Visable in LLM
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LLM Pilot
LLM Visibility Pilot
A structured pilot program to measure and improve how large language models
understand, display and recommend your e-commerce products.
About the pilot
This pilot consists of three phases:
1) Onboarding & baseline measurement,
2) Analysis and improvement advice,
3) Joint evaluation and next steps.
Participants join a closed group where we run the pilot together,
share insights, and learn what actually drives visibility in AI-driven
shopping experiences.
Baseline measurement
We measure how large language models (LLMs) currently interpret your product data,
how they describe your assortment, and when they recommend your products in response
to customer questions. Together we define KPIs and set up monitoring.
Analysis & optimization
We analyze initial results and identify bottlenecks in generative engine optimization (GEO),
such as weak product descriptions, unclear taxonomy, missing attributes, or queries that lead
to poor or incomplete answers. Improvements are tested and measured.
Evaluation & insights
We share the most valuable insights gathered during the pilot and translate them into a clear
roadmap. The focus is on sustainable improvements that increase visibility, relevance, and
performance in AI-driven product discovery.
Why this matters
- Improved product discovery: LLMs understand intent and context better than traditional search.
- Long-tail queries: AI can handle complex and rare questions through semantic understanding.
- Efficiency: Structured catalog enrichment reduces manual work.
- Competitive advantage: Be visible in future AI-driven shopping interfaces.