous row.
The data exists. The structure to hold it exists. The bridge between them is 340 rows of manual parsing, which is several hours of work you were not budgeting for when you built the Zapier flow.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the raw payload data in one tab, extracts the fields you specify, and writes clean records into another tab — without you opening a single row by hand.
Parse the raw Payhip paid webhook JSON in column B of the "Raw Events" sheet and write cleaned rows — date, product name, buyer email, gross amount — into the "Revenue Log" sheet.
What You Get
- Each row in "Raw Events" column B is parsed for the four key fields.
- Clean records land in "Revenue Log" with one row per event: date in column A, product name in column B, buyer email in column C, gross amount in column D.
- Rows where the JSON is malformed or missing a field get flagged in a "Parse Error" column rather than silently dropped.
What If the Data Is Not Quite Ready
Some payloads include discount codes applied — you want those captured too
Parse the Payhip paid webhook JSON in column B of "Raw Events" and write date, product name, buyer email, gross amount, and coupon code applied (if any, otherwise blank) into the "Revenue Log" sheet, one row per event.
The "Raw Events" tab has non-JSON rows from a different trigger mixed in
For each row in column B of "Raw Events", check whether the value is a valid Payhip paid event JSON object. If it is, extract date, product name, buyer email, and gross amount and write a clean row to "Revenue Log". If it's not a Payhip paid event, write the row number and a note into an "Errors" tab.
The revenue log already has some rows — you only want to append new events
Find the most recent date already in the "Revenue Log" sheet's column A. Then parse only the rows in "Raw Events" column B whose event date is later than that date, and append clean rows — date, product name, buyer email, gross amount — to the bottom of "Revenue Log".
Full pipeline in one prompt — parse, clean amounts, deduplicate, and write a summary
Parse the Payhip paid webhook JSON in column B of "Raw Events". Convert gross amounts from cents to dollars. Deduplicate by transaction ID if column C of "Raw Events" holds an ID field. Write clean rows to "Revenue Log" and a pivot summary of gross revenue by product name to a "Product Summary" tab.
The whole transformation from raw webhook dump to reportable revenue data runs in a single ask.
Try It
Get the 7-day free trial of SheetXAI and open the sheet where your Payhip webhook payloads are landing, then ask it to parse and clean the full log into a revenue tracker. For the next analysis step, see Reconcile Payhip Refund Events Against a Sales Log in Google Sheets or return to the Payhip integration overview.