Question mining
Build representative prompt sets across category, comparison, brand, support, and local intents.
Laboratory · 03
The Conversational Search Laboratory is our research practice for Answer Engine Optimization (AEO): the question-led content structures, FAQ schema, passage design, and entity scoping that allow AI assistants and voice interfaces to extract a clean, attributable answer. It tests how Google AI Overviews, ChatGPT, Perplexity, Alexa, and Siri parse, summarize, and cite branded answers across informational and local queries.
Focus areas
Methodology
Build representative prompt sets across category, comparison, brand, support, and local intents.
Design atomic answer blocks and FAQ structures that match the way assistants extract content.
Probe ChatGPT, Perplexity, Google AI Overviews, Gemini, and Claude with the same prompt sets to compare cited sources.
Active experiments
Measuring the effect of answer length and structure on extraction into AI assistant responses.
Studying how depth of FAQ coverage influences whether assistants recommend the brand as an authoritative source.
Examining how local services optimize structured answers for assistant-driven local queries.
Applied to
FAQ
Start with a diagnostic Organic Visibility Audit to see how machines currently perceive, understand, and retrieve your business.
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