The Scenario
The ICP scoring model your RevOps team promised for Q3 has a prerequisite: every account in the CRM export needs employee count and industry attached to it. You have 200 rows in a Google Sheet — company names, nothing else. LeadIQ has the firmographic data. Getting it from there to here is the problem.
Someone exported this list six weeks ago and it's been sitting because "enrichment" didn't have a clear owner. Now it does, and it's you, and the RevOps lead wants the scored model by Thursday.
The bad version:
- Open LeadIQ's company search, type in the first company name, pull employee count and industry from the profile, switch back to the sheet, paste both values, go again.
- Hit a company name that returns three results with similar names and spend three minutes figuring out which one is correct based on the headquarters city you don't have.
- Get through fifty rows and realize you haven't been consistent about whether you're writing "Financial Services" or "Finance" in the industry column, which means the scoring model is going to bucket them differently.
200 companies at two minutes per lookup is nearly seven hours of work. The scoring model deadline isn't going to move.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent built into your Google Sheet. It reads the sheet, understands what you have, and through its LeadIQ integration it can run the company lookups and write back the firmographic fields in one pass.
For each company name in column A, search LeadIQ and fill in employee count, industry, headquarters city, and LinkedIn URL into columns B through E
What You Get
- Column B fills with employee counts as integers, matching the LeadIQ record for each company.
- Column C fills with the LeadIQ industry classification, consistent across all rows since it comes from the same source.
- Column D fills with headquarters city.
- Column E fills with the company's LinkedIn URL for cross-referencing.
- Rows where LeadIQ finds no match are flagged so you can follow up on them separately.
What If the Data Is Not Quite Ready
You want employee count bucketed into size bands rather than raw numbers
For each company name in column A, search LeadIQ and write the raw employee count into column B. Then based on that count, write the size band into column C: "1–50", "51–200", "201–1000", or "1000+" — use those exact labels
Some company names are ambiguous and might match the wrong company
For each company in column A, search LeadIQ and fill in employee count and industry in columns B and C. Also write the headquarters city into column D so I can verify any ambiguous matches by eye
The sheet has company domains in column B instead of names
Look up each company domain in column B using LeadIQ and add employee count to column C, industry to column D, and headquarters city to column E — leave cells blank where LeadIQ returns no match
Normalize the company names, deduplicate, enrich all firmographic fields, and flag low-confidence matches
Trim whitespace from all company names in column A, flag any duplicates in column F, then for each unique company search LeadIQ and fill in employee count, industry, headquarters city, and LinkedIn URL into columns B through E — mark any rows where LeadIQ confidence is low or the match is ambiguous in column G
Getting the cleanup and the enrichment done in one shot means the sheet that goes into the scoring model is already consistent, not something that needs another pass before it's usable.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet with a CRM export or account list — then ask it to pull firmographic data from LeadIQ into your columns. For the contact-level version of this workflow, see backfilling job titles and current employers, or check the LeadIQ overview for everything that's possible.