White Papers
Original research on how AI systems decide which brands to recommend — and what that means for visibility, sentiment, and discovery in the AI era.
2 papers
August 202618 min read
The Personalization Gap: Account History and Brand Recommendations in Generative AI
A controlled study of account history and AI brand recommendations, using identical questions across neutral sessions and history-primed accounts.
By Cassie Wilson Clark and Joao da Silva
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May 202642 min read
Beyond Knowledge Graph Strength: what 14,140 LLM queries revealed about brand visibility in generative AI
A controlled 14,140-run study of 12 athletic apparel brands across 5 large language models shows that Knowledge Graph strength predicts brand surfacing direction within a category, but carries no signal across category boundaries. The variable that does the work is Category Coding: the KG description field combined with the category-aligned third-party content corpus.
By Maryanna Franco and João da Silva
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