Services FAQ
AI visibility services FAQ.
These answers define how the service layers work together: technical access, entity clarity, answer coverage, proof sources, and market measurement.
What AI visibility services does Market Disruptors offer?
Market Disruptors offers AI visibility services across foundation, citation, and scale layers, including AI SEO, Answer Engine Optimization, Generative Engine Optimization, schema markup, entity SEO, AI citation building, Share of Model measurement, and AI Discovery Surface builds for local service businesses.
Which AI visibility service should a local business start with?
Most local businesses should start with an AI Visibility Audit or AI SEO foundation work. The audit shows whether AI systems can find, understand, verify, and recommend the business before deeper citation, content, or market-share work begins.
How are AEO, GEO, and AI SEO different?
AI SEO improves the technical and content foundation that helps AI systems access and understand a business. Answer Engine Optimization structures direct answers for buyer questions. Generative Engine Optimization builds the entity, authority, and proof signals that help AI models include the business in generated recommendations.
Do you only work with local service businesses?
Market Disruptors specializes in local and multi-location service businesses, including home services, legal, dental, med spa, health, longevity, and other appointment or call-driven categories. The same AI visibility framework can support broader service brands when local proof and entity clarity matter.
How does an AI Discovery Surface fit with these services?
An AI Discovery Surface is the dedicated AI-readable proof layer built on the client's domain. It connects services, locations, business facts, evidence, FAQs, and machine-readable files so platforms like ChatGPT, Perplexity, Google AI, and Meta AI have a clearer source to evaluate.
How do you measure whether AI visibility is improving?
AI visibility is measured through prompt coverage, citation presence, entity consistency, crawlability, answer inclusion, competitor comparison, and Share of Model. The goal is to understand whether AI systems are naming, citing, and recommending the business more often in buyer-intent prompts.