First-time comprehension
Select people who have enough context to be plausible users without giving them the product-team vocabulary that hides confusing language.
§ Use case · artificial respondents
Artificial respondents for UX research
Artificial respondents can review an interface before you recruit real usability participants. Use the first round to find obvious confusion, trust breaks, mismatched expectations, and better questions for the live UX session.
- Pages, onboarding, prototypes, and app journeys
- Select respondents before the read
- Sharpen the real usability session
Last updated
The decision
Do not spend a paid UX session discovering the first screen is unclear
Real participants are most valuable when the basic framing has already survived contact with someone outside the product team.
Bring the interface or journey you can still revise. Select artificial respondents by the audience characteristics that matter to the task, then let them encounter it independently.
The first round gives the team concrete hypotheses about what people notice, what they think the product wants them to do, where they hesitate, and which assumptions deserve direct human validation.
Why Antestrata is different
Respondents are synthesized before the research brief searches for them. The research selects people from the generated population rather than inventing personas to fit the task.
§ 02 · The panel
Choose people for the UX question you actually have
A usability question about first-time setup needs different people from a trust question about a financial workflow.
Antestrata lets you select respondents by geography, age, income, education, literacy, technology readiness, behavioural disposition, and other available characteristics. The point is to build the panel around the decision, not around a generic user portrait.
Because respondents already exist inside the population, the research brief selects them. It does not create their personalities to fit the interface being tested.
Different levels of technical comfort
Compare respondents who treat setup friction as normal with respondents who expect the next action to be obvious immediately.
Trust-sensitive journeys
Use cautious and proof-sensitive respondents when the interface asks for money, data, permissions, commitment, or delegation.
Same panel after a revision
Re-run the same people after the interface changes so the team can compare reactions without replacing the audience at the same time.
§ 03 · Workflow
How artificial UX research works
Use artificial respondents before recruitment, then hand the unresolved questions to real participants.
01
Choose the interface
Bring a landing page, onboarding sequence, prototype, screen set, or bounded app journey that the team can still change.
02
Select the audience
Choose respondents whose circumstances and behaviour make them relevant to the specific UX question.
03
Observe the read
Use a quick read for early direction or a deeper encounter when scroll, path choice, available clicks, and sequence can change the finding.
04
Plan the human study
Carry the strongest confusion points and competing explanations into the real session instead of starting from a blank discussion guide.
§ 04 · Research questions
Questions worth asking before recruitment
The artificial round is best at exposing where the product team has mistaken familiarity for clarity.
What does this screen appear to be for?
Check whether the user's first interpretation matches the job the product team thinks the screen performs.
What would they do next?
Find competing next actions, hidden prerequisites, and moments where the interface asks the user to infer too much.
Where does trust change?
Trace which claim, permission, price, proof cue, or missing explanation changes willingness to continue.
Who should the real study recruit?
Use the disagreement between respondents to identify the profiles that deserve direct observation with real people.
Planning your study
It is not eye-tracking, a validated usability benchmark, or evidence that real users will complete a task at a measured rate.
Use it to remove obvious problems, sharpen hypotheses, and spend real participant time on behaviour that needs a real human in the loop.
More use cases
Other work worth pressure-testing first
The product stays the same. The panel, research question, and thing being tested change with the business decision.
Pitch decks
Pressure-test a pitch deck with artificial respondents selected for investor-relevant backgrounds and decision patterns before real VCs and angels see it.
Landing pages
Test landing-page positioning, proof, trust, pricing context, and calls to action with artificial respondents before sending real traffic.
Pricing
Pressure-test price presentation, plan logic, value framing, premium tiers, and willingness-to-pay questions with artificial respondents before real buyers see them.
Product concepts
Pressure-test an early product idea, feature concept, value proposition, or product brief with artificial respondents before engineering or live recruitment.
Onboarding
Use artificial respondents to find setup friction, unclear next steps, trust breaks, and activation problems in onboarding before real users encounter them.
§ Before the real users.
Let the rough version meet people before recruitment starts
Bring the interface that is still changing. Use artificial respondents to find the questions worth paying real participants to answer.