From RoastIQ score to buyer objection: how context makes synthetic interviews sharper

Why BuyerLens requires a RoastIQ result

BuyerLens never runs without a RoastIQ result. This is a deliberate architectural decision, not a limitation.

Generic synthetic interviews — where you describe a product and ask AI personas what they think — produce generic responses. The personas have no specific creative to react to, no diagnostic data to ground their objections, and no evidence timeline to reference.

BuyerLens starts differently. It starts with evidence.

What context flows from RoastIQ

When a BuyerLens study opens from a RoastIQ result, the following context is automatically passed:

1. The 5 KPI scores and verdict — the persona knows the creative scored 71 with a Sharpen verdict
2. The weak KPI and its score — the persona knows Sell Proposition scored 63
3. The evidence timeline — the persona knows the product pour arrives at 18 seconds
4. The platform and category — the persona knows this is an Instagram Reels ad for FMCG in the UK

This context shapes every interview question and every response.

How context changes interview quality

Without context, a generic question like What do you think of this ad? produces a generic answer: It looks nice but I would not buy it.

With RoastIQ context, the same persona answers differently because the interview script is different. The question becomes: The product benefit does not appear until 18 seconds. As an FMCG buyer on Instagram Reels, at what point did you consider scrolling past?

The response is specific: By second 5. The visuals are strong but there is no personal hook before the halfway point. I have already decided whether I am interested by then.

The difference is not in the AI model. It is in the context.

The study design flow

BuyerLens uses three setup steps, each informed by RoastIQ:

1. Audience — Pre-filled from the RoastIQ category, platform, and region. Editable.
2. Participants — The user chooses 1-15 synthetic buyers. Personality traits (OCEAN) shape response patterns.
3. Goal — Pre-filled from the weak KPI evidence. Can be customized or inferred from RoastIQ.

The Infer from RoastIQ button on both Audience and Goal auto-fills from the diagnostic data. The user can accept, edit, or replace these defaults.

Source enrichment

For even sharper interviews, users can upload source documents: creative briefs, past research, customer reviews, landing pages. These documents are retrieved at response time, grounding the synthetic buyer in the specific brand context.

Without sources, BuyerLens gives directional objections. With sources, the objections reference the brand actual positioning, competitive context, and audience expectations.

The principle

Context is not a nice-to-have. It is the difference between a generic AI output and a useful diagnostic input. BuyerLens exists to be the second layer after RoastIQ — not a standalone tool.