The Scenario
Your team is preparing a competitive content brief and your manager wants to know what the top 25 competitors have been posting on LinkedIn over the past month — actual post text, engagement numbers, and dates, in a workbook the content team can sort and filter.
The bad version:
- Open each company's LinkedIn page, scroll through their recent posts, and copy the text and engagement count into a row in the workbook
- Discover that LinkedIn limits how far back you can scroll without the right account type
- Manually flag posts that mention pricing or product launches, reading every post twice
Twenty-five companies, ten posts each, reading every post twice. That is a full day that produces a table your content team will partially ignore anyway.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Excel workbook. It reads your company list and calls Crustdata's LinkedIn post retrieval endpoint for each entry, writing the returned posts into the structure you need.
For each company in column A, use Crustdata to fetch the last 10 LinkedIn posts and write them into new rows in a worksheet called LinkedIn Posts with columns: Company, Post Date, Text Preview, and Likes Count. Flag any post that mentions pricing or product launches in a Signal column.
What You Get
- A LinkedIn Posts worksheet with one row per post
- Columns: Company, Post Date, a 200-character text preview, Likes Count
- A Signal column flagging posts where the text contains pricing or product-related keywords
- Any company with no recent LinkedIn activity gets a single note row
What If the Data Is Not Quite Ready
Some company names in column A do not match their LinkedIn page names
For each company in column A, check Crustdata for a LinkedIn URL match and note the resolved page name in column B, then fetch the last 10 posts using the matched entity
You want posts from a specific date range
For each company in column A, use Crustdata to fetch all LinkedIn posts published between April 1 and April 30, 2026 — write them into the LinkedIn Posts worksheet with Company, Post Date, Text Preview, and Likes Count
You want to separate high-engagement posts from low-engagement ones
Fetch the last 10 LinkedIn posts per company in column A using Crustdata, write them all into the LinkedIn Posts worksheet, then add an Engagement Tier column where posts with over 100 likes get "High" and everything else gets "Low"
One prompt to collect posts, flag signals, score engagement, and produce a priority summary
For each company in column A, use Crustdata to fetch LinkedIn posts from the past 30 days — write them into LinkedIn Posts with Company, Post Date, Text Preview, Likes Count, and a Signal column for pricing, funding, product launch, or hiring mentions. Then create a Summary worksheet with one row per company showing total post count, average likes, and whether any high-signal posts were found.
Try It
Get the 7-day free trial of SheetXAI and open your competitor tracking workbook with company names, then ask it to pull the last 10 LinkedIn posts per company from Crustdata and flag the ones worth reading. You can also ask it to run keyword-based LinkedIn searches across the same list.