The numbers
| Measure | Founders and CEOs | Dataset average | Rank |
|---|---|---|---|
| Prospects contacted | 19,600 | – | – |
| Reply rate | 41.2% | 32.3% | 1st of 14 |
| Meeting rate | 6.3% | 4.7% | 1st of 14 |
| Average deal size | €16,400 | €39,006 | 14th of 14 |
| Pipeline per 1,000 prospects | €1,033,000 | – | 12th of 14 |
Reply rate is 8.9 points above the dataset average and meeting rate is 1.6 points above it.
What the data says about this persona
Founders and CEOs reply more than any other persona in the dataset and they are worth the least per deal. Both facts follow from the same thing: the people who answer their own LinkedIn messages are running companies small enough that nobody screens their inbox.
That makes them the right target when you need speed and volume of conversations, and the wrong one when you are building a business case on deal value. Per thousand prospects contacted, founders produce about €1.03m of pipeline. Solution architects, who reply nine points lower, produce €2.78m from the same thousand.
The other thing worth knowing is that the seniority rule inverts here. Everywhere else in the dataset, going one rung below the decision maker produced twice the meetings. Under about 50 employees the founder is also the operator, so there is no rung below to go to. Go straight at them.
What to put in the message
Name their product. Reference something they built or shipped, not something they announced. Ask one operational question about how they handle a problem today.
What to leave out
Anything that reads like it went to a list. Founders see more outbound than anyone and pattern-match on it in the first line. Also avoid asking for 15 minutes in the first message.
The format itself does not change by persona. Across every segment we tested, the winning first message was two and a half sentences, ended in a question, named something of theirs, said nothing about us and landed between 240 and 420 characters. That version replied at 44.5% against 18.6% for the same message with solution detail added.
Method
Figures for this persona come from 19,600 prospects inside a wider dataset of 389,890 prospects and 15,018 meetings, run for 17 clients across 41 programmes between 2018 and 2026. Prospects were split at random inside each client account, so industry, geography, seniority and company size are held constant on both sides of every controlled test. Meetings are counted at the point one was accepted in the client’s calendar; we do not track what happens after that.
Full method, all fifteen tests and the breakdowns by company size and region are on the 2026 outbound benchmarks page.
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Cite this page as: Prospectio.ai, Outbound benchmarks for Founders and CEOs, 19,600 prospects, 2018 to 2026.