{rows.map((a) => {
const v = S.by[a.key];
const tone = v === hi ? "hi" : v === lo ? "lo" : "mid";
return (
{a.label}{v}
);
})}
Spread of {hi - lo} pts across accounts — {hi - lo <= 6 ? "merchandise it everywhere; the read barely moves." : "weight it to the accounts where it over-indexes."}
);
}
function SpreadCard({ franchise }) {
const F = FRANCHISES[franchise];
if (!F) return null;
const sorted = F.makeups.slice().sort((a, b) => b.score - a.score);
const hi = sorted[0].score, lo = sorted[sorted.length - 1].score;
const cut = sorted.filter((m) => m.lean === "weak");
const fv = window.VERBATIM ? window.VERBATIM.BY_FRANCHISE[franchise] : null;
return (
Every retailer cut sits at or above the overall baseline ({OVERALL_ES.toFixed(3)}) — small boutiques and Anthropologie segment hardest. The pattern is consistent, not a one-segment artifact.
);
}
function SyntheticCard({ franchise }) {
const F = FRANCHISES[franchise];
const P = SYNTH[franchise];
if (!F || !P) return null;
const mid = Math.round((F.range[0] + F.range[1]) / 2);
const score = clamp(mid + P.effect, 30, 85);
const v = (x) => x === "up" ? "▲" : x === "down" ? "▼" : "—";
return (
Synthetic · model estimate, not fielded
untested make-up
{P.name}
{P.treat}
{score}est.
likely {clamp(score - P.band, 30, 85)}–{clamp(score + P.band, 30, 85)} · vs {F.label} field {F.range[0]}–{F.range[1]}
{P.attrs.map((a) => (
{v(a.v)}{a.k}{a.t}
))}
“{P.quote}”synthetic respondent
Basis · {P.basis}
);
}
// =====================================================================
// answerFor — pick the shape, return { node, confidence, sources }
// =====================================================================
function answerFor(f, preset) {
const m = meta(f);
const fr = m.franchise && FRANCHISES[m.franchise] ? m.franchise
: (m.kind === "design" ? "hawk" : "hawk");
const k = preset.kind;
if (k === "compare") {
const style = (m.kind === "design" && FRANCHISES[m.franchise] && STYLES[FRANCHISES[m.franchise].leader])
? FRANCHISES[m.franchise].leader : "Hawk Twill";
return {
text: `Reading ${style} across the four accounts you sell into:`,
node: ,
confidence: "High", sources: ["Buy-consideration × account (O4)", "Product ratings"],
};
}
if (k === "spread") {
return {
text: `Here's the full ${FRANCHISES[fr].label} make-up ladder, ranked:`,
node: ,
confidence: "High", sources: ["Within-franchise ratings (O3)", "Open-text synthesis"],
};
}
if (k === "synthetic") {
return {
text: `Modeling a ${FRANCHISES[fr].label} make-up we haven't fielded — estimated from the tested range plus what the line has taught us about treatments:`,
node: ,
confidence: "Synthetic", sources: ["Treatment priors", "Franchise score distribution"],
};
}
if (k === "acctHeroes") {
const accKey = m.account ? accKeyFromName(m.account) : null;
if (accKey === "anthro") return { text: "Anthropologie reads the line warmly (avg 58). Heroes: Hawk Twill (77), Championship (72), Sprinter Reflect (70), with Sprinter Satin over-indexing (69). Floor: Clora Mule (30), rejected as firmly as everywhere else.", confidence: "High", sources: ["Anthropologie shoppers (O4)"] };
if (accKey === "fp") return { text: "Free People tracks Anthropologie closely (avg 57). Heroes: Hawk Twill (76), Sprinter Reflect (71), Championship (71), Delta Tonal (70). Floor: Clora Mule (33) and the Celestra quilts (40).", confidence: "High", sources: ["Free People shoppers (O4)"] };
if (accKey === "dept") return { text: "Department-store shoppers are the toughest crowd (avg 56) — your conservative sell-in read. Same heroes hold (Hawk Twill 73, Sprinter Reflect 68, Championship 68) but the floor is harsher: Trakstar Flex (38), Clora Mule (34).", confidence: "High", sources: ["Department-store shoppers (O4)"] };
if (accKey === "gola") return { text: "Gola consumers are the enthusiast ceiling (avg 61) — treat as a high read, not a forecast. Hawk Twill hits 82 here (highest in the study); loyalty lifts Delta (73) and Elan (72). Even this warm crowd puts Clora Mule last (39).", confidence: "High", sources: ["Gola affinity (O4)"] };
return {
text: "Two verdicts hold across every account: Hawk Twill is the universal hero (#1 for all four) and the Clora Mule is the universal floor (last in all four). Generosity ranks Gola (61) > Anthropologie (58) > Free People (57) > Dept. stores (56).",
node: ,
confidence: "High", sources: ["Cross-account agreement (O4)"],
};
}
if (k === "segHold") {
return {
text: "Yes — the segmentation holds across the retailer cuts. Every account-relevant cut sits at or above the overall baseline:",
node: ,
confidence: "Moderate", sources: ["Effect size × retailer shopped"],
};
}
// free-text / fallback — ground it in the pinned finding
return {
text: `On "${f.statement}" — ${trimProse(f.prose)} Want me to read it across accounts, ladder the make-ups, or model an untested one?`,
confidence: f.sig === "high" ? "High" : "Moderate",
sources: [f.lensLabel || "This finding"],
};
}
function trimProse(p) {
if (!p) return "";
const first = String(p).split(/(?<=\.)\s/)[0];
return first.length > 220 ? first.slice(0, 217) + "…" : first;
}
function greetingFor(f) {
const m = meta(f);
if (m.kind === "design" && FRANCHISES[m.franchise]) {
return `Pinned the ${FRANCHISES[m.franchise].label} read. Ask me to compare its hero across accounts, ladder the make-ups, or spin up synthetic research on one you haven't fielded.`;
}
if (m.kind === "account") {
return `Pinned this account read. I can compare a style across all four accounts, pull this account's heroes and floors, or model an untested make-up.`;
}
return `Pinned "${f.statement}". Ask me to compare a style across accounts, dig into a franchise, or model an untested make-up.`;
}
window.MakerLabCtx = { presetsFor, answerFor, greetingFor, meta };
})();
})
}