In short
The LinkedIn reply rates doing the rounds vary tenfold. That is not because some people prospect ten times better than others: they are not counting the same thing. Before asking whether your rate is good, you have to decide how you calculate it. Only then does the figure become a management tool.
This article deliberately gives no benchmark figure. We do not know of one solid enough to state, and copying one would lend it a reliability it does not have.
Why published figures cannot be compared
The denominator changes. Replies measured against messages sent, connections accepted or people contacted: the same number of replies gives three very different rates.
The definition of a reply changes. Does a polite refusal count? An out-of-office auto-reply? Depending on the choice, the result can double.
The population changes. A rate measured among procurement directors at large groups has nothing to do with a rate measured among managers of ten-person businesses. Comparing them means comparing two markets.
Three rules to write down once and for all
| Decision | The rule that holds | |---|---| | Denominator | People contacted, never messages sent | | Reply | Any human reply, refusals included | | Cut-off date | Last send + 21 days |
The first rule is the one that catches people out most. If you divide by the number of messages, every follow-up you add pushes the rate down. A complete sequence then looks less effective even though it produces more replies. You are reading the opposite of reality.
In an SME where two or three people prospect, these rules have to be shared. Otherwise Monday's sales meeting compares calculation methods, not results.
The closed cohort
A rate calculated on a rolling basis is always wrong: at any given moment, some of the messages are too recent to have received their reply.
The closed cohort solves the problem. You freeze a sending period, wait for the complete sequence to finish, on day 21, then you count. Once. The next period forms a new cohort.
Also note which message each reply came in on: the first message, or the follow-up on day 3, day 7 or day 14. Let us take a worked example, on a fictitious cohort of 80 people contacted:
| Message | Replies received | Share of replies | |---|---|---| | Day 0 | 6 | 50% | | Day 3 | 2 | 17% | | Day 7 | 3 | 25% | | Day 14 | 1 | 8% | | Total | 12 out of 80 people | Rate: 15% |
In this example, half the replies arrive after the first message. Stopping the sequence at day 0 would have given a rate of 7.5%, and led you to rewrite a message that was working. If, on the other hand, almost everything comes in on the first message, your follow-ups deserve a second look.
What moves the rate, in order of impact
1. How well the target fits. By far the biggest factor. An excellent message sent to the wrong person rescues nothing; an ordinary message addressed to someone the subject genuinely concerns gets a reply. If your rate is stalling, look at the list before the text, using an ICP written in one sentence.
2. The first line. It decides whether the rest gets read. A precise observation about the person works better than a presentation of your company.
3. The size of the ask. "Twenty minutes this week?" and "Is this something you are looking at right now?" do not ask for the same level of commitment. The heavier the ask, the fewer people reply.
4. Length. On a phone, a LinkedIn message is cut off after a few lines. Whatever goes beyond that is often never read.
5. Timing. It plays a part, but only at the margin. Optimising the send time of a poorly targeted message makes little difference.
Between two cohorts, change only one of these factors. Two simultaneous changes produce a result nobody can interpret.
How many contacts before drawing conclusions
Let us take a worked example. You test two first messages, each sent to 30 people. The first gets 3 replies (10%), the second 5 (around 17%). The gap looks clear. Yet it comes down to two people, and two people more or fewer may reply for reasons that have nothing to do with the text: holidays, a reorganisation, a busy day.
Around thirty people per version is therefore a floor, not a confidence threshold. The lower the rates, the more you need. Below that, the right reading is "no result yet", not "result to be confirmed".
The figure that really counts
The reply rate is an intermediate indicator. You can push it up by asking questions everyone answers with "yes, interesting", and fill your diary with meetings that lead nowhere, as described in the article on empty LinkedIn meetings.
So track two figures side by side: the reply rate, which tells you whether the message is being read, and the qualified meeting rate, which tells you whether it attracts the right people. They fit into the Friday dashboard, alongside three other figures noted in a quarter of an hour.
In the Trouve Tes Clients method, this measurement is the Manage step: without it, the four previous steps do not improve from one month to the next.