Product recommendation, shopping assistants, clienteling tools, demand forecasting: every retailer deployed team by team and brand by brand. Leadership knows what the estate costs and rarely knows what it is worth. Idun Group measures actual usage from the logs your platforms already produce, then puts the decision on the table.
Customer assistants in pre-sales and e-commerce, support for sales and beauty advisors, brand voice in communications, marketing and product content, research and product development, and the product engineering teams. For each one we report what the analysis reveals and the decision it unlocks.
Industrialise where usage is broad, repeated and settled over time. Consolidate where one use case is covered by several tools or several brands. Cut where usage is marginal and paid seats go unused. Each outcome maps to an immediate budget action.
Measuring changes nothing on its own. Three forms of tooling move usage, from cheapest to most committing: publishing the shared assets, putting AI where the work already happens, and sharing agents on the use cases that recur. Tooling, not instructions on discipline.
We start from the logs and exports you already produce, with nothing installed on workstations and no re-instrumