Questions
How do I present the ROI of synthetic research?
TL;DR
- Present the ROI of synthetic research in terms of decisions: count the launches, pricing changes, messages and positions your team decides today with no data, or with data that arrives too late.
- Neon Blue builds simulated audiences: AI models that answer the way a defined group of people would, grounded in Neon Blue's own paid studies and AI-moderated interviews with real people.
- The value comes from bad ideas dropped before they cost anything, decisions made earlier, ideas that get a read at all, and smaller live tests because the shortlist is shorter.
- Lead with the number your approver already tracks, fill in the worksheet with your own numbers, then propose one pilot on a decision already on the calendar.
Which number should you lead with for each approver?
| Your team | Who signs off | The number to lead with |
|---|---|---|
| Fund analyst | PM or head of research | A consumer variable you estimated without data last quarter, and what being wrong on it cost |
| Product or growth team | VP of product or growth | Tests you couldn't run for lack of traffic, and features built before anyone checked demand |
| B2B GTM team | Head of sales or CRO | Messages and segments tried on the live list, and the accounts burned doing it |
| Enterprise marketing or product lead | CMO or GM | Concepts and creative that went to media or production without a read |
Where does the ROI of synthetic research come from?
Ideas dropped earlier. A feature, campaign or message that would have flopped gets dropped before engineering time, media or list reach is spent on it.
Earlier decisions. A read before the planning meeting can move a launch, a price change or a position forward.
A read on everything. Most teams test a fraction of their ideas and ship the rest on opinion.
Smaller live tests. If simulation narrows 12 options to 3, the live test has 3 arms instead of 12 and reaches a result sooner on the same traffic.
How do you estimate the ROI of synthetic research?
Fill in your own numbers. Leave a line blank if you can't defend it.
| Line | How to estimate |
|---|---|
| A. Decisions made last year without a read | Features, pricing changes, campaigns, outbound messages, model variables |
| B. Share of those that underperformed | Your post-mortems or retros |
| C. Average cost of one underperformer | Build time, media, discounting, burned accounts, or a wrong estimate |
| D. Value of deciding one week earlier | Weekly revenue of a comparable launch, or the window before a print |
| E. Cost per arm of a live test | Traffic share, list reach, or study cost per concept |
| F. Arms cut by screening first | Options you'd test minus options you'll keep |
| G. Cost of synthetic research | The quote you get |
Failures caught: A × B × C × the share a pre-read would catch (be conservative). Speed: weeks saved × D, for decisions where the read was on the critical path. Smaller tests: E × F per test. Subtract G. Present only the lines you can defend. A small number your approver believes gets further than a big one they question.
What goes in a one-page ROI memo?
A hypothetical example from a growth team:
- The decision. "We're choosing between four onboarding flows for the spring release."
- Today's process. "We'd normally test two of them, because the signup page doesn't have the traffic for four."
- The proposal. "Run a simulated read on all four, then A/B test the top two."
- The downside. "If the simulated read is wrong, the live test catches it."
- How we'll judge it. "We'll compare the simulated ranking with the live result and with what we'd have picked without it."
How do you answer objections to synthetic research?
"Isn't this just made-up data?" It's modeled data grounded in interviews with real people, labeled as simulated, and checked against live results on the decisions that matter.
"We already A/B test." Keep doing it where you have the traffic. This is for the tests you can't power, and for cutting arms before the ones you can.
"What if it's wrong?" That's why the pilot includes a live check on the shortlist.
How should you run the pilot?
Pick one decision in the next four to six weeks that you'd test or guess at anyway. Run the simulated read and the live check on the same options, then compare.
Want this run on your own question? Neon Blue's first study is free: start a free first study.
Common questions about the ROI of synthetic research
Should I pitch synthetic research as a replacement for A/B testing or surveys?
Pitch it as covering decisions you don't test today and shrinking the tests you do run. Replacement claims start the wrong argument.
How do I measure ROI after the pilot?
Compare the simulated read with the live result on the same options, and record whether it changed what you'd have done.
How does the case differ for a fund?
Lead with a model variable you estimated without data and what the miss cost, then pilot on an upcoming print.
How do I start a free first study?
Make the pilot decision your first study, so the main cost is your team's time. Neon Blue's first study is free. Start a free first study