There are two people who search for how to see who liked a LinkedIn post. One is curious: they wrote a post, or they saw one, and they want to glance at the list. The other is prospecting: every one of those reactions is a person who just raised a hand, and they want that list as leads. The good news is that the first question takes one click, and the second takes one more.
How to see who liked a LinkedIn post
Open the post and click the reaction count, the small cluster of reaction icons directly beneath the post text. A panel opens listing everyone who reacted, with tabs to separate a plain Like from Celebrate, Support, Love, Insightful, and Funny. It works on desktop and in the mobile app, and it needs nothing installed. [1]
That is the whole answer for the curious reader. For everyone else, the more useful question is what you do with the list, and the honest first step is choosing which of these you actually want:
| What you want | Do this | What you get | Can you export it? |
|---|---|---|---|
| Just to see who reacted | Click the reaction count under the post | An on-screen list, tabbed by reaction type | No, view only |
| The likers as a lead list | Paste the post URL into a likes finder | The people, ready to filter and export | Yes |
| Likers pulled through your own login | A cloud tool that logs in as you | A CSV, generated by a tool running your account | Yes, once you are logged in through the tool |
The three rows are three different jobs. Most guides collapse them into one and then wonder why the "just looking" reader ends up signing up for a whole outreach tool they only needed for a glance. Keep them separate.
Where the native reactions panel stops
The panel is the right tool right up to a point, and then it quietly becomes the wrong one. It loads names in small batches, there is no export button, the reaction-type tabs are the only sorting on offer, and there is no way to save the list. It is built for reading, not for working. The moment your goal is a list you can act on, the panel is friction.
Two hard limits are worth knowing before you scroll:
- There is no export and no search. By a few hundred reactions you are scrolling a modal and retyping names into a spreadsheet, and every name a hand mistypes is a prospect the search bar can never find again.
- PhantomBuster reports a limit of 3,000 visible likers per post. Its export documentation attributes this ceiling to LinkedIn, so the tool cannot retrieve every profile from a post above that limit. [2]
So the panel answers "who liked this" and fails at "give me these people as a list". For the second job you need a different approach.
How to export the liker list as a lead list
Reactions on a public post are public data. That means a server can read the same list you can see and hand it back as an exportable lead list instead of an on-screen panel. This is the path for the prospector: paste a URL and work from a list you can filter, not a scroll session with no search bar.
- Copy the post URL. Open the post on its own page, not in your feed, and copy the address from the bar. Use the full permalink, not a shortened share link.
- Paste it into a finder. The LinkedIn likes finder takes the URL and returns the people who reacted, ready to filter and export.
- Filter before you export, not after. Cut the list down while it is still on screen. Trimming it now is faster than cleaning a CSV later.
Commenters are worth grabbing in the same pass. A comment costs visible effort, so it is a stronger signal than a like, and the list is usually shorter. The comments finder works the same way, from the same URL.
This is the see-and-export path. If you want the full comparison of every export method, that is a separate piece: how to export LinkedIn post likers. This page is about seeing the list; that one is about getting it out at scale.
Paste a post.
Get the people who liked it.
The likes finder reads a public post and hands back the people who reacted, in a list you keep. Free to try.
Find who liked a post
The automation tools: PhantomBuster and Dux‑Soup
The other common route is a bulk automation tool. These work, and they are popular. Here are the two most-searched options next to BeReach's approach, on the axes that actually matter: whether the list comes back ready to work, and whether a person reviews the message before it sends.
