The numbers
| Measure | Heads of Engineering | Dataset average | Rank |
|---|---|---|---|
| Prospects contacted | 31,200 | – | – |
| Reply rate | 36.4% | 32.3% | 3rd of 14 |
| Meeting rate | 5.6% | 4.7% | 3rd of 14 |
| Average deal size | €41,200 | €39,006 | 5th of 14 |
| Pipeline per 1,000 prospects | €2,307,000 | – | 4th of 14 |
Reply rate is 4.1 points above the dataset average and meeting rate is 0.9 points above it.
What the data says about this persona
Heads of engineering are third on reply rate at 36.4 percent and fourth on pipeline value at €2.31m per thousand prospects. They are the reliable middle of the technical buying group: senior enough to sponsor a purchase, close enough to the work to answer a specific question.
They appeared in the subject-matter fit test alongside solution architects, and the result there is the single most useful thing to know about them. Sent a message that matched their actual technical remit, they replied at 51.9 percent. Sent the same message on job-title targeting alone, 13.0 percent. Four times the response for work done before the send button, not after.
The failure mode with this persona is volume. There are far fewer heads of engineering than IT directors, and the ones at interesting companies get approached constantly. A list of 500 well-researched heads of engineering will outperform 5,000 scraped ones by a wide enough margin that the second list is not worth building.
What to put in the message
The specific system or team you think is under strain. A named competitor or tool in their stack. One question about how they currently handle it.
What to leave out
Anything about cost savings or efficiency without a technical anchor. Also avoid the word ‘solution’.
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 31,200 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 Heads of Engineering, 31,200 prospects, 2018 to 2026.