The Scenario
You track 50 SaaS companies as part of your competitive intelligence function. Every quarter you're supposed to produce a ranking by headcount growth rate — but the data lives in Crustdata, the sheet is in Google Sheets, and whoever built the last version of this report left the company in January. You inherited the tab but not the process.
The bad version:
- Open Crustdata, find each of the 50 companies, navigate to the headcount history view, and manually copy quarterly snapshots into the sheet
- Notice halfway through that the date format Crustdata displays is different from what the sheet expects, and spend time reformatting each entry
- By the time you hit company 30, you realize you have not been consistent about which quarter you recorded — some rows have March data, some have February
The resulting table will technically have numbers in it, but the analysis built on top of those numbers will be unreliable.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Google Sheet. It reads your company list, calls Crustdata's headcount timeseries endpoint for each company, and places the returned values in a consistent structure across your sheet.
For the 50 companies in column A, pull Crustdata headcount timeseries from January 2023 to today at 6-month intervals — write each snapshot into a new column labeled with the date, then add a growth-rate formula in the final column comparing the first and last values
What You Get
- One column per 6-month interval, labeled Jan 2023, Jul 2023, Jan 2024, Jul 2024, Jan 2025, Jul 2025
- Each cell contains the Crustdata headcount figure for that company at that point in time
- Final column contains the calculated growth rate across the full window
- Any company where Crustdata has no timeseries data gets a note in a separate column rather than a silent blank
What If the Data Is Not Quite Ready
Some companies in the list have been acquired or renamed since the last report
For each company in column A, check Crustdata's records and note in column B if the company has been acquired or rebranded, then fetch headcount timeseries only for companies that are still independent and active
You need the data structured as a pivot-ready flat table instead of wide columns
For the 50 companies in column A, pull quarterly Crustdata headcount snapshots from Q1 2023 to Q1 2026 and write the results as a flat table in a new sheet called Headcount Data, with columns: Company, Quarter, Headcount
The growth rate should be calculated against a specific baseline quarter, not just first-vs-last
Use Crustdata to fetch headcount for each company in column A at Q1 2024 and at Q1 2026 — write both values into columns B and C, then calculate the 2-year growth rate in column D sorted descending
One prompt to clean the company list, pull the timeseries, and produce a ranked output
Remove any rows in column A where the company name is blank or duplicated, then use Crustdata to fetch headcount at Jan 2024, Jul 2024, Jan 2025, and Jul 2025 for each remaining company — write those four values into columns B through E and add a rank column in F ordering companies from highest to lowest growth between Jan 2024 and Jul 2025
The approach is to ask for the structural transformation and the data pull together. SheetXAI handles both without needing you to prepare the sheet first.
Try It
Get the 7-day free trial of SheetXAI and open your competitive intelligence tracker with a list of target companies, then ask it to pull Crustdata headcount timeseries and build the growth-rate table. You can also ask it to track funding milestones or job listing counts for the same company set.