Your LinkedIn connection acceptance rate is the share of your connection requests that people accept: accepted divided by sent, times 100. There’s no single “good” number that holds for everyone, because the rate swings with who you contact and how well they know you. The benchmark that tells you something is your own median across several batches.
Below are the common questions people search about this number, answered in the order they usually come up once you start tracking.
1. What is a good LinkedIn connection acceptance rate?
Honest answer: it depends on who you’re sending to, and anyone quoting one universal figure is mixing very different situations together.
Think about what goes into the number. A request to someone you met at a conference last week is a different task from a request to a stranger in another industry. People with mutual connections or a shared school have a reason to say yes. People who barely log in leave requests sitting for weeks. Job seekers, recruiters, founders and salespeople all reach out for different reasons, and recipients treat each one differently. Your photo and headline play a part too, since many people glance at them before deciding.
So we don’t publish a target figure, and we’d be wary of one that comes without a clear description of who was contacted and how. A rate someone else got with a different audience tells you very little about yours. What does tell you something: comparing your next batch with your own past batches.
2. How do I calculate my acceptance rate?
acceptance rate = accepted ÷ sent × 100
Two more rates show what happens after people accept:
reply rate = replies ÷ people messaged × 100
meeting rate = meetings ÷ replies × 100
You can do this on paper, or enter your counts into the free Acceptance and Reply Rate Calculator, which works out all three plus how many requests each meeting takes.
3. Can you show me a worked example?
Here’s one with made-up numbers, purely to show the math. They aren’t a benchmark.
Priya, an account executive at a fictional company called Lumen Health, sends 50 requests in one week to clinic operations managers. Two weeks later she has:
| Count | Number |
|---|---|
| Requests sent | 50 |
| Accepted | 18 |
| Messaged after accepting | 18 |
| Replied | 4 |
| Meetings booked | 1 |
We entered these counts using the same formulas our calculator runs, and it returned:
- Acceptance rate: 36.0%
- Reply rate: 22.2%
- Meeting rate: 25.0%
- Requests per meeting: 50.0
One detail from the calculator’s code worth knowing: if you leave “people you messaged” empty, it works out the reply rate from accepted requests instead. That’s a fair stand-in when you message everyone who accepts, as Priya did.
None of this tells Priya whether 36% is good. It tells her where she is today, which is the thing she’ll measure her next change against.
4. When should I count? Requests are still being accepted.
Easy to get wrong. Requests keep getting accepted for a while after you send them, so a batch counted after three days looks worse than the same batch counted after three weeks.
Pick a fixed waiting period, for example two weeks after sending, and count every batch at the same point. Then your batches are comparable.
5. Do pending and withdrawn requests count?
Pending requests count as sent but not accepted. If a large share of a batch is still pending at your cutoff, make a note of it, because that usually points to inactive recipients rather than a “no.” Our glossary entry on pending invitations explains what happens to them.
Withdrawn requests also stay in the “sent” total for their batch. Clearing out old requests is good housekeeping, but removing them from the math would make your rate look better than it is.
6. How do I set my own baseline?
One batch is noisy. In a batch of ten, one extra acceptance moves your rate by ten points. So build a baseline from several:
- Take your last 10 to 20 batches if you have them. Fewer is fine as a starting estimate.
- Work out each batch’s rate, counted at the same waiting period.
- Sort them and take the median, the middle value. With an even number of batches, average the two in the middle.
- Write down what those batches had in common: who you targeted and which note you used.
Another made-up example. Morgan, a recruiter, has ten weekly batches with acceptance rates of 22, 25, 28, 30, 31, 33, 35, 38, 41 and 60 percent. The two middle values are 31 and 33, so the median is 32%. The average would be 34.3%, pulled up by the 60% week when Morgan only contacted people from a recent event. The median barely notices that week, which is why we prefer it.
Keep separate baselines for audiences that behave differently. Warm event contacts and cold prospects shouldn’t share one number.
7. My rate is low. What’s wrong?
Use the pattern in your numbers to narrow it down:
| What you see | Likely cause | What to try next batch |
|---|---|---|
| Low across every audience | Your profile or your note | Clearer photo and headline, a more specific note |
| Low in one audience only | Targeting | Narrow to people with a visible link to you |
| Lots still pending at cutoff | Inactive recipients | Check for recent activity before sending |
| Good acceptance, few replies | Your first message | Shorter, more about them, an easy question |
Change one thing per batch. If you change the note and the audience at the same time, you won’t know which one made the difference.
8. How do I raise it without risking my account?
Send fewer, better requests. That’s most of it.
- Check that each person has a clear reason to say yes: shared work, a shared event, a real overlap.
- Add a short note that names the shared context and why you want to connect, with no pitch. Notes have a character limit, which can be shorter on some free accounts; the LinkedIn limits page has the current figure.
- Make your profile easy to trust at a glance.
- Draft with the Connection Message Generator, which writes a note from the person’s name and one detail, then edit it so it sounds like you.
An example note we wrote for this page:
Hi Dana, I saw your talk on intake workflows at the Northwind clinic summit. I work on the same problem at Lumen Health and would like to connect.
What not to do: send more requests to make up for a low rate. More ignored requests make the problem worse, and lots of ignored or declined requests can lead LinkedIn to limit your invitations. Skip automation tools that send requests for you, too. They break LinkedIn’s rules and put your account at risk. For structure and wording, see How to Write a LinkedIn Connection Request.
9. They accepted. Now what?
Acceptance gets you in the door and nothing more. If your reply rate is the weak spot, work on the first message and the follow-up. How to Follow Up on LinkedIn covers timing and wording.
A simple log to start with
Copy these columns into a spreadsheet and fill in one row per batch:
| Batch | Date sent | Audience | Note used | Sent | Accepted at 2 weeks | Still pending | Rate |
|---|---|---|---|---|---|---|---|
| 1 | |||||||
| 2 |
After five or six rows, sort by rate and you’ll start to see which audiences and notes work for you. That’s your benchmark, and it’s more useful than any outside figure.
Measure your next batch
Send your next batch with one change, wait your usual period, then put the counts into the free Acceptance and Reply Rate Calculator and compare the result with your median. The LinkedIn analytics guide shows how outreach numbers sit alongside the rest of what you track.