Case Study — Phoenix Roofer (From zero AI mentions to the answer AI gives Phoenix homeowners in 60 days)

Core Messaging / Positioning

Hero: "From zero AI mentions to the answer AI gives Phoenix homeowners in 60 days."
Problem framing (Silent Customer Loss angle): "A trusted roofer being skipped by every AI engine that homeowners now ask first." A respected 12-year Phoenix contractor with "hundreds of completed jobs and a loyal referral base" was invisible because "most people asked ChatGPT for a roofer before they ever called one."
Done-for-you promise: "A step-by-step plan our team executed while the owner ran the business." / "From the day the business signed up for Stay Found, our team handled everything."
Result headline: "Score went from 16 to 66. Calls tripled. In 90 days."
Humanized outcome: "The leads are warmer and they trust us before they even call. That changed how we sell."

"12 years in business" with "hundreds of completed jobs."
"zero AI mentions → answer AI gives Phoenix homeowners in 60 days" (60-day hero window).
AI Visibility Score "went from 16 to 66" (headline).
"Calls tripled" (headline).
"In 90 days."
Source caveat: "Every number below is from the business's Bizl dashboard, 90 days after starting Stay Found."
Owner quote on seasonality: "Roofing is seasonal and the good jobs are big, so missing one storm season really hurts. We used to rely on knocking doors after every hail storm."
Flag (evidence quality): Figures (16→66, calls tripled) are unsourced vendor-dashboard claims — Tier 3, no independent verification, single anonymous client. "60 days" in hero vs "90 days" measurement window are slightly inconsistent.
Flag: "First-page AI recommendations," "top AI engines," prompt-gap stats referenced by headers but figures themselves are not enumerated in this scrape.

Name-drops the paid product: "Stay Found" (Bizl's managed subscription service).
Not pricing specific on this page; entry point is the free audit.

Step-by-step timeline is listed in headers but body specifics are minimal in the scrape: audit → "step-by-step plan" team executes → "while the owner ran the business" → 90-day dashboard results → "Beyond the numbers" qualitative wins → results across other industries.
CTA flow: free audit (4 minutes) → "Our team handles everything after."

Narrative arc of customer-path loss: homeowner behavior shift (ask AI first) → business invisible → structured fix → measured rebound.
Strong quantified headline pair (score + calls) with a dramatic delta (16→66).
Owner voice / emotional proof: warm leads, pre-sold trust, seasonal revenue at risk — makes abstract AI visibility tangible.
"Beyond the numbers" section humanizes results (conversion + relatability).
Ends with "Your business could be our next case study" — aspirational social proof.

Silent Customer Loss: Page is a textbook articulation of it — a good, established business losing inbound solely because AI engines can't surface it. DOP can reuse this framing: "you're not losing because of quality, you're losing because AI can't find you."
Evidence quality: Result figures are unsourced vendor-dashboard claims (single anonymous client, no third-party validation, inner-platform metrics) → Tier 3. DOP differentiator: measured, verifiable before/after audits with independent evidence.
Human supervision vs black-box: Explicitly fully-managed/done-for-you ("our team handled everything," "without the owner lifting a finger"). DOP's human-supervised + agent-assisted model is a direct contrast — same scope but transparent methods and human approval checkpoints.
PoC-style entry: Starts with a free AI visibility audit (measured, specific: 5 engines, citation gaps, schema status, competitor searches) then escalates to paid managed service. Same free-scan→paid shape as DOP's Cold Audit→PoC→Retainer.
Conversion patterns: quantified delta headline, owner testimonial, seasonal-revenue risk framing, aspirational case-study close, free-audit CTA tie-in.