45 lines
3.5 KiB
Markdown
45 lines
3.5 KiB
Markdown
# DOP Homepage Blueprint (Draft v0.1 — collaborative, not yet committed)
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**Authors**: Qwen (structure) + Leonard (evidence grounding) · **Date**: 2026-08-10
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**Brand**: red-accent `#b8402c`, rigorous-engineering tone, no marketing fluff
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**Evidence rule**: every claim maps to Tier 1 (Verified) or Tier 2 (Indicative); human-approved.
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---
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## Section A — "Proof in Action" (replaces testimonials)
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*Headline: "We Don't Guess. We Verify."*
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Split visual:
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- **Left — Industry Standard**: generic "AI citation tool" dashboard, green checkmarks, red overlay showing the customer path leaking ("AI recommended a competitor because their schema was structured better").
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- **Right — DOP Standard**: a Tier 1 Verified finding with human analyst approval stamp.
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**Interactive element (slider/tab)** — anchored on the **Gilmore HVAC** live audit (`research/cold-audits/cold-audit-hvac-gilmore.md`):
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- Prompt shown: *"Best HVAC company in Cameron Park, CA"* (Perplexity/ChatGPT).
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- Leak shown: 3 conflicting phone numbers (page `(916) 884-6354` / schema `+1-530-290-5551` / snippet `(530) 344-4515`) + schema geo `Antelope, CA 95843` vs Cameron Park target.
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- Caption: "The AI doesn't know which number is real. Neither do the customers it sends elsewhere."
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(This is the Screenshot of Shame moment.)
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## Section B — "Three Domains of Integrity"
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1. **Customer Path Integrity** — diagram AI Search → SERP → Website → Conversion, leak markers at each handoff. Grounded in our audit gaps (Martel: zero machine-readable NAP = leak at AI Search).
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2. **AI Visibility Integrity (AEO)** — how LLMs parse local entities (schema, citations) vs how legacy SEO tools assume. Grounded in CPFD generic-schema finding.
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3. **Local Competitive Awareness (Clean Competitive Fuel)** — "Shadow competitors" ranking in AI but not in top-10 blue links. We refine fragmented public data (reviews, offers, hiring signals, AI mentions) into trustworthy local market intelligence. Grounded in Gordon Law: rank #1 at home, invisible for Cameron Park.
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## Section C — "Engagement Ladder" (the motion, radical transparency)
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- **Step 1 — Cold Audit (Layer 1a)**: Free. We find the leaks. You keep the report.
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- **Step 2 — Threat Diagnosis**: Paid fixed-fee. We quantify revenue impact of the Silent Customer Loss.
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- **Step 3 — Focused PoC**: We fix one critical leak **and make the business Agent-Ready** (structured facts AI systems can trust). You measure.
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- **Step 4 — Retainer**: Ongoing human-supervised, agent-assisted integrity + monthly measurement loop. *"We do not accept retainers without a successful PoC."*
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## Section D — "Objection Handling" FAQ
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- **Q: Why not just use an automated AI citation builder?**
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A: Automated tools generate Tier 2 (indicative) data; LLMs hallucinate or ignore unverified input. DOP relies on Tier 1 (verified) evidence, human-approved, so the AI actually trusts the entity.
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- **Q: How is this different from Bizl?**
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A: Bizl shows Tier-3 self-reported case studies. Our 5 live audits are observed, falsifiable evidence — we show our work.
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## Trust Anchor (site-wide footer/header)
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*"Every finding on this site was verified by a human analyst. AI agents draft the reports; humans verify the truth."*
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---
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## Open governance refinement (from Claude, pending Leonard incorporation)
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"If a proposed Tier 1 classification is rejected by human review, it defaults to Tier 2 unless the reviewer discards the finding entirely or requests more evidence." → Add to `docs/project-plan.md` §5 Governance before any client-facing launch.
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