Generative AI / LLM Search Console
Created an integrated generative AI tracker and search console to monitor how LLMs utilize site content; track brand and competitive visibility; report website engagement; and analyze query fan-outs for directional and optimization insights.
The Problem
Several clients needed to know how different generative AI platforms utilized their content, how visible they were, if popular LLMs were sending them traffic, and what visitors did once they reached their websites.
The Solution
- Built an integrated AI Search Console utilizing Looker Studio and BigQuery to combine large-scale datasets, visualizing key performance indicators including indexation, bot crawls, visibility tracking, and website engagement.
- Integrated a generative AI-focused server access log database to create a maintained historical record of content access by LLMs and paired with log analysis to understand which content is utilized and favored.
- Created a generative AI tracker in Python, Google Colab, and Google BigQuery to track probable mentions and citations across ChatGPT, Perplexity, Gemini, AI Overviews, and AI Mode for directional insights.
- Constructed a benchmarking framework to monitor brand and competitor citations and share-of-voice, as well as industry citations and share-of-voice for indirect visibility, traffic, and leads.
- Included query fan-out analysis to derive directional insights for GEO, optimizing content for citation preference and AI-driven discovery.
The Results
Screenshots coming soon.
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