The numbers
| Measure | Product Leaders | Dataset average | Rank |
|---|---|---|---|
| Prospects contacted | 38,700 | – | – |
| Reply rate | 33.8% | 32.3% | 5th of 14 |
| Meeting rate | 4.9% | 4.7% | 6th of 14 |
| Average deal size | €39,800 | €39,006 | 6th of 14 |
| Pipeline per 1,000 prospects | €1,950,000 | – | 6th of 14 |
Reply rate is 1.5 points above the dataset average and meeting rate is 0.2 points above it.
What the data says about this persona
Product leaders reply at 33.8 percent and book at 4.9 percent, both slightly above average, with a €39,800 average deal. What makes them worth separating out is the gap between those two numbers: they book at a higher rate than IT directors despite replying less often, which means the replies you get are better qualified.
They appeared alongside CTOs in the InMail test, and it is the most extreme result in the dataset. Sales Navigator InMail to product and technical leaders at 500 to 2,000 employee companies replied at 3.7 percent. A connection request followed by a message, same list, same twelve weeks, replied at 37.0 percent. Ten times, and the organic route costs nothing per send.
The reason is that senior product people treat InMail as advertising, because that is functionally what it is. A connection request is a social object. A sponsored message is an ad unit, and they have learned to read the little label.
What to put in the message
A specific problem in their product surface, or a competitor’s release. One question about how they are thinking about it.
What to leave out
InMail entirely. Also avoid anything framed around sales or revenue outcomes, which is not what they are measured on.
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 38,700 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 Product Leaders, 38,700 prospects, 2018 to 2026.