How does DineVisible score restaurants?
DineVisible runs 80–150 of the natural-language questions diners ask, against ChatGPT, Claude, Gemini, and Perplexity, then scores each restaurant 0–100 from five dimensions: mention frequency (30%), position (25%), cross-engine consistency (15%), context richness (15%), and source diversity (15%).
The five dimensions
Mention Frequency (30%) — how much of the question matrix names you. Position (25%) — how high you land when you appear. Cross-Engine consistency (15%) — how many of the four engines agree. Context Richness (15%) — how much detail AI gives, such as price, vibe, and dishes. Source Diversity (15%) — the breadth of sources backing you up.
Why four engines
The engines disagree constantly — one names you first, another skips you, a third cites a rival. A single-engine view is noise. Scoring across all four is what makes a ranking trustworthy, and the disagreement itself is a signal we surface.
How often it updates
Each neighborhood is re-audited weekly, and the public leaderboard updates the morning after. The method and weights are published so the score is transparent rather than a black box.
More questions
How many questions does DineVisible run per neighborhood?
80–150 natural-language questions across cuisine, neighborhood, occasion, and preference — phrased the way real diners ask.
How often is the score updated?
Weekly. Each neighborhood is re-audited across all four engines and the public leaderboard refreshes the next morning.