Listen: Beyond Rank Tracking: Analyzing Brand Perceptions Through Language Model Association Networks
The DEJAN methodology uses large language models to analyze brand perception and semantic associations, moving beyond traditional keyword rank tracking.
Transcript
For years, search engine optimization, or SEO, has relied on tracking keyword rankings to measure online visibility. But as search engines evolve, traditional rank tracking is losing its edge. Today’s search engines are driven by large language models, or LLMs. These models don't just match keywords; they understand user intent, relationships, and context.
This is where the DEJAN methodology comes in. Instead of just monitoring where a website ranks, this approach directly queries LLMs to map how a brand is actually perceived. By asking the AI what concepts it associates with a brand, and what brands it associates with a concept, we can build a detailed map of brand associations.
Tracking these AI-generated associations over time reveals how a brand's positioning shifts, who its real competitors are, and where new opportunities lie. It moves us past simple keyword matching and into a deeper understanding of the entire semantic landscape. Ultimately, it helps businesses manage their presence in a world where search is defined by meaning, not just ranking.