The number
| Measure | AI order-to-cash |
|---|---|
| Prospects contacted | 12,400 |
| Meeting rate | 4.2% |
| Rank | 9th of 12 |
| Cross-category average | 3.9% |
| Meetings per 1,000 prospects | 42 |
This is meeting rate, not reply rate. It counts a meeting from the point it was accepted in the client’s calendar, which is why it is a much smaller number than the reply-rate benchmarks published elsewhere in this category. Reply rate is a leading indicator. Meeting rate is the decision.
What the data says
AI order-to-cash books at 4.2 percent across 12,400 prospects, above the 3.9 percent cross-category average.
It is the most interesting entry in the table because it should not perform this well. It is a newer category, which normally means education, and education is what drags the bottom of this table down. What appears to save it is that the underlying problem, cash collection and invoice handling, is old, painful and owned by someone specific, usually in finance or operations.
The lesson generalises. A new category attached to an old problem sells. A new category attached to a new problem needs a different channel entirely.
The tests that matter most here
- Question-led against company-led copy: 3× the reply rate
- Verified subject-matter fit against job title: 4× the reply rate
- Two and a half sentences, question-led: 2.4× the reply rate
The full set of fifteen is on the 2026 outbound benchmarks page.
All twelve categories
| Category | Prospects | Meeting rate |
|---|---|---|
| Software development | 17,630 | 5.5% |
| Coding software | 3,690 | 5.3% |
| Outsourcing | 3,480 | 5.3% |
| Marketing SaaS | 2,880 | 5.3% |
| Systems integration | 4,050 | 4.6% |
| Analytical SaaS | 3,760 | 4.6% |
| HR SaaS and AI | 46,200 | 4.4% |
| CPaaS | 34,800 | 4.2% |
| AI order-to-cash | 12,400 | 4.2% |
| Cloud platform | 117,000 | 3.5% |
| CRM | 84,300 | 3.5% |
| Networking and security | 59,700 | 3.5% |
The spread from top to bottom is 5.5 against 3.5 percent, a factor of 1.6. Worth keeping in perspective: in the targeting test, the same sequence produced 13.0 and 51.9 percent reply rates depending only on how the list was built. Category matters less than how well you know the person you are writing to.
How this data was collected
12,400 prospects in this category, inside a 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 for every controlled test, holding industry, geography, seniority and company size constant on both sides, and no test was called below 2,000 prospects per arm.
One thing to hold in mind. The category is the seller’s, not the prospect’s: it describes what our client sells rather than what the person receiving the message does. The breakdowns by who was contacted are on the persona, company size and region pages.
Cite this page as: Prospectio.ai, Outbound benchmarks for AI order-to-cash, 12,400 prospects, 2018 to 2026.