A repeatable AI visibility audit for local businesses: define entities, test prompts, verify facts, track sources, and log changes without confusing visibility with revenue.
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How local businesses can align their legal name, trade name, locations, and services across site and profiles to reduce confusion and keep updates organized.
Read itPractical ways local businesses can make their sites clearer to AI systems by stating services, locations, ownership, and policies in plain, consistent formats.
Read itA practical way to test AI answers about your business, spot factual mistakes, and track accuracy with a repeatable prompt, source checks, and a simple log.
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Use the last ten customer conversations to build a practical FAQ, align staff on answers, and publish it where customers can actually find it.
Read itHow to make your business name, address, services, and contact details easier for AI systems and customers to trust across your site and listings.
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In 2022 our engineering team made a bet on structured data. Three years later, that bet is the foundation of every Revenue Engine install. Here's what we did, and what we learned.
Read itWe track LLM visibility for hundreds of businesses. The four major models almost never agree. The disagreement is the point — and it's how you know what to fix.
Read itOver the back half of 2025 we ran 14 schema markup variants across a controlled set of client sites and measured the ChatGPT recommendation rate. The results changed how we ship schema.
Read itThe exact 12-step checklist we run with new clients to get them cited in ChatGPT, Perplexity, and Google's AI Overviews inside one quarter — including the structured-data audit, GBP fixes, and content gaps to close first.