The Scenario
Your pipeline review is Friday morning. You have a Google Sheet with 400 target accounts — company name in column A, domain in column B — and right now columns C through F are empty. The VP of Sales wants headcount, latest funding round, and 6-month headcount growth attached to every row before the slides go out Thursday evening.
The bad version:
- Open Crustdata's web interface, search each company name one at a time, copy the headcount and funding fields into the right row
- Hit a naming mismatch on row 38 — "Acme Corp" vs. "Acme Corporation" — and spend 15 minutes figuring out which company is actually right
- Finish 60 rows by lunch, realize you have 340 left, and accept that the data will be incomplete when the deck lands
There is no version of that process that gets 400 rows done by Thursday. The work itself is not the problem — the volume is.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that runs inside your Google Sheet. It reads your sheet structure, connects to Crustdata, and can enrich your full list in one pass based on a single typed instruction.
For every company in column A, use Crustdata to fetch current headcount, latest funding round, and 6-month headcount growth — write the results into columns C, D, and E. Flag any rows where Crustdata returned no match in column F.
What You Get
- Column C: current headcount figure from Crustdata's live dataset
- Column D: latest funding round label (e.g., Series B, Seed) and amount
- Column E: 6-month headcount growth percentage
- Column F: a "no match" flag for any company name that didn't resolve — so you can review those rows rather than silently receiving blank cells
What If the Data Is Not Quite Ready
The company names in column A have extra suffixes — "Inc.", "Ltd.", "GmbH"
For every company in column A, strip legal suffixes before passing the name to Crustdata, then fetch current headcount and latest funding round — write results into columns C and D and flag unmatched rows in column E
The list has duplicate companies at different rows
Deduplicate column A by company name, then for each unique company use Crustdata to fetch headcount and funding stage — write results back to every matching row and add a note in column F if the row was a duplicate
Headcount growth should be calculated from two specific Crustdata snapshots, not the default window
For each company in column A, use Crustdata to get headcount as of January 2025 and headcount as of January 2026 — write both values into columns C and D, then calculate the percentage change and put it in column E
One prompt to clean the list, enrich it, and score each account
Remove any rows in column A where the company name is blank or says "TBD", then use Crustdata to fetch headcount, funding stage, and 6-month growth for the remaining companies — write those into columns C, D, and E, then add a priority score in column F where companies with over 200 employees and Series B or later funding get "High" and everything else gets "Low"
The pattern is to ask for the data cleanup and the enrichment action in the same prompt. SheetXAI handles the conditional logic without requiring two separate passes.
Try It
Get the 7-day free trial of SheetXAI and open your prospect pipeline sheet with company names and domains, then ask it to bulk-enrich every row using Crustdata's firmographic data. From there, also see how SheetXAI handles headcount timeseries pulls and job listing signals.