🔎 AI Search Visibility Auditor

Purpose

Run a diagnostic audit of a roofing contractor's online presence against the way modern AI assistants rank and cite local businesses. Produces a prioritized remediation plan covering authority signals, pricing transparency, local/climate specificity, and structured data — the four levers that determine whether a roofer gets mentioned when a homeowner asks an AI "who should I hire to fix my roof near me?"

When to Use

• Annual marketing plan review, or whenever a contractor notices declining inbound leads from organic channels
• When a competitor starts showing up in AI-assistant responses and the contractor does not
• Before investing in paid search or SEO, to fix foundational visibility first
• After a website redesign or domain migration
• To produce a before/after measurement baseline when rolling out AI-search-focused content

Required Input

Provide the following:

1. Company basics — Company name, primary service area (counties/cities), website URL, Google Business Profile URL, phone, physical address, years in business
2. Top service categories — The 5–8 core services the contractor wants to be cited for (e.g., storm damage repair, insurance claim support, standing seam metal, flat roof replacement)
3. Climate & region detail — State, climate zone, common local weather events (hail, hurricane, wildfire, snow load), and any regional code amendments
4. Current content inventory — List of existing pages or a sample of 5–10 URLs to audit; blog cadence; whether they have FAQ/How-To pages
5. Credentials & authority assets — Licenses, manufacturer certifications (GAF Master Elite, CertainTeed SELECT ShingleMaster, Owens Corning Platinum), insurance certificates, BBB rating, Google review count and average, any awards or press mentions
6. Competitors to benchmark — 2–4 local competitors the contractor is losing visibility to

Instructions

You are running an AI-search-visibility audit. Your output is a diagnostic report plus a prioritized 90-day remediation plan, written for a marketing manager or owner-operator, not a technical SEO specialist.

Before you start:

• Load config.yml from the repo root for company tone, brand voice, and any prior audits on file
• Reference knowledge-base/industry-overview.md for current AI adoption stats
• Reference knowledge-base/terminology/ to calibrate technical depth for each service category
• Cross-reference knowledge-base/tools-ecosystem/ai-tools-landscape.md for the current tool set that contractors should be tracking

Audit framework — four levers:

Lever 1: Authority & Trust Consistency

Check these items across the website, Google Business Profile, Facebook page, Yelp, and any directory listings:

• Business name matches exactly in every location (no "Roofing Co." vs. "Roofing Company, LLC" mismatches)
• Address, phone, hours, and service area identical everywhere
• Credentials published on the site with supporting images (license cards, cert certificates, insurance COI)
• Owner/crew bios with real names and years of experience
• Review count and recency across Google, BBB, Nextdoor, Angi — AI assistants weight recency, not just totals
• Schema markup: LocalBusiness, RoofingContractor, AggregateRating, FAQPage, HowTo on relevant pages

Lever 2: Pricing Transparency

AI assistants reward contractors who publish ranges over those who hide pricing. Audit whether the contractor has:

• A dedicated pricing page with ranges by roof size, material, and complexity tier
• Typical project cost examples with enough specificity to anchor homeowner expectations
• Tariff/market adjustment notes (cross-reference the tariff-price-adjuster skill output if recent)
• Financing options and payment plans listed plainly
• A one-sentence "what drives cost up or down" explainer per material type

Lever 3: Local & Climate Specificity

Generic contractor content does not get cited. Audit whether pages include:

• Geographic qualifiers in headings (city/county/zip), not just in metadata
• Climate-specific material recommendations (e.g., Class 4 impact shingles for hail-prone zones, Cool Roof ratings for hot-arid regions)
• Local code citations (wind rating requirements, ice-and-water-shield code, historic district rules)
• Neighborhood/subdivision references with before/after project photos when available
• Storm-event microcontent published within 48 hours of local major weather events

Lever 4: Structured, AI-Friendly Content

AI assistants pull 150–300 word answer-shaped blocks. Audit whether content is:

• Chunked with descriptive H2/H3 headings that restate the question a homeowner would ask
• Answer-first in each section (lead with the answer, then the caveats)
• Supported by FAQ schema with 5–10 Q&As per service page
• Rich with specific numbers (years, percentages, square footage, lifespan)
• Free of thin/duplicate pages (every service page 600+ words, unique per city if multi-city)
• Linked to original research or proprietary data when possible (e.g., "average hail claim in [county] in 2025")

Diagnostic output (audit report):

1. Executive Summary

• One-paragraph overall AI-visibility grade (A–F) with rationale
• Top 3 quick wins (items that can be fixed in under 2 weeks)
• Top 3 structural issues (items requiring a 30–90 day project)
• Estimated AI-visibility uplift if all recommendations are implemented

2. Scorecard Table

3. Findings by Lever

For each lever, produce:

• What's working
• What's missing or inconsistent (with specific URL or location)
• Competitor benchmark (how the benchmarked competitors handle this)
• Concrete fix recommendation

4. Prompt Battery for Ongoing Monitoring

Deliver a set of 10–15 test prompts the contractor can run monthly against ChatGPT, Claude, Gemini, and Perplexity to track their citation frequency. Examples to draft:

• "Best roofing contractor in [city] for hail damage"
• "Who repairs [material type] in [region]"
• "[Carrier name] insurance claim roofer [city]"
• "Roof replacement cost [zip] 2026"

Instruct the contractor to log, for each prompt: whether they appear, which competitors appear, what supporting detail is cited about each.

5. 90-Day Remediation Plan

6. Measurement Plan

• Baseline the 10–15 monitoring prompts before any changes
• Re-run monthly and track AI Share of Voice (% of prompts returning your company)
• Pair with standard lead source tracking in CRM to connect visibility to leads

Output requirements:

• Written for a non-technical owner-operator — translate jargon (NAP, schema, E-E-A-T) on first use
• Every finding references a specific URL, screenshot callout, or competitor example
• The 90-day plan sequences quick wins first to build momentum
• Saved to outputs/audits/{company-slug}-ai-visibility-audit-{YYYY-MM}.md if the user confirms
• Recommend companion skills: estimate-builder for pricing-page content, tariff-price-adjuster for pricing transparency copy, follow-up-sequence for review solicitation

Example Output

[This section will be populated by the eval system with a reference example. Run with sample input to anchor format.]