Set up a keyword alert for "sales pipeline" or "cold outreach" and the posts start flooding in. Some from VPs of Sales at companies that look exactly like your ICP. Some from recruiters posting about hiring for a sales role. Some from a student writing an essay for class. All three match the keyword. Only one is worth your time.
This is the blind spot in most LinkedIn engagement tools and most manual routines built around keyword tracking. It answers "what's this post about" and skips right past "who wrote it." For anyone using LinkedIn to build pipeline, that second question is the one that matters.
Why this happens
Keyword matching is the easy version of this problem. Scan the text, flag a match, done. It's fast and simple, which is why most tools default to it. Figuring out who's actually behind a post, their title, their industry, whether they even resemble your buyer, means reading the writer's profile, not just their caption. That's the harder problem, and most tools skip it.
The cost shows up as wasted time. You open your queue, see a post that matched, read it, realize the author is a recruiter or a hobbyist, and move on. Do that enough times a day and a "quick fifteen minute check" turns into something much longer, not because there's more engaging happening, just more filtering.
What matching on the right thing looks like
Take the phrase "sales pipeline." A VP of Sales at a B2B SaaS company using it is exactly the kind of prospect worth commenting on. A recruiter using the same phrase to describe a hiring pipeline isn't, even with an identical keyword match. The difference lives entirely in who's behind the account.
That's the actual engineering problem behind prospect matching. It's not enough to flag posts about your topics. The system also has to check whether the person posting has a job title and industry resembling your actual buyer, and only surface posts that clear both filters.
Why this changes what your queue looks like
Once every post in front of you comes from someone who genuinely matches your ICP, everything downstream gets easier. The comment is more relevant because you're speaking to someone in a role you actually understand. The relationship has a real shot at turning into a conversation. And reviewing the queue takes less time, because there's no sorting real prospects out of a pile of noise.
Allen's prospect-matched discovery reads both the topic and the author, job title and industry, and only surfaces posts that pass both filters. A VP of Sales writing about cold outreach makes it into your queue. A recruiter writing about sales hiring gets filtered out automatically, even with a matching keyword.
If your current routine involves a lot of scrolling past posts that don't quite fit, that's the keyword problem showing up in real time. The fix isn't finding more posts. It's finding the right ones.
Start a free trial and see what a queue built around your prospects looks like, not just your keywords.