The Scenario
It is a Tuesday morning and you are staring at a Salesforce export with 500 companies. Someone in RevOps set this up for a firmographic enrichment run — employee count, industry, LinkedIn URL — before the account scoring model gets updated next week. You know PDL has bulk enrichment endpoints that batch 100 records per call. You also know that using the individual enrichment endpoint on 500 rows will cost roughly 5x the API credits. Nobody told you how to run the batch endpoint from a sheet.
The bad version:
- Try to write a script that reads from the sheet, batches the rows, calls the PDL bulk endpoint, and writes results back — three hours in and you're still debugging the authentication header
- Fall back to the individual endpoint to unblock yourself, burning 500 API calls instead of 5
- Deliver the enriched sheet on Thursday, over budget on credits, with 14 rows that silently failed because the script didn't handle the no-match case
This is the kind of task where the right solution exists, but getting to it from a blank script file is a full-day project.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the sheet and uses its built-in People Data Labs integration — including the bulk endpoint — to enrich your records in batches and write results back.
Enrich all 500 companies in this sheet using PDL bulk enrichment in batches of 100, matching by the website in column B, and write employee count, industry, and LinkedIn URL back into columns C through E.
What You Get
- Five bulk API calls instead of 500 individual ones — credits preserved
- Columns C, D, and E populated with employee count, industry, and LinkedIn URL for each matched company
- Rows where PDL finds no match flagged in column F with a "No match" note so nothing fails silently
- A processing note in the sheet header showing how many records matched and how many were skipped
What If the Data Is Not Quite Ready
The website column has inconsistent formatting — some rows have https://, some don't
Before enriching, normalize the website URLs in column B: strip any trailing slashes and ensure they have no protocol prefix. Then run PDL bulk company enrichment in batches of 100 and write employee count, industry, and LinkedIn URL to columns C through E.
Some rows have company name but no website — use name as fallback
For rows where column B is empty, enrich by company name in column A instead. For rows where column B has a website, use the website. Run all rows through PDL bulk enrichment in batches of 100 and write employee count, industry, HQ city, and LinkedIn URL to columns C through F.
The sheet has duplicate websites — deduplicate before enriching to save credits
Deduplicate the website column B first. Then run PDL bulk company enrichment on unique websites only, write the results back to all matching rows, and note which rows were enriched from a shared match in column G.
Enrich, score, and route accounts in one pass
Enrich all companies using PDL bulk enrichment in batches of 100, matching by website in column B. Write employee count, industry, and LinkedIn URL to columns C through E. Then add a column F score: 3 for companies over 200 employees in fintech or SaaS, 2 for 50 to 200 employees, 1 for everything else.
The pattern is to run the enrichment and the scoring logic in a single prompt so you get a decision-ready sheet, not just a data-filled one.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet with a list of company websites or names. Ask it to enrich using PDL bulk batching and write firmographics back. Then see how to enrich individual contacts with PDL person enrichment or go back to the People Data Labs overview.