We tested Evelance predictions against real human responses to measure accuracy. We selected airfocus, a roadmapping tool for product teams, and ran parallel evaluations with 2 groups: 23 real people and 7 Evelance personas.
Both groups gave open feedback about the product with no scripts or leading questions. We then mapped their responses to find where themes overlapped.
Evelance personas and real people flagged the same concerns. Both groups mentioned Jira integration as their first connection to the product. Both questioned what "AI-powered" actually meant. Both said the value proposition required extra effort to understand, and both expressed hesitation about learning another tool.
A real respondent put it differently but meant the same thing: they would "keep using what we are already using since we are already familiar with Jira/Notion."
It took us 3 weeks to collect feedback from 23 real people between recruiting, scheduling, following up, and compiling their responses. Evelance gave us the same insights in under 10 minutes.
| Dimension | Real People | Evelance Personas |
|---|---|---|
| Time to Insight | 2-4 weeks | Under 10 minutes |
| Accuracy to Real Behavior | 100% (baseline) | 89.78% validated |
| Audience Targeting | Limited by recruitment | 2M+ Evelance Personas, 1,700+ job types |
| Behavioral Memory | Full life history | Absorbed behavioral data |
| Context Awareness | Real circumstances | Time, stress, environment factors |
| Response Authenticity | Genuine reactions | Internalized identity shapes response |
| Cost Per Response | $57+ per participant | $2.99 per persona |
| Scheduling Required | Yes, with no-shows | None |
| Psychology Framework | Requires analysis | 12 dimensions built-in |
| Repeatability | Different people each time | Same persona, consistent baseline |
Evelance predicted how real people would respond to airfocus with 89.78% accuracy. The personas flagged the same concerns, valued the same features, and expressed the same hesitations.
This does not mean you skip talking to real users. It means you already know what they will say before you ask.