R3 — Maximise self-relevance in the output: show the user's own number, not "people like you average X"; the personalization mechanism is the best-evidenced lever in the brief

Rule: Design the tool's output so it is maximally self-relevant: surface the user's own number computed from the user's own inputs, not a generic "average customer like you sees X" framing.

Why: Personalization is the best-evidenced mechanism in the brief — Symons-Johnson 1997 (Symons & Johnson (1997) meta-analysis — self-reference effect: information encoded in relation to the self is better recalled; the self is a well-developed elaboration construct), Svensson 2022 (Svensson et al. (2022), Quarterly Journal of Experimental Psychology — self-relevance modulates attentional processing (narrowing of visual attention / executive control) even for arbitrary stimuli), Tam-Ho 2006 (Tam & Ho (2006), Information Systems Research — content relevance + self-reference mediate the effect of web personalization on attention, processing, decisions; users clicked self-referent offers far more), De Keyzer 2025 (De Keyzer et al. (2025), Journal of Advertising — meta-analysis: actual personalization outperforms imagined / scenario personalization via stronger self-referencing and perceived relevance) — actual personalization (computed from real input) outperforms hypothetical / scenario personalization via stronger self-referencing.

How to apply:

• Result page leads with "Your estimate: $X," not "Customers your size typically see $X."
• When confidence intervals are appropriate (per the calculator brief's R7 — Treat every public number on a client site as an anchor; design accordingly), still anchor on the user's number first, range second.
• Avoid hypothetical / second-person-plural framings that dilute self-reference.