Add value creation model and evidence-tier taxonomy

2026-07-24 04:10:52 +00:00
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+# Value Creation Model
+
+## Purpose
+
+Explain how the company creates measurable or directional value for local service businesses.
+
+## Core Value Thesis
+
+The company creates value by reducing Silent Customer Loss through continuous monitoring, diagnosis, prioritization, and approved low-risk optimization of digital pathways that affect discovery, trust, and customer action.
+
+## Value Categories
+
+### Customer Path Leakage
+
+Customer Path Leakage occurs when a customer has interest or intent but fails to contact, book, visit, or otherwise engage the business because of digital friction.
+
+This category often produces **verified evidence** because the issue can be tied to a concrete defect, timestamp, platform state, or measurable artifact.
+
+### Discovery Failure
+
+Discovery Failure occurs when a potential customer never meaningfully encounters the business because customers, search engines, or AI systems do not find, understand, surface, or accurately represent it.
+
+This category often produces **indicative evidence** because absence or weak representation in search or AI-assisted discovery can be sampled and demonstrated, but not always proven as a direct lost customer.
+
+## Evidence Tiers
+
+### Tier 1: Verified Evidence
+
+Verified Evidence is based on concrete, timestamped, observable, or instrument-backed findings.
+
+**Examples:**
+- Wrong phone number
+- Incorrect business hours
+- Broken booking link
+- Broken contact form
+- Incorrect listing data
+- Indexing problem
+- Metadata problem
+- Canonical tag issue
+- Missing or incorrect Google Business Profile information
+
+**Reporting standard:**
+
+Verified Evidence may be presented as a confirmed issue.
+
+### Tier 2: Indicative Evidence
+
+Indicative Evidence is based on sampled, directional, or probabilistic findings that suggest risk or opportunity but do not prove direct customer loss.
+
+**Examples:**
+- AI answer absence
+- AI misrepresentation
+- Weak entity clarity
+- Inconsistent service descriptions
+- Thin FAQ coverage
+- Missing structured data
+- Competitors appearing more consistently in AI answer samples
+- Weak local discovery signals
+
+**Reporting standard:**
+
+Indicative Evidence must be presented as directional risk or opportunity, not as confirmed customer loss.
+
+## Reporting Principle
+
+Reports must distinguish between confirmed issues and directional risks.
+
+The company should not overstate indicative findings as proven customer loss.
+
+## Before/After Proof
+
+Customer Path Leakage may support stronger before/after proof.
+
+Discovery Failure may support directional before/after comparison, but should be labeled as sampled or indicative when appropriate.