The Scenario
You are an account executive three days out from a territory planning session. Your manager asked you to bring an enriched version of the target account list — 80 company names, currently just names and nothing else. You need employee count, industry, LinkedIn company URL, and HQ city before you can segment the list into tiers. You've been putting this off because you knew it would mean manual API work.
The bad version:
- Look up each company name in the PDL UI one at a time, copy the firmographic fields you need into the sheet by hand
- Find that 15 of the 80 names are ambiguous — "Acme Corp" matches 6 different companies in PDL — and spend 20 minutes per entry trying to figure out which is the right one
- Get through 40 rows before the meeting prep overhead eats the rest of your afternoon, leaving the list half-enriched and the tier plan unfinished
You're supposed to be building the territory strategy. The data prep is supposed to be done before you start, not instead of starting.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the company names already in the sheet and uses its built-in People Data Labs integration to enrich each row with firmographic data and write it back.
Enrich each company in this sheet using PDL: match by the name in column A and write employee count, industry, LinkedIn URL, and HQ location into columns B through E.
What You Get
- Column B filled with PDL's employee count for each matched company
- Column C filled with the industry classification from PDL's taxonomy
- Column D filled with the company's LinkedIn URL
- Column E filled with HQ city or location
- Ambiguous or unmatched company names flagged in column F so you can resolve them manually if needed
What If the Data Is Not Quite Ready
The list has both company names and website domains — use both as signals
Enrich each company using PDL: use the name in column A as the primary match signal and the website in column B as a secondary signal. Write employee count, industry, LinkedIn URL, and HQ city into columns C through F.
Some names are holding companies with multiple subsidiaries in PDL
For each company in column A, enrich via PDL and write the primary company match. If PDL returns multiple matches, pick the one with the largest employee count and note the match count in column G.
The list needs a revenue band instead of raw employee count
Enrich each company in column A via PDL and write employee count to column B. Then add a tier label in column C: "Enterprise" for over 500 employees, "Mid-Market" for 50 to 500, "SMB" for under 50.
Enrich, tier, and flag healthcare companies for a specific sequence in one prompt
Enrich each company in column A via PDL: write employee count, industry, and HQ city to columns B through D. Flag any company where PDL's industry is health or healthcare in column E as "Healthcare sequence" for routing.
The pattern is to ask for enrichment and classification at once — you walk away with a tiered, routed account list, not just a sheet with raw fields.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet with a column of target company names. Ask it to pull employee count, industry, and HQ city from People Data Labs and write it back. Then see how to run a company search and import results directly or go back to the People Data Labs overview.