| Tool | Hands back a list ready to message? | AI and workflow support | Watch-out |
|---|---|---|---|
| PhantomBuster post-likers export | Exports profile data; sorting it is a separate workflow | AI filtering and outreach in the separate engagers workflow [6] | Reports a 3,000-liker limit per post [2] |
| Dux-Soup / STACKED | Lead management and CSV export; the rest depends on your setup | AI message personalization and campaign automation | Local needs your machine; Cloud runs on vendor infrastructure [4] |
| BeReach likes finder | Yes, a list ready to export and message | Yes, drafts each message for your approval | Public posts only |
The sources behind those rows, checked on 2 October 2026:
- PhantomBuster. Its Post Likers Export takes a LinkedIn session cookie and post URLs, then exports profile data to CSV. Its documentation reports a 3,000-liker ceiling per post. [2] The current annual plans are Start at $56 per month, Grow at $128 and Scale at $352, billed annually. Plans include unlimited users, with execution time and credits varying by tier. [3]
- Dux-Soup now presents its offer as STACKED. Local runs as a desktop app on your own machine; Cloud runs on the vendor's infrastructure without keeping your machine on. Local costs $55 per seat monthly, or $41.25 per month billed annually. Cloud costs $99 monthly, or $74.17 per month billed annually. Both include AI message personalization. [4]
If your job is to monitor engagement continuously as a buying signal rather than grab one post's list, a signal platform is a different category worth knowing. Trigify was one of them and closes on 22 October 2026; the Trigify alternatives rundown compares the signal tools still open and which of them send.
BeReach sits deliberately on the other side of this table. The likes finder reads the public post, builds the list, and drafts a first message for each person, with a human approving every one before it sends. Pricing and trial details are on the pricing page rather than quoted here so they stay current.
Turning likers into replies
A list of 400 names is not 400 leads, and this is the half that decides whether the whole exercise was worth an hour. A like is a weak signal on its own: it costs nothing and often means "I read the first line". Two filters do most of the work. First, fit: does this person match who you sell to, judged more on company shape than on title alone. Second, relevance of the post: someone who reacted to a post about the problem you solve is worth far more than someone who reacted to a viral hiring post.
Belkins' 2026 study reports a 12.2% total reply rate for Messenger campaigns targeting existing connections, compared with 7.9% for Connector campaigns that begin with a connection request. These figures come from Expandi's dataset of 15.1 million outreach contacts during 2025. They compare campaign types, not post likers against other prospects, and do not establish that a like causes a higher reply rate. [5]
Timing matters as much as fit. Content engagement is the most perishable signal on LinkedIn: the person was thinking about your topic minutes ago, not next quarter. The deeper read on why reactions rank where they do among intent signals is in LinkedIn engagement signals, and the full playbook for acting on them without spraying is signal-based selling on LinkedIn.
When you do write, reference the idea, not the click. "I saw you liked a post about X" is surveillance with extra steps. "Your point about X" or "the thread on X got me thinking" writes to a person engaged with a topic, which is the only version of this that earns a reply.
Frequently asked questions
How do I see who liked a LinkedIn post?
Open the post and click the reaction count, the small row of reaction icons directly under the post text. A panel opens listing everyone who reacted, with tabs to filter a plain Like from Celebrate, Support, Love, Insightful, and Funny. It works on both desktop and the mobile app and needs nothing installed. The panel is for reading, not exporting.
Can I see who liked a post that is not mine?
Yes. The reaction list on any public post is publicly viewable, so you can open someone else's post and click the reaction count to see who reacted, exactly as you would on your own. Posts shared to a restricted audience are the exception: if you cannot see the post, you cannot see its reactions.
Does the person know when I view who liked their post?
No. Clicking the reaction count and reading the list does not notify anyone. Viewing the panel is not a profile view. What can be visible is opening an individual person's profile from that list, which may appear in their "who viewed your profile" depending on your own privacy settings. The list itself is silent.
How do I turn the list of likers into leads?
Copy the post URL, use a likes finder to export the profiles, then cut the list down for fit and relevance before messaging. For context, Belkins reports 12.2% replies for existing-connection Messenger campaigns and 7.9% for Connector campaigns. Those benchmarks are not specific to people who liked a post.
Sources and references
External sources checked on 2 October 2026. Each numbered mark in the article points to the source that supports that passage.
- LinkedIn Help: Use LinkedIn reactions
The reaction types available on LinkedIn.
- PhantomBuster: LinkedIn Post Likers Export
Export inputs, CSV output and the reported 3,000-profile visibility limit.
- PhantomBuster: Pricing
Current plan names, annual billing and execution allowances.
- Dux-Soup: STACKED pricing
Local and cloud deployment, AI personalization and current prices.
- Belkins: LinkedIn B2B outreach statistics, 2026 study
Messenger and Connector reply rates, based on 2025 campaign data. Updated 29 June 2026.
- PhantomBuster: LinkedIn Post Engagers to Lead Outreach
The separate workflow includes AI filtering and outreach.
