The Scenario
Your team sells HR-tech software to enterprise accounts, and your best signal for prioritization is whether a company is actively hiring in engineering — that usually means they have a technology investment underway and budget moving. You have a Google Sheet with 80 target accounts. You need open job listing counts broken down by department before your outreach planning session tomorrow morning.
The bad version:
- Open LinkedIn or each company's career page, count roles by department, and enter the tallies into the sheet by hand
- Notice that some companies post engineering roles under "Technology" and others under "R&D" — so the department labels are inconsistent across companies, making the counts incomparable
- Get through 20 companies before the end of the day and realize this will take three more days at this pace
The inconsistency problem alone makes the manual output unreliable. You would spend as much time normalizing categories as you spent collecting the data.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Google Sheet. It reads your account list and calls Crustdata's job listings endpoint for each company, then writes the results in whatever structure you specify — counts per department, one row per open role, or both.
For each company in column A, use Crustdata to fetch current open job listings and write a count column per department — Engineering, Sales, Marketing, and Other — into columns C, D, E, and F. Note in column G when Crustdata returned no job listings for a company.
What You Get
- Column C: engineering role count
- Column D: sales role count
- Column E: marketing role count
- Column F: all other open roles
- Column G: a note for any company where Crustdata returned zero listings or no match, so you know the absence is real rather than a data error
What If the Data Is Not Quite Ready
You need individual role titles, not just counts
For each company in column A, use Crustdata to pull all current open job listings and write the individual roles into a new sheet called Job Listings with columns: Company, Job Title, Department, and Posting Date
Some companies in the list are parent companies and you only want listings from the subsidiary you actually sell to
For each entry in column A, check whether Crustdata has separate records for the parent and subsidiary, note which entity was matched in column B, then fetch job listings for the matched entity only
You want to flag accounts whose engineering hiring spiked in the last 30 days
Use Crustdata to fetch job listings for each company in column A and compare current engineering role count to what was posted 30 days ago — write both counts into columns C and D and add a flag in column E for any company where engineering listings grew by more than 20 percent
One prompt to enrich the account list with job signals, firmographics, and an outreach score
For each company in column A, use Crustdata to fetch current engineering job count, current headcount, and last funding stage — write those into columns B, C, and D, then add an outreach score in column E where companies with 10 or more engineering openings and Series B or later funding get "Priority" and everything else gets "Standard"
Combining the signal pull and the scoring logic in one prompt means you walk into the planning session with a ranked list, not raw counts.
Try It
Get the 7-day free trial of SheetXAI and open your target account sheet, then ask it to pull job listing counts by department from Crustdata for each company. You can also ask it to overlay those signals with headcount trends or recent LinkedIn posts from the same accounts.