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Glossary · definition

Agent-Ready Booking Index

The G-Lab Agent-Ready Booking Index is the share of businesses in a defined market that an AI assistant can find, understand and book, measured across a fixed random sample under identical conditions and published with its sample, its boundary and its method version. No reservation is ever submitted.

The same measurement as the Check, applied to a city, a country or a vertical, so a market can be compared with itself over time and with other markets.

A market, not a business

The Check answers a question about one business. The Index answers it about a market: what share of restaurants in this city could an assistant book right now? To make that share mean something, the market has to be drawn the same way every time.

The sample is mechanical and seeded. The frame, the exclusions and the sample size are fixed and published before anyone looks at a single website, so the result cannot be steered by choosing which businesses to include.

What an index reports

Distributions, not league tables. How many businesses have a working website, how many expose a booking path an agent can find, how many let the agent reach the final step, how many publish an interface an assistant can call directly. Every figure comes with the sample size it was measured on.

No business is named as a low scorer. A business in the sample can ask for its own full result privately and can ask to be excluded from future runs.

The first index

The Amsterdam Restaurant Agent-Ready Booking Index 2026 measured 200 restaurants drawn at random from the city in July 2026, and measured the same sample again in September. It was published on 22 July 2026 under method version 1.0.

How to cite this term

Method v1.0, dated 21 Jul 2026. The definition changes only when the method version changes; the address stays.

G-Lab Research (2026). "Agent-Ready Booking Index". G-Lab agent-ready booking measurement, method v1.0 (21 Jul 2026). https://g-lab.studio/research/glossary/agent-ready-booking-index

Related

G-Lab Research studies how local businesses are found, understood and booked by people and by AI assistants. We publish the method before the findings, name every source, and version the methodology so a result can always be traced to the way it was measured.

Questions about a figure, the sample or the method: hello@g-lab.studio. Corrections are published in the methodology changelog. Quoting us: how to cite.