The Scenario
You are the business development manager, and the team review meeting is in 90 minutes. You have an Excel workbook with 80 qualified prospects — Company in column A, Deal Value in column B, Stage in column C, Expected Close Date in column D. None of them are in Bigin yet. The sales director is going to pull up the Bigin pipeline board during the meeting and expect to see everything there.
You have been in back-to-back calls since 8 AM and this is the first moment you have had to deal with it.
The bad version:
- Open Bigin's pipeline view and click "New Record" 80 times, pasting in each row individually.
- Realize halfway through that the Stage values in your workbook do not match the picklist options in Bigin exactly — "Discovery" in your table is "Qualification" in Bigin — and stop to figure out which mapping is correct.
- Run out of time, get to the meeting with 40 of 80 deals in Bigin, and explain to the director why the pipeline looks half-empty.
Manual entry at this scale, under time pressure, is how deals get entered with the wrong stage and nobody notices until the forecast is off.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Excel workbook. It reads your deal data and calls the Bigin Pipelines API to create records in bulk. No clicking through individual forms, no stage-picklist guessing.
Add all 80 rows from my Excel deals table into the Bigin Pipelines module using the column headers as field names
What You Get
- 80 new pipeline records created in the Bigin Pipelines module, each with the correct deal name, amount, stage, and close date.
- The returned Bigin deal ID written into column E for every row.
- Rows that fail (stage value not recognized, date format wrong) surface an error in column E rather than creating a malformed record.
What If the Data Is Not Quite Ready
Stage names in the workbook do not match Bigin picklist values exactly
Create Bigin pipeline records for all rows in this workbook. Before creating each record, map the Stage value in column C: if it says "Discovery" use "Qualification", if it says "Verbal Yes" use "Proposal Sent"; for any other value use it as-is. Write deal IDs into column E.
Close dates are in mixed formats
Create Bigin pipeline records for all rows. Normalize the Expected Close Date in column D — convert MM/DD/YYYY to ISO format (YYYY-MM-DD); for rows where the date is text like "Q3 2026" set the close date to the last day of that quarter. Write deal IDs or errors into column E.
Some rows need the deal linked to an existing contact by company name
For each row, look up the company name (column A) in Bigin Contacts and find the matching contact ID. Then create a pipeline record with the deal name, amount, stage, close date, and the contact association. Write the deal ID and matched contact ID into columns E and F.
Full normalization and bulk create in one shot
Trim all cells in columns A through D. Map stage values: "Discovery" to "Qualification", "Verbal Yes" to "Proposal Sent". Convert dates in column D to YYYY-MM-DD format. Create a Bigin pipeline record for each row using columns A through D. Write the returned deal ID or error into column E.
One pass handles the cleanup and the record creation — the pipeline board is ready before the meeting.
Try It
Get the 7-day free trial of SheetXAI and open your qualified-prospect workbook, then ask SheetXAI to create Bigin pipeline records for all 80 rows. If you need to push stage and amount updates back after a review, see the spoke on bulk-updating deal records.