The segments – and how Arc was built

Arc is deliberately layered. The foundation is published segmentation science – More in Common's seven British segments, credited above, used exactly as published and never altered. On top sits the GBNH archetype lens: eight energy-specific motivational types developed for the book Green But Not Heard, from years inside the industry watching who buys, who refuses, and why the marketing misses. The two lenses answer different questions – who someone is in Britain, and why they would buy – and Arc keeps them separate on purpose.

The layer that makes it more than a framework is first-party research. The archetypes are being validated and sized through structured consumer studies on Prolific via MyGreenPrint, with further evidence flowing from the GBNH venture sites across EVs, heat pumps, and solar. Survey waves feed the engine's evidence grades; nothing joins the scoring tables without cross-examination – every table went to five independent AI models with a fixed challenge prompt before freezing, and the record of what they changed is on the method page.

The method is published; the recipe is not. What every page shows: the sources, the dates, the evidence states, the working behind each result. What stays in the engine: the full weight tables and blend constants. Enough transparency to be checked, not enough to be photocopied.

The scoring is deterministic – the same inputs produce the same result, every time, with the working shown. AI sits above the engine, never inside it: it explains, adapts, and drafts from evidence packs the engine and the research supply. AI dresses the evidence; it never invents it. Where a page uses AI, it says so, and shows its inputs.

There are two routes into the Persona Builder. Describe a customer in plain words and a deterministic extractor reads what it can hear – showing each phrase it matched, guess by guess, for you to correct. Or skip the description and set the pickers directly. Either way, only what you confirm is scored, and anything unset simply says less rather than pretending to know.