How to Turn LinkedIn Post Likes and Comments Into an ICP-Filtered Lead List
People who liked or commented on a LinkedIn post turn into a lead list in three steps. Pull the reactions and comments off the post. Cut everyone outside your ICP, which on most posts is the majority. Then write to the people who are left within a few days, with the post as the reason. For one post, our free post scanner does the first two steps in about 30 seconds and needs no account. If you want that list every day from posts you never see, such as your competitors' posts or the loudest voices in your market, you need a tool that watches them for you.
Why engagers beat a cold list
A name on a bought list did nothing. A person who commented on a post about the problem you solve did something this week, in public, and you can refer to it in your first line.
The kind of engagement matters. A like costs one second. A comment costs a sentence, and it tells you what the person thinks, which is most of what a good first message needs. Work the commenters first.
Recency matters just as much. A comment from this week is a reason to write. A like from three months ago is a record, and signals lose value by the week.
Picking people this way moves the numbers before you write a single better sentence. Between June and September 2026 we sent 836 LinkedIn invitations to people picked by signals, with no note on the invitation. 40% accepted, and 25% of the people we then messaged replied (HeyReach data, pulled 1 October 2026). Expandi's 2026 benchmark across 13.2 million connection requests puts the average at 28.5% acceptance and 10.4% replies. The invitation said nothing, so the difference came from who we picked.
Which posts to pull, warmest first
| Post | Who engages | What it tells you |
|---|---|---|
| Your own posts | People who already follow your thinking | The warmest list you have. They chose you |
| A competitor's posts | Buyers comparing options in your category | Active research, often before a shortlist exists |
| A category voice writing about your problem | People working on that problem | Interest in the problem, not yet in a vendor |
| Posts about an event you attend | Speakers, attendees and exhibitors | A shared moment you can mention |
| A job ad for the role you sell into | Mostly job seekers and recruiters | Usually nothing. Skip it |
Your own posts are the most underrated list a small team has, and the list refreshes every time you publish. Competitor posts are the richest, and they have their own playbook in your competitor's followers are your warmest leads. If you exhibit at shows, the engagers on show posts belong in your trade show follow-up list.
Step 1: get the names off the post
LinkedIn has no export button for reactions or comments. There are three ways to get the list, from no risk to the most.
By hand. Open the post, open the reactions, read the comments and copy the names into a sheet. That is fine for one post with 40 engagers, and nothing runs on your account.
A scanner for one post. Paste the post URL into our free post scanner. It pulls the people who liked or commented, works out where they work and what they do, and marks the ones who look like your customers. No account, about 30 seconds.
Automation on your own login. Browser extensions and scraping tools that run on your LinkedIn session can pull hundreds of posts. They also act as you. LinkedIn does not publish a limit, and in our own test on 7 October 2026 a read-only job in a logged-in Chrome tab started getting 403 errors after about 150 calls in about 40 minutes. LinkedIn's User Agreement does not allow scraping, so a restriction lands on the account you used, which is often the one you sell from.
This is why we never read data through a client's LinkedIn account. We run our own accounts and infrastructure for it, so a restriction lands on us.
Step 2: cut the noise, then check the ICP
Most engagement on most posts does not come from buyers. In our own daily review of raw signals, around two thirds fall into four noise classes, and all four show up under posts:
- Colleagues congratulating a teammate.
- Former colleagues doing the same on a job-change post.
- Likes on job ads.
- Likes on motivational posts that name no product, problem or number.
A fifth class appeared on 30 September 2026: a recruiter's job ad is filed under the recruiter, so the "hiring company" is a staffing firm posting for someone else.
Then apply the ICP: industry, company size, geography and role, checked against where the person works now, not where an old export says they worked. Expect the list to shrink hard. In our production run on 21 August 2026, 161,072 companies were evaluated and 8,689 passed the ICP filter, about 5%. In a run we published on 10 August 2026, 341 of 4,774 raw signals survived, 7.1%. If most of a post's engagers pass your filter, the filter is too loose. Tighten it with an ICP built for signal-based selling.
Step 3: write about the topic, not the like
"I saw you liked Mark's post" reads like surveillance, and it gives the person nothing to answer. Write about what the post was about, and what it means for them.
For a commenter, their own words are the opening: "Hi Anna, you wrote under Mark's post that reply rates dropped once the list got bigger. Was that a list problem or a timing problem on your side?"
For someone who only liked the post, leave the like out and use the topic: "Hi Tom, a lot of sales leads are rethinking volume this quarter. Is reply rate the number your team watches, or meetings booked?"
Send within a few days, while the post is still in their head. The pattern behind both openers is in name the consequence, not the signal.
Which tool fits which job
| Your situation | Pick |
|---|---|
| One post, once, to see who is in there | By hand, or our free post scanner |
| A few posts a month, and someone who is fine running a scraper and owning the account risk | A general scraping tool such as PhantomBuster or an Apify actor, plus a sheet for the filter |
| You already pay for Sales Navigator | It has no filter for engagers on other people's posts. See is Sales Navigator enough for buying signals |
| You used Trigify for this | Trigify customers had until 22 October 2026 to export their data. See what to export and how to switch |
| Engagers on competitors' and category voices' posts every day, filtered to your ICP, with a draft waiting for approval | B2B Signals. Software from $200 a month, or we run it for you |
| You work from Claude or Codex | Our MCP is in every plan. See buying signals your AI agent can use |
If you post twice a month and sell to a few dozen accounts, you do not need a tool for this. Do it by hand. Whichever way you pull the list, the steps after it are the same ones laid out in signal-based selling, the complete system.
Mistakes that waste a good post
Pulling every engager into a sequence. Most of them were never buyers. The filter is the step that pays.
Messaging about the like. Nobody wants to be told what they clicked. Talk about the topic.
Treating old engagement as fresh. A like from last quarter is history. Pull posts from the last week or two.
Running the scraper on the account you sell from. If it gets restricted, your outreach stops with it.
Skipping your own posts. The people who engage with you are the warmest names outside your customer list.
Frequently asked questions
Can I export the people who liked a LinkedIn post? Not with a button. You can read reactions and comments on the post by hand, run a scanner for a single post, or use a tool that collects them on a schedule. Tools that log in as you put that account at risk.
Is it allowed to scrape LinkedIn post likers? The names on a public post are visible to anyone who opens it. Automated collection is different: LinkedIn's User Agreement does not allow scraping, and tools that run on your logged-in account can get it restricted. Read by hand, or use a service that does not run on your account.
How many engagers on a post are usually a fit? It depends on the post and your ICP, so measure it on your own posts. For context, around two thirds of our raw signals are noise before any ICP check, and on 21 August 2026 about 5% of 161,072 companies passed our ICP filter.
Should I mention the post in my first message? Mention the topic, or their comment if they wrote one. Leave out the like.
How soon should I reach out after someone engages? Within a few days. A comment from this week gives you a reason to write. One from last quarter does not.