Case Studies
Technical and applied studies of AI representation, evidence quality, measurement, and answer alignment.
Inside Kojable’s DataForSEO integration for fan-out queries, AI Search Volume, keyword discovery, topic clustering, citations and AI answer alignment.
Answers: How does Kojable use DataForSEO fan-out queries, keyword intelligence and AI answer observations without automatically turning every retrieval query into a content target?
View case studyAn engineering case study on how Kojable handled market availability, sparse AI data, relevance filtering, provider costs, partial failures and citation confidence in its DataForSEO LLM Mentions integration.
Answers: How can DataForSEO LLM Mentions data be made reliable, cost-controlled and honest enough for production AI visibility monitoring?
View case studyHow Target Visibility Rate measures whether a company appears when relevant buyers ask high-intent questions across AI systems.
Answers: Do we show up when our ideal buyer asks an AI?
View case studyHow real user questions revealed substantial differences in company representation across Claude, Gemini, ChatGPT, and Perplexity.
Answers: Does our brand visibility change across different AI models?
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