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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.

Evidence Tier Assignment Authority

Agents may propose an evidence tier for a finding, but the final evidence tier used in any client-facing report must be approved by a human reviewer during Version 1.

A finding may only be classified as Verified Evidence when it is supported by concrete, current, observable, timestamped, or instrument-backed evidence.

If a finding does not clearly meet the standard for Verified Evidence, it defaults to Indicative Evidence until a human reviewer confirms otherwise.

Ambiguous findings must not be presented as confirmed customer loss.

If an agent proposes a finding as Verified Evidence and the human reviewer rejects that classification, the finding defaults to Indicative Evidence unless the reviewer discards the finding entirely or requests additional evidence.

Examples:

  • A currently visible wrong phone number on a verified business profile may qualify as Verified Evidence.
  • A broken booking link observed and timestamped during review may qualify as Verified Evidence.
  • A stale or unconfirmed citation mismatch defaults to Indicative Evidence until confirmed.
  • Absence from sampled AI answers is Indicative Evidence.
  • Agent-reported findings without supporting artifacts are not sufficient for Verified Evidence.