Rewrite research brief front into three plain claims.

Lead with problem, industry today, and what we build in plain English;
keep North Star, muffin shop, and evidence tables underneath; refresh PDF.

docs/ALTERNATE_BUSINESS_PROPOSAL.md

@@ -89,16 +89,31 @@ We win if we are the shortest path from “AI can’t find / trust / correctly d
 
 Refocused 2026-10-01 so every section ladders to BUSINESS_PLAN North Star intent + concept Presence/Recommendability. Evidence from Localeze research and r/localseo; statistics are practitioner-reported, not independently replicated.
 
-**Research brief appended 2026-10-01; North Star preamble + plain-English muffin-shop section added same day** — verbose evidence synthesis below (section RESEARCH BRIEF). PDF export: [`docs/research-brief.pdf`](./research-brief.pdf). Does not replace North Star / Problem / Solution / Differentiators / Open questions; amends Capture with this date stamp only.
+**Research brief appended 2026-10-01; front rewritten same day into three plain claims (problem / industry today / what we build), with prior North Star + muffin-shop + evidence kept below** — verbose evidence synthesis below (section RESEARCH BRIEF). PDF export: [`docs/research-brief.pdf`](./research-brief.pdf). Does not replace North Star / Problem / Solution / Differentiators / Open questions; amends Capture with this date stamp only.
 
 ---
 
 ## RESEARCH BRIEF
 
 **Title:** GEOLOCAL Research Brief — evidence behind North Star Presence + Recommendability  
-**Date:** 2026-10-01  
+**Date:** 2026-10-01 (front rewritten same day for plain-spoken claims)  
 **Branch:** `planning-selfserve-audit`  
-**Relationship:** Append-only evidence layer for this alternate proposal. Does not replace the concept SoT ([`SELF_SERVE_AI_DISCOVERABILITY_CONCEPT.md`](./SELF_SERVE_AI_DISCOVERABILITY_CONCEPT.md)). Labels below: **practitioner-reported** (r/localseo / agency anecdotes), **vendor** (product marketing or vendor research), **primary study** (named methodology / published research). Flag **UNVERIFIED** where community claim or secondary paraphrase lacks a clean primary cite.
+**Relationship:** Append-only evidence layer for this alternate proposal. Does not replace the concept SoT ([`SELF_SERVE_AI_DISCOVERABILITY_CONCEPT.md`](./SELF_SERVE_AI_DISCOVERABILITY_CONCEPT.md)). Labels in the evidence sections below: **practitioner-reported**, **vendor**, **primary study**, **UNVERIFIED**.
+
+### Three claims (read this first)
+
+**1. What the problem is.**  
+Local business owners fix one listing — usually Google — and assume they are done. They are not. The same phone number, hours, and categories still sit wrong or missing on Yelp, Bing, Apple, and a long trail of directories fed by a few big data companies. When a customer asks an AI assistant for a bakery, a plumber, or a vet nearby, that assistant often pulls from those scattered copies. The shop may not appear at all. Or it appears with last year’s number. The owner never sees the miss. Customers lose trust. Being “good on Google” no longer means you are findable or correctly described wherever people discover local businesses — including AI answers.
+
+**2. What the industry looks like today.**  
+The local SEO world still lives mostly on Maps wins: Google Business Profile categories, reviews, photos, and occasional citation cleanup. Those moves can grow calls. Vendors sell listing pipes, completeness scores, and rank trackers. Almost none of that product story measures what AI assistants actually say — whether they find you, recommend you, or get the facts wrong. Studies show assistants are far pickier than the Google 3-Pack, disagree with each other, and often misstate details even when they “know” the business. Practitioners warn that big recurring listing platforms can hold your data hostage. Small shops get credit for doing the work themselves. AI visibility is rising fast with customers, but the tools they are offered still optimize yesterday’s scoreboard.
+
+**3. What we can build to solve it.**  
+We build a product that starts where the owner feels the pain: ask the major AI assistants what they say about this business, then show what is missing, wrong, or stale. That audit is the hook. Behind it, one action files corrections across the sources that actually feed answers — the umbrella data companies (Lane A) and the major claim surfaces like Google, Apple, Bing, and Yelp (Lane B) — so the owner does not fill out a dozen directory forms. We keep Google strong because it is still the proof hub and where many customers double-check. We measure success the only way that matches the North Star: is the business present where discovery happens, and would an assistant recommend it accurately if asked again?
+
+The sections below keep the North Star framing, the muffin-shop story, the research tables, and the detailed whys and hows. They are the receipts. The three claims above are the front door.
+
+---
 
 ### North Star (how to read this brief)