diff --git a/docs/ALTERNATE_BUSINESS_PROPOSAL.md b/docs/ALTERNATE_BUSINESS_PROPOSAL.md index 50f8146..7e68867 100644 --- a/docs/ALTERNATE_BUSINESS_PROPOSAL.md +++ b/docs/ALTERNATE_BUSINESS_PROPOSAL.md @@ -89,29 +89,29 @@ 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; 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 appended 2026-10-01; three claims rewritten same day for zero-insider readers (problem / industry today / what we build + why viable), 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 (front rewritten same day for plain-spoken claims) +**Date:** 2026-10-01 (three claims rewritten same day for first-time / non-industry readers) **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 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. +A small business owner updates their Google listing — new phone number, new weekend hours — and thinks customers will find the right info everywhere. They will not. The same details still sit wrong or missing on Yelp, Bing, Apple Maps, and dozens of other online directories. A handful of big data companies quietly copy that stale information around the web. When someone asks an AI assistant — ChatGPT, Gemini, or anything like them — “where’s a good bakery near me?”, that assistant often pulls from those scattered, outdated copies. Sometimes the shop never shows up. Sometimes it shows up with last year’s number. The owner never sees the miss. Customers lose trust. Fixing one listing is not the same as being findable and accurately described wherever people discover local businesses today, including when they ask AI. **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. +Most of the “help your local business get found” industry still chases Google Maps wins: polish the Google business profile, collect reviews, post photos, clean up a few directory listings. That work can bring more phone calls from Google. Companies sell subscription tools that push your listing to many sites at once, score how “complete” your profile looks inside their own software, and track where you rank on a map. Almost none of those products answer the question owners now care about: what do AI assistants actually say about my business — do they find me, recommend me, and get the facts right? Outside research shows AI assistants name far fewer businesses than the short list of three Google shows at the top of many local searches, disagree with each other, and often get hours or phone numbers wrong even when they recognize the shop. People who work in this field warn that big listing subscriptions can lock up your data — stop paying and your listings may disappear. Small owners who do the work themselves usually get the credit for results. Customers are asking AI for local recommendations more than they did a year ago, but the tools for sale still mostly optimize last year’s game. -**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? +**3. What we can build to solve it — and why it can be a business.** +We build a product that starts with what the owner can feel: ask the major AI assistants what they say about this business, then show what is missing, wrong, or stale. That check is the reason to sign up. Behind it, one action files corrections on the places that actually feed those answers — the big data companies that fan out into many directories, and the major sites people and machines trust (Google, Apple, Bing, Yelp, and similar) — so the owner does not fill out a dozen forms. We still help them keep Google strong, because Google is where many customers double-check after an AI suggestion, and because a correct Google listing is useful proof when we ask other sites to update. We measure success simply: after the fixes, ask the same AI questions again — does the business show up, and is the description accurate? That is a viable business because owners already pay for listing tools that do not answer that question, AI recommendations are rising fast, and the gap between “I fixed Google” and “AI gets me right” is painful, visible, and mostly unserved. -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. +The sections below keep the longer framing, a muffin-shop story, the research tables, and the detailed whys and hows. They are the receipts. The three claims above are the front door for anyone new to this industry. --- diff --git a/docs/research-brief.pdf b/docs/research-brief.pdf index 5258ab8..f69441f 100644 Binary files a/docs/research-brief.pdf and b/docs/research-brief.pdf differ