A good engagement rate on LinkedIn is one that beats your own baseline, meaning the median rate of your last 10 to 20 posts. There is no single figure that holds for everyone, because the rate shifts with your audience, your niche, the post format and the formula you use. So the useful question is not “is 3% good?” but “is this post better than my normal post?”
That sounds like a dodge until you try it. Once you know your median, judging a post takes ten seconds. The rest of this page is a worksheet to get you there, plus the free Engagement Rate Calculator to do the arithmetic.
Why a universal number does not work
Several things move the rate that have little to do with whether your post was any good:
- Audience size and history. A small, close network behaves differently from a large one that includes people who followed you years ago for another reason.
- Niche. Some professional communities comment constantly. Others read quietly and act offline.
- Format. A poll, a document post, a plain text post and a post with a link invite different kinds of action.
- Reach beyond your network. When a post travels to strangers, impressions often grow faster than engagement, so the rate can drop on a post that did well.
- The formula. A rate by impressions and a rate by followers are different numbers, and many published figures do not say which they used.
That last point is why we do not publish a target. We have not collected engagement data across accounts with a method we would stand behind, and a number measured on someone else’s audience tells you little about yours.
Pick a formula, then never switch
Both common formulas count the same engagements: reactions, comments, reposts and, if you include them, clicks. They divide by different things.
| Formula | The question it answers | Use it when |
|---|---|---|
| Engagements ÷ impressions × 100 | Of the times this post was shown, how often did someone act? | Judging individual posts. This is the default for most people. |
| Engagements ÷ followers × 100 | Relative to my audience size, how much action did this get? | Comparing across months while your follower count changes, or comparing two accounts |
| Either one, without clicks | Same as above, counting only visible actions | Your older posts lack click data, or you want to focus on public reactions |
Pick one row and write it at the top of your notes. Mixing them is the most common way people fool themselves. The inputs are in each post’s analytics, and LinkedIn Impressions Explained covers what the impressions figure actually counts.
The baseline worksheet
Set aside fifteen minutes. You need a spreadsheet or a sheet of paper.
Step 1: list your recent posts
Take your last 10 to 20 posts. Fewer than ten is too noisy to trust. Going back many months can mix in an audience you no longer have. If you post in very different formats, such as polls and long text posts, make a separate list for each.
Step 2: work out each rate the same way
Pull reactions, comments, reposts, clicks and impressions for each post, at the same age if you can (one week after posting is a sensible checkpoint, since numbers keep moving for a while). Run each post through the calculator.
To see how much the formula matters, here is one hypothetical post. These numbers are made up to show the math, not a benchmark: 60 reactions, 15 comments, 5 reposts, 20 clicks, 2,500 impressions, 4,000 followers.
- By impressions: 100 ÷ 2,500 × 100 = 4.0%
- By followers: 100 ÷ 4,000 × 100 = 2.5%
- By impressions without clicks: 80 ÷ 2,500 × 100 = 3.2%
Same post, three answers, all correct. That is why Step 2 says “the same way.”
Step 3: sort and take the median
Sort the rates from lowest to highest and take the middle value. With an even number of posts, average the two in the middle.
Another hypothetical example. Ten rates by impressions, sorted: 1.8, 2.1, 2.4, 2.6, 2.9, 3.1, 3.3, 3.6, 4.4 and 9.0 percent. The two middle values are 2.9 and 3.1, so the median is 3.0%.
Step 4: write it down
Note the median, the date, the formula and whether clicks were included. Next month you will redo this with your newest posts, and those notes are what make the comparison fair.
What we checked
We ran the numbers above through a short script and through the logic our calculator uses, to make sure the page and the tool agree.
- The median of the ten example rates came out at 3.0%. The plain average came out at 3.52%. Only three of the ten posts beat that average, which shows how one strong post (the 9.0%) can make ordinary posts look weak if you use the average as your yardstick.
- Dropping the 9.0% post moved the median only from 3.0% to 2.9%, while the average fell from 3.52% to about 2.91%. The median barely notices one outlier. That stability is the reason to use it.
- The single-post example matched the calculator: 4.00% by impressions and 2.50% by followers.
- The calculator rounds to two decimal places, accepts numbers typed with commas like 2,500, and treats clicks and followers as optional. Leave followers blank and the by-followers result simply shows a dash instead of a number.
Reading a new post against your baseline
Once you have a median, each new post falls into one of a few cases.
| What you see | What it probably means | What to do |
|---|---|---|
| Rate above median, impressions normal | The post landed with your usual audience | Note the topic, hook and format. Try a similar one. |
| Rate below median, impressions much higher | It reached people outside your network, who act less often | Usually fine. Check total engagements, which may be up. |
| Rate below median, impressions flat or lower | Something did not connect | Look at what changed: topic, format, time or posting frequency |
| Rate far above median, few impressions | A small group responded strongly | Promising, but wait for a few more posts before reading much into it |
Two habits keep this honest. Compare like with like: polls with polls, text with text, same age, same formula. And ignore single swings. One post at half your median is not a trend; three months of falling medians is.
Look at comments on their own, too. A post with fewer reactions but several thoughtful comments from exactly the people you want to reach may have done more for you than its rate suggests.
Raising your baseline
Change one thing at a time, run it for several posts, and compare against the median. One post cannot tell a better hook from a lucky day.
- Work on the first line, since it decides whether people expand the post. How to write a LinkedIn hook has patterns to test.
- Write for one specific reader, such as first-time managers, so those readers have a clear reason to respond.
- End with a question people can answer from their own experience in a sentence. “Thoughts?” rarely does it.
- Keep paragraphs short for phone readers. The LinkedIn Post Generator turns rough notes into a draft with that structure.
- Reply to comments early, which keeps the conversation going.
- Post when your audience is around. The Best Time to Post planner helps you pick a window to test.
Skip anything that games the number, like comment-for-a-freebie posts or groups that trade likes. They inflate the rate without reaching anyone who matters to you.
Your next step
Open the free Engagement Rate Calculator, run your last ten posts through it, and find your median. Then measure your next post against it. For a monthly routine that turns these numbers into decisions, see our LinkedIn analytics guides.