The Scenario
The compensation committee meeting is next Tuesday. You're a compensation analyst and someone just handed you a list of forty job titles that the company is actively hiring for — they want a pay-range benchmark for each role, grounded in what's actually being posted in the market today, not last year's survey data.
Google Jobs is the most current source you have. SerpHouse can query it. Your workbook already has the job titles in column A. What it doesn't have is the ten columns of employer, location, and salary data that need to be there by end of week.
The bad version:
- Search Google Jobs manually for each title, scroll through the postings, record the employer, location, and listed salary for the top results
- Some postings list salary ranges, some list hourly rates, some list nothing — decide how to handle each case mid-paste
- Finish row 12, realize you forgot to note the posting date on rows 3 through 8, go back
You're supposed to be doing analysis. The synthesis — which roles are underpaying relative to market, which locations carry a premium — is the part the committee actually needs. But you can't get to the synthesis until the raw data is in the workbook.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Excel workbook. It reads the job title list, queries Google Jobs via SerpHouse for each role, and writes the posting data — company, location, salary, date — directly into the columns you specify.
For each job title in column A, search Google Jobs via SerpHouse and paste the top 5 results with company name, location, and salary into the next 15 columns
What You Get
- Columns B through P receive employer name, location, and salary data for up to five Google Jobs postings per role
- Salary fields include whatever the posting lists — range, hourly rate, or blank if no compensation is posted
- Posting dates are written where available, giving you a recency signal for each data point
- Rows are written in order so each job title maps cleanly to its results
What If the Data Is Not Quite Ready
The job titles have seniority prefixes that need normalizing before the search
For each title in column A, strip any leading "Senior," "Junior," or "Associate" prefix before searching Google Jobs via SerpHouse, then write the top 3 result companies, locations, and salaries into columns B through J
You only want roles where a salary range is listed
For each job title in column A, search Google Jobs via SerpHouse, write the top 5 results into columns B through P, and mark column Q as "No salary listed" for any posting where SerpHouse returned no compensation data
You want to join the benchmarks with your internal salary bands from a second worksheet
Search Google Jobs via SerpHouse for each title in column A of the "Job Titles" worksheet, write the top market salary into column B, then look up the internal band from the "Salary Bands" worksheet and write the variance into column C
You want to clean the list, pull benchmarks, flag gaps, and calculate average market salary in one shot
Deduplicate the titles in column A, search Google Jobs via SerpHouse for each unique role, write the top 3 salaries into columns B, C, and D, calculate the average across those three in column E, and mark column F as "No market data" for any role where SerpHouse returned no salary information
The committee gets the benchmark table. You get to spend your time on the analysis that actually drives the decision.
Try It
Get the 7-day free trial of SheetXAI and open any Excel workbook with a list of job titles in column A — ask SheetXAI to pull live Google Jobs data from SerpHouse and fill in employer, location, and salary across your columns. See also bulk organic ranking pulls or return to the SerpHouse overview.