Validate with real world data
Use observed responses to check a decision after modelled research.
Validate with real world data when a finding from modelled research needs to be checked against observed behaviour, actual product use or responses from the intended market.
Plan the check
Keep the decision, audience definition, question or stimulus and outcome measure comparable to the research you are validating. Decide in advance what result would support, revise or reject the working hypothesis.
Choose a real-world method that fits the risk: interviews for explanation, a survey for structured responses, a usability session for observed interaction or a controlled product or message test for behaviour. Do not describe a synthetic response as a real-world observation.
Compare the evidence
Read the modelled result and observed responses side by side. Record where the audiences, context, wording, sample source or outcome measure differ. A disagreement can identify a coverage or modelling limitation; it is not automatically proof that either source is correct.
Document the decision, the evidence used and the remaining uncertainty. Share the relevant research scope through reports, and preserve the real-world method and outcome alongside the synthetic result.
Cost and next steps
Validation costs depend on the external method and provider. iMario research credits do not purchase real participants or guarantee a real-world sample. Use the comparison to refine the audience, material or question before a new run.