AEO Audit

Audit a restaurant's online presence to understand why AI models do or don't recommend it. This checks the signals that feed into LLM training data and search-augmented responses.

Arguments

The user provides a restaurant name and optionally a URL:

• /aeo-audit "Sabai Fine Thai" — searches for the business, then audits
• /aeo-audit https://sabaifinethai.com — audits starting from the URL

Your task

Step 1: Find the business

Search the web for the restaurant to find:

• Official website URL
• Google Maps / Google Business Profile listing
• Major review platform listings (TripAdvisor, Yelp, Burpple, HungryGoWhere, etc.)
• Social media presence (Instagram, Facebook)

Step 2: Website technical audit

Fetch the restaurant's website and check:

1. Crawlability: Can search engines and AI crawlers access the content? Check for:

   • robots.txt restrictions (especially blocks on GPTBot, ClaudeBot, Google-Extended, PerplexityBot)
   • JavaScript-only rendering (content invisible without JS execution)
   • Meta robots noindex/nofollow tags

2. Structured data: Look for Schema.org markup:

   • Restaurant or LocalBusiness schema
   • Menu schema with item names and prices
   • OpeningHoursSpecification
   • AggregateRating and Review markup
   • address, geo, telephone properties

3. Content signals: What text does the page surface?

   • Restaurant name, cuisine type, location mentioned in headers/title
   • Menu items described in crawlable text (not just images/PDFs)
   • Unique selling points visible in first 500 words
   • About page with story, chef background, sourcing

4. Technical health:

   • Page load (is the site up?)
   • Mobile meta viewport tag
   • HTTPS
   • Canonical URL

Step 3: Google Business Profile check

Search for the restaurant on Google and report:

• Rating and review count
• Business status (open/closed)
• Listed categories
• Photos count
• Recent reviews sentiment
• Completeness of the listing (hours, menu, description)

Step 4: Platform presence

Check major listing platforms:

• TripAdvisor ranking and review count
• Yelp presence
• Local platforms (Burpple, HungryGoWhere for Singapore; equivalent for other cities)
• Instagram hashtag volume

Step 5: Competitor benchmarking

If the user provided a category (e.g., "Thai restaurants in Singapore"), identify the top 3-5 competitors that AI models DO recommend (from the research database if available) and note what they do differently online.

Step 6: Generate report

Write a report at data/probes/<business_name>/audit.md with:

1. Visibility Score: Rate 1-10 based on overall discoverability
2. What AI models see: Summary of crawlable content
3. What's missing: Gaps in structured data, content, or platform presence
4. Intervention hierarchy (ordered by effort/impact):
   • Quick wins (structured data, Google Business Profile optimization)
   • Medium effort (content additions, platform listings)
   • Long-term (review acquisition, content strategy, PR)
5. Competitor comparison table

Report tone

Factual, not salesy. Present findings as data, not pitches. "Your site blocks GPTBot in robots.txt" not "You're missing out on AI traffic!"