The numbers
| Measure | VP Sales | Dataset average | Rank |
|---|---|---|---|
| Prospects contacted | 42,800 | – | – |
| Reply rate | 30.1% | 32.3% | 10th of 14 |
| Meeting rate | 4.4% | 4.7% | 8th of 14 |
| Average deal size | €57,300 | €39,006 | 1st of 14 |
| Pipeline per 1,000 prospects | €2,521,000 | – | 3rd of 14 |
Reply rate is 2.2 points below the dataset average and meeting rate is 0.3 points below it.
What the data says about this persona
VP Sales carry the largest average deal in the dataset at €57,300 and reply at 30.1 percent, which is below average. That gap is the whole story with this persona: hard to reach, expensive to reach, worth a great deal when you do.
Per thousand prospects they produce €2.52m of pipeline, third highest of the fourteen. The cost of getting there is higher than the number suggests, because sales leaders are the single most heavily prospected group on LinkedIn and they evaluate your outbound as a professional. A weak first message does not just fail, it disqualifies you.
The seniority finding applies here as strongly as anywhere. In enterprise accounts the sales director will reply and delegate; the sales manager or head of SDRs one rung down will take the meeting. If you are selling anything that changes how a team works day to day, the manager is the better first contact and the VP is the second.
What to put in the message
A number from their own world. A competitor they lose to. One question about how the team currently does the thing.
What to leave out
Selling to a salesperson with sales technique. They will name the framework you are using. Also avoid flattery of any kind.
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 42,800 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 VP Sales, 42,800 prospects, 2018 to 2026.