The result
| Variant | Reply rate | Meeting rate |
|---|---|---|
| Generic value proposition | 17.1% | 1.8% |
| Named their product or a competitor | 34.5% | 4.3% |
Sample
2023, twelve weeks, 10,815 prospects. Companies of 500 to 2,000 employees. Split at random inside each account.
Why it works
A named product is a proof of work. It cannot be produced by a merge field on a scraped list, so it tells the reader that someone spent time on them specifically, before they have read a single claim.
Naming a competitor does something slightly different and slightly better. It creates a small unresolved tension. People have opinions about their competitors and those opinions want out, which is why the reply you get to a competitor mention is often longer and more useful than the reply to a compliment.
It also skips a step. If you can name their product, you do not have to explain the category, and the message can be about their situation rather than about establishing what you are talking about.
How to apply it
Name one thing, in the first line, that you could only know by looking. Their product, their competitor, something they shipped.
Do not stack them. Two specifics in a short message reads as research; four reads as a dossier, and the tone shifts from interested to unsettling.
If you cannot find something specific for a given prospect, that prospect is telling you something about your list. Take them off it rather than falling back to a generic opener.
What this test does not tell you
Mid-market and upper mid-market only, at 500 to 2,000 employees. Smaller companies frequently have no obvious named competitor, so the tactic is harder to execute there. The test does not separate the effect of naming their own product from naming a competitor, which are likely to behave differently.
Method
One variable at a time. A test alters a single element; if two things change we learn nothing. Prospects were split at random inside each client account, holding industry, geography, seniority and company size constant on both sides. No test was called below 2,000 prospects per arm, because outbound is noisy at low volume. Reply rate is reported as the leading indicator and meeting rate as the decision, because several variants lifted replies and produced no extra meetings at all, and those were not rolled out.
This test is one of fifteen in a dataset covering 389,890 prospects and 15,018 meetings across 41 client programmes and 17 clients, run between 2018 and 2026. The full set is on the 2026 outbound benchmarks page.
Cite this page as: Prospectio.ai, Test 5: naming the prospect’s own product or a direct competitor, B2B Outbound Benchmarks 2026.