See who engages with your competitors on LinkedIn

Your typical B2B target list is built from filters like Industry, company headcount, job titles and maybe the funding stage. In theory they should care about your category, but IRL nobody has actually shown any signal yet.

In contrast, a competitor engager list starts from leads taking action. Someone left a like on a post in your topic sphere or they wrote a comment under someone's post giving away a guide adjacent to your product. That action is public and has a date attached. It tells you if they engaged with the topic in the last 90 days.

This is a lower bar than intent data and a much higher bar than firmographic data. And the best thing is you can verify it yourself, look at the post and the people reacting. This is your market

Competitor engagers are one of six sources. The others are brand engagers, meaning people who engaged your own page and your team's posts; trusted voices, the creators your market follows; champions, people who bought or used you before and moved company; market trends, the topics rising in the category; and your own inputs, such as a customer list or a CRM export.

Once the market exists, capture keeps it live. Every reaction, comment and profile view from a person in your market comes back as a named person with the exact post attached, so you know what they responded to and when. (Profile view capture needs LinkedIn Premium or Sales Navigator on the connected seat.)

Outbound. Every week you get an up to date outreach list: who entered the market, who is warming and who showed any kind of signal. That is your queue, already in order.

Ads. The market becomes a company list plus a title layer for LinkedIn Campaign Manager. You stop paying to reach a title filter and start paying to reach companies with proven attention in your category.

Events. You actually see who attended or will attend industry events. Company and person level where available.

Influencers. The creators your market follows with exact numbers and names who is following them. Steer your influencer collaborations with laser focus.

This is a real readout, pulled 27 August 2026. The market was built from competitor engagers and then title-filtered. 642 people were sampled, the 170 most active were used for the table, and the window was 90 days.

Attention published 24 posts in that window and drew zero reactions from this sampled market. We print zero as zero with the post count next to it, because the number is only true for these 170 people across these 90 days. Clari and Salesloft now post as one company, which is why they still appear with separate histories.

The topic rows are the useful part. Gong's strongest post in the window was about the biggest mistake people make on sales calls, at 74 market reactions. A post about AI discussions rising while teams stay the same size pulled 29. In all four markets we have pulled so far, craft beats product news by roughly two to one.

Method, printed on every table: market reactions per post = reactions and comments from the sampled market on a vendor's public posts in the window, divided by that vendor's posts in the window.

You can assemble a version of this by hand. Extraction is a solved problem and the tools are decent.

Databar describes itself as the data layer for modern go-to-market, with LinkedIn Post Likers and LinkedIn Post Commenters extractions, waterfall enrichment across many providers, and access through a spreadsheet, an API or MCP (as published on databar.ai, September 2026).

Linked Panda tracks a set of profiles, watches every like and comment around the clock, enriches the engagers and exports to CSV, Google Sheets, HubSpot, Salesforce or an API depending on plan. Published plans run from a 10 dollar pay as you go pack of 100 profiles to 199 dollars per month for 2,500 profiles and 15 tracked voices (as published on linkedpanda.com, September 2026).

Both handle the extraction step well. What is left after extraction is the slow part:

• Collapsing one person who reacted to four different competitors into a single row.
• Deciding which titles count as your market, then applying that same rule every week.
• Re-running the pull on a schedule so the list ages instead of rotting.
• Turning rows into a table you can act on: which vendor won attention, which topics pulled, which rooms, which voices.
• Keeping struck-out people struck out across every future pull.

If someone on your team owns that pipeline, the DIY route is cheaper. Most of the DIY pipelines we have looked at stopped within a couple of months, because nobody owned the weekly re-run.

Title looks right is not buying authority. A person can match the filter and still hold no budget and no influence. We write the sampled market. We do not write your buyers decided.

The list comes from public engagement on public posts. We do not buy intent data and we have no private view into who is in a buying cycle.

We never publish an engager list and never pass one to another customer. Vendors in the tables are public companies measured on public posts, so we name them. Voices are public creators measured on public posts, so we name them with their role. Private people stay inside your own account.

Postelix is a brand of Unfair Advantage Ltd in Cyprus, and the product is built for the European rules. We work from public LinkedIn engagement, vendor level aggregates and your own inputs. That posture is deliberate, because several US attention vendors geofence the EU or do not operate here at all.

Any number we give you is true for the sample and window printed beside it. A vendor with zero reactions from 170 people over 90 days did not reach those 170 people. A wider claim would need a wider sample.