Research data and methodology details will be published here when the benchmark study is complete. The study uses SatelliteAI's seven-signal cross-engine matrix to evaluate citation accuracy across ChatGPT, Claude, and Gemini in both base knowledge and search-augmented modes.
Original Research
AI Citation Accuracy
Benchmark 2026
Cross-Engine Analysis: ChatGPT, Claude, Gemini
SatelliteAI analyzed 500+ queries across three major AI engines to measure citation accuracy rates, cross-engine disagreement patterns, and hallucination frequency by category. This is the first study to apply multi-model statistical consensus to the question of whether AI engines cite brands correctly, not just frequently. Built on the same verification methodology behind answer engine optimization.
Methodology
How We Measured Citation Accuracy
Results
Results by Engine
Per-engine accuracy rates, citation source analysis, and hallucination patterns will be published here.
Cross-Engine
Cross-Engine Agreement Rates
Analysis of how often ChatGPT, Claude, and Gemini agree on citations for the same query will be published here.
Categories
Hallucination Frequency by Category
Category-level hallucination rates (healthcare, finance, technology, e-commerce) will be published here.
Findings
Key Findings
Summary findings and actionable insights will be published here.
This benchmark applies multi-model statistical consensus to measure whether AI engines cite brands correctly, not just frequently.
Citation accuracy and citation frequency are different metrics; a brand can be cited often and inaccurately, creating reputation risk rather than visibility gains.
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