Methodology · · 7 min read
What Synthetic Research Actually Replaces — and What It Doesn't
Synthetic research is not a replacement for fielded studies. It is a different instrument, useful in different windows. The teams that get the most out of it are the ones who learn the difference fast.
The decisions traditional research can't reach in time
Most enterprise insights teams already have the research they need for the high-stakes, projectable reads — the launch trackers, the segmentation studies, the regulatory work. What they don't have is a way to test the messaging tweak, the payer objection, the field talk track on Tuesday and have an answer Wednesday morning.
That gap — the everyday decisions that fall between fielded studies — is where synthetic research compounds. It runs in hours, calibrated against the brand's own data, and it is built for iteration rather than projection.
Where synthetic research should not be allowed
Anything requiring statistical projection to a real population. Anything going on a regulatory submission. Anything that depends on observing a behavior nobody has documented yet. Synthetic models cannot see what is not in the data they were grounded against.
We say this on every pilot scoping call. The customers who succeed with the platform are the ones who treat it as an extension of their research stack, not a substitute for it.
How to sequence both inside one workflow
Field the projectable study. Use the synthetic layer to iterate on the message, the objection map, the field talk track between waves. When the next wave reads out, recalibrate the synthetic models against the new data. The two layers feed each other.
The teams that adopt this pattern stop arguing about whether synthetic research is real research. They start arguing about which decisions belong in which layer — which is the conversation that actually moves the work forward.