In plain English
For decades, usability research meant finding real people who match your audience and watching them use your product. Synthetic users compress that into software: instead of recruiting a busy parent on a slow phone or a screen-reader user in a hurry, you spin up an AI persona that behaves like one.
Each synthetic user carries traits that shape how it behaves — its device, its tech-savviness, how much patience it has before giving up, and what it's trying to accomplish. Point it at your app and it acts the part, then tells you exactly where the experience let it down.
What makes a synthetic user
| Background | Who they are and what they already know — a first-time visitor vs. a power user. |
|---|---|
| Device & context | Phone or desktop, fast or slow connection, distracted or focused. |
| Goal | The job they're trying to get done — sign up, find pricing, complete checkout. |
| Patience | How much friction they'll tolerate before they bounce — a key driver of realistic behavior. |
Why it matters
Synthetic users make usability testing something you can afford to do constantly instead of rarely. They're repeatable — the same tester can run against every release — and they cover audiences that are hard to recruit, like people using assistive technology. For a solo founder or small team, they turn a program that used to require a research budget into a $49 check. They're the engine behind AI user testing and agentic testing.
SaaS Dummies testers are synthetic users with names
SaaS Dummies gives you a cast of reusable synthetic testers — each with a fixed device, temperament, and quirks — that drive your live app in a real browser and report back with session video. Because they're consistent run to run, you can watch the same tester retry a flow after you ship a fix and confirm it's actually better.
Meet the testers ($49) →Synthetic users vs. human testers
- Speed: synthetic users report in minutes; human studies take days to schedule.
- Cost: a fraction of moderated research, so you can run them on every change.
- Consistency: the same tester behaves the same way each run — clean before/after comparisons.
- Depth: humans still win on genuine emotion, taste, and brand perception.