The Scenario
A new keyword showed up in three discovery calls this week: prospects keep mentioning they are evaluating "AI agents" for their operations team. Your demand-gen manager wants to know which companies are actively posting about this on LinkedIn right now — the assumption is that companies posting publicly about AI agents are either buyers, competitors, or both. You need a list by end of day.
The bad version:
- Search LinkedIn manually for each keyword, scroll through the results, and copy company name, post date, and a text snippet into a sheet row by row
- Notice that LinkedIn search results are personalized and you are not seeing the full universe of posts — your network is filtering the output
- Try to add a second keyword and realize you now have two separate result sets that you need to deduplicate before the sheet is usable
Manual LinkedIn keyword research at any scale is not a workflow. It is a sampling exercise with unknown bias.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Google Sheet. It reads your keyword list and calls Crustdata's LinkedIn post search endpoint, writing the results into a structured output sheet.
Search LinkedIn posts on Crustdata for the keywords in column A of my sheet — use a 14-day lookback window — and write matching results into a new sheet called Signal Posts with columns: Keyword, Company, Post Date, Post Snippet, and Follower Count. Deduplicate rows where the same company appeared for multiple keywords.
What You Get
- A Signal Posts sheet with one row per unique company-post combination
- Columns: the keyword that matched, company name, post date, first 200 characters of the post, company follower count
- Deduplication applied so a company posting about both "AI agents" and "workflow automation" appears once, with a note listing both matched keywords
- Row count per keyword written to a Summary row at the bottom so you can see which terms returned the most activity
What If the Data Is Not Quite Ready
Your keyword list in column A has some duplicates and near-duplicates
Before searching Crustdata, deduplicate column A and remove keywords that are substrings of other keywords in the list, then run the LinkedIn post search for the cleaned keyword set and write results to Signal Posts
You want to filter results to companies above a certain follower count — smaller pages are not relevant
Use Crustdata to search LinkedIn posts for each keyword in column A over the past 14 days — write results to Signal Posts only for companies with more than 5,000 followers, and note how many results were filtered out at the bottom of the sheet
You need to separate results by industry to route them to different sales teams
Search Crustdata for LinkedIn posts matching keywords in column A from the past 14 days — write results into Signal Posts with a Company Industry column populated from Crustdata's company data. Then create separate sheets for SaaS, FinTech, and Other industries.
One prompt to search, enrich, score, and deliver a prioritized outreach list
Search Crustdata for LinkedIn posts matching the keywords in column A posted in the past 14 days. For each company in the results, also fetch their headcount and last funding stage from Crustdata. Write all results into Signal Posts with columns: Keyword, Company, Post Date, Headcount, Funding Stage, and a Priority column where companies with over 100 employees and Series A or later get "High" and everything else gets "Research".
The keyword search and the firmographic enrichment happen in the same pass.
Try It
Get the 7-day free trial of SheetXAI and open a Google Sheet with your keyword list in column A, then ask it to search LinkedIn via Crustdata and populate a Signal Posts sheet with matched companies. You can then ask it to enrich those companies with headcount and funding data to score the list.