The LinkedIn algorithm, explained
Your post doesn’t go to everyone. It goes through stages, and each stage is decided by different signals. Step through them and flip the habits that matter.
Pool. Candidate pool: Of everything posted by your connections, follows, and topics they care about, the system picks a pool of candidate posts for each member’s feed.
Bars are illustrative relative audience sizes, not real LinkedIn numbers. Toggle the switches to see which stage each habit affects.
What we actually know
LinkedIn has published a fair amount about its feed on its engineering blog and in statements from its product team. The consistent themes:
- Relevance first. The feed tries to show each member posts they will find valuable, weighted towards people they know and topics they follow.
- Meaningful engagement. Comments and conversations count for more than a quick reaction. Time spent reading a post (“dwell time”) is a signal — which is why the hook and the “…more” tap matter.
- Quality filtering. Classifiers look for spam, low-quality content and engagement bait, and can limit distribution.
- Expertise. LinkedIn has said it wants to surface knowledge and advice from people with genuine expertise in a subject.
What nobody outside LinkedIn knows is the exact weighting. Be wary of anyone quoting precise “golden hour” percentages or secret rules.
What to do with that
- Write a hook that earns the tap — test it in the preview.
- Make the body easy to read on a phone — the formatter helps.
- End with a real question and reply to comments early.
- Post when your audience is online — see the best-time chart.
- Skip the bait, the mass tags and the three-posts-a-day schedule.
Engagement rate calculator
3.46% engagement rate
(reactions + comments + reposts + clicks) ÷ impressions. Compare to your own average post.
0.25 comments per reaction — a conversation post: people are talking, not just tapping.
Questions people ask
How does the LinkedIn algorithm work?
LinkedIn Engineering describes a multi-stage system: it gathers candidate posts for each member, filters out spam and low quality, then ranks what’s left by how likely each member is to engage meaningfully. New posts get an early test audience; strong early signals widen distribution.
What does the LinkedIn algorithm reward?
Posts people spend time on and talk about: dwell time, genuine comments and replies, and relevance to the reader’s interests and network. LinkedIn has said it values knowledge and advice from people with expertise in a topic.
What hurts reach on LinkedIn?
Engagement bait (“comment YES to get the PDF”), tagging many people who aren’t involved, posting several times a day, and content its classifiers treat as spam. Many creators also report lower reach on posts with outbound links.
What is a good engagement rate on LinkedIn?
It varies widely by audience size and industry; industry reports commonly put typical rates in the low single digits (roughly 1–5% of impressions). Compare your posts against your own average rather than a universal benchmark.
Does editing a post hurt reach?
LinkedIn hasn’t confirmed any penalty for editing. Fixing a typo after posting is fine; the bigger risk is spending the crucial first hour editing instead of replying to comments.