LinkedIn attention benchmark for one B2B market
We read the public LinkedIn reactions of the most active people in one B2B market. In the latest pull, no single author reached more than 4 of the 100 people we read, and 94.8% of authors reached exactly one person.
Very little of it landed on vendors we could measure. Of 30,029 public actions seen across four weekly reads, 15 landed on posts from the company itself or the competitor pages it watches. That is 0.05%.
The market is Postelix's own, so the company in that sentence is us. This is one market and one period, and the limits below matter as much as the numbers.
By Julian Meinke, Founder of Postelix. Published 31 October 2026. Updated quarterly, next in January 2027.
The LinkedIn attention benchmark at a glance
Most LinkedIn benchmarks start from the post and report what it received, such as an engagement rate for a company page. This one starts from the audience and asks where a defined market's public reactions went.
| Measure | Result |
|---|---|
| Widest reach of any author, latest pull | 4 of 100 people |
| Authors who reached exactly one person | 94.8% |
| People touched by the 10 widest-reaching authors | 27 of 100 |
| Actions on own posts or watched competitor pages | 15 of 30,029 (0.05%) |
| Actions on any post we track | 118 of 30,029 (0.39%) |
| Reactions on posts by a person, where the author is known | 247 of 330 (74.8%) |
Pulled 31 October 2026. One market. Reach comes from 100 people in the latest pull, and actions from 503 people over four weekly reads.
Author reach: no one covered more than a few people
Reach counts how many of the people we read reacted to an author at least once. One person counts once per author, however many of that author's posts they reacted to. This is the creator overlap count from our method. We publish no author names.
| Week of | 7 Sep | 14 Sep | 26 Oct |
|---|---|---|---|
| People read | 199 | 200 | 100 |
| Authors seen | 5,504 | 5,629 | 2,544 |
| Authors reaching one person | 96.0% | 95.9% | 94.8% |
| Widest reach of any author | 8 | 5 | 4 |
| People touched by top 10 authors | 40 | 37 | 27 |
The widest reach was about 4% of the people read in two pulls and 2.5% in the other. The pulls overlap only in part: we matched 19 of the October people to the second pull and 11 to the first. The result repeating across them is the strongest evidence on this page.
The last row needs care. We picked those 10 authors after seeing the results, which nobody planning a creator budget can do. Even with that advantage they touched between about 1 in 5 and 1 in 4 of the people read, at least once each. In the October pull, the 100 widest-reaching authors touched 67 of the 100 people.
Where the actions landed: 99.6% on posts we do not track
Across four weekly reads in October we saw 29,956 public reactions from the 503 most active people in the market. We matched each one by post to everything Postelix tracks in this market, then added 73 further actions that our other capture routes saw from the same people.
| Landed on | Actions | Share |
|---|---|---|
| Own posts and watched competitor pages | 15 | 0.05% |
| Posts from watched accounts in the market | 71 | 0.24% |
| Posts found through tracked topics and events | 32 | 0.11% |
| Every other post | 29,911 | 99.61% |
| Total | 30,029 | 100% |
The 15 actions came from 11 people on 9 posts. Own posts and competitor pages share a row because we do not publish a group smaller than 10 people.
A handful of pages will always look small next to everything on LinkedIn, so read this as a sense of scale, not a verdict on any vendor.
Treat 15 as a floor. We watch eight competitor company pages and only three produced data in this window, and part of that gap is a capture problem on our side. Posts by competitors' employees count as other posts. Postelix is also a small company, and a well-known vendor would score higher. Ten times this count would still be 0.5%.
The whole market shows a similar picture. Of 3,595 people, 88 (2.4%) were seen acting on our posts or a watched competitor's page between 29 September and 26 October.
Who wrote the posts: people first, then their own employer
For a smaller set of 330 reactions we know the author, because a separate process had opened those posts.
| Author | Reactions | Share |
|---|---|---|
| A person | 247 | 74.8% |
| The reader's own employer's page | 45 | 13.6% |
| Another company or organisation page | 38 | 11.5% |
About 3 in 4 went to people. A little over half of the reactions on pages went to the reader's own employer, which leaves about 1 in 9 for every other page, vendors included.
Read this as a rough split. The set is not random, and it only covers posts with readable text that the other process chose to open.
What we take from it
These are our readings of one market, not rules.
Who is in the sample
The market is Postelix's own target market: marketing, growth and founder roles at B2B software and technology companies, mainly with 10 to 250 employees, in DACH, wider Europe and the US. On 31 October 2026 it held 3,595 people at 2,365 companies. Unlike our category reports, it is a list of target people, not a sample of people who engaged with vendors.
We read only the most active part of it. People are ranked by Postelix's activity score, which is built from the public actions we record. The reads feed that score, so the same people tend to stay on the list. The 503 people in the weekly reads and the 100 in the latest pull are the top of that ranking, and 502 of the 503 were still in the market on 31 October.
| Group | Market | Read |
|---|---|---|
| Founder or CEO | 45% | 38% |
| Marketing or growth practitioner | 21% | 25% |
| Marketing or growth leader | 19% | 21% |
| Sales, revenue or other | 15% | 17% |
| United States | 36% | 35% |
| Rest of Europe | 26% | 25% |
| DACH | 23% | 24% |
| Elsewhere or unknown | 15% | 16% |
Shares are of the 3,595 people in the market and the 502 in the weekly reads. Groups come from free-text titles and locations, so they are approximate. A title is a proxy: some of these people hold no budget, and some real buyers are missing.
The weekly reads cover 14% of the market and 11% of the people seen acting on own or competitor posts, so they do not lean towards those engagers. Some people in the sample have been contacted by Postelix, which could lift our own share.
How we measured it
Sample, calculation and naming rules follow our published method, and we name no person or company in the target set.
What this data cannot see
Who this applies to, and who it does not
This describes a broad market, where the same job titles exist at thousands of companies across several regions. That is the position of a B2B software company selling to marketing or growth leaders.
It does not describe these cases:
Refresh plan and corrections
This page keeps its address. We plan to rerun it every quarter with the same saved queries, and the next update is planned for January 2027. If the market definition changes, the page will say so.
If a number here is wrong, write to help@postelix.com. We will fix it and say what it was before and when it changed, as our method promises.
Questions
It is too early to say. One market in one period cannot set a norm. This edition shows what happened in a broad B2B marketing market in autumn 2026, and narrow categories already look different.
An engagement rate benchmark starts with posts and reports what they received. This one starts with a defined market and reports where its public reactions went. The two answer different questions, so the numbers cannot be compared.
No. It means 15 of the 30,029 public actions we saw landed on those posts. Views are invisible to us, some competitor pages produced no data, and employees' posts are counted elsewhere. Read it as a floor on public actions, not a share of attention.
The data cannot say that. It counts public reactions, and a page can reach people who never react. It does suggest that reaction counts on your own page are a poor picture of what your market is doing.
This data does not say that. It says one author reached few of the most active people in a broad market, so a single large bet has little support here. A narrow category can look very different, so measure overlap in your own market and test several creators first.
Because it is ours to publish. Customer workspaces are never used for this research, in aggregate or otherwise.
Postelix tracks the same public signals for a market you define, including creator overlap and competitor engagement. The tables on this page were built by hand for this report, so the demo shows the product views, not this exact page.
Book a demo. Then run it on your own market for 7 days.
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