Recruited-Incentive Research vs. a Causal Simulated Experiment First
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A product or research-ops lead with a recruiting budget faces the same question before every round of paid, incentive-based sessions: spend that budget now on real participants, or run a causal experiment on a simulated market first to find out which questions are worth paying people to answer.
The two things being compared are not substitutes
Recruited research pays real people, screened and scheduled, to sit through a session. The incentive is the cost of their time; the recruiting workflow is the cost of finding and confirming them. This is the right tool when a regulator, a stakeholder, or the method itself requires a real human: usability testing, ethnographic fieldwork, or any study where the record has to show an actual person responded.
A causal simulated experiment runs before any of that spend happens. It tests actions, comparisons, and audience definitions on a simulated market to estimate which ones are worth carrying into a recruited round. It answers a narrower question than a full study: is this concept, message, or price point differentiated enough to justify the incentive and scheduling cost, or should it be cut or reworked first.
The real decision is sequencing: which questions get answered with a simulated pass first, and which go straight to recruited participants because only a real session will do.
Where does the incentive-recruiting workflow actually spend the budget?
Incentive budgets depend on participant count, audience difficulty, and session duration. Recruitment and scheduling add operational costs; User Interviews' current pricing distinguishes plans and session allowances. One session can address several questions, so per-session pricing does not imply cost rises linearly with question count. Request a scoped recruitment and incentive estimate.
| Recruited, incentive-paid session | Causal simulated experiment | |
|---|---|---|
| What it produces | Human observations under the specified protocol | Estimated effects on generated choices within the design |
| Cost driver | Participant count, duration, audience and recruitment scope | Design, generation, analysis, review and any human validation scope |
| Where it's required | Usability, ethnographic, or regulator-mandated research | Narrowing which questions deserve that spend |
| Failure mode when misused | Fieldwork on a poorly specified question or sample | A modeled result treated as sufficient human evidence, or a promising option rejected without checking a simulation false negative |
What does Subconscious do in this sequence?
Subconscious uses generated responses in controlled choice studies and can separately scope a human study of the same alternatives and causal question. A synthetic screen can help prioritize, but keep uncertainty and false-negative risk visible before excluding alternatives.
The public causal-fidelity paper compares estimated choice parameters with corresponding human studies. Those rank results are different from a proven screening error rate for this research program. Evaluate task fit and human confirmation before treating a synthetic shortlist as settled.
Does Subconscious replace the recruited session it's meant to precede?
Agree who recruits, pays incentives and fields any human validation study. Those responsibilities and the participant consent process are separate from the modeled choice comparison. Direct human observations remain necessary when the endpoint or required provenance calls for them.
Cost of getting the order wrong
Recruiting for a poorly specified question can waste participant time and budget. Screening synthetically without checking population fit can reject a useful option. Omitting required human evidence can leave a consequential claim unsupported. Choose the sequence from those concrete risks.
Next step
Start with the questions on the research list and sort them: which require a real, recruited human session no matter what, and which are candidates for a causal simulated pass first. For the second group, see how the method works, check the research library for study examples, or book time to walk through a live experiment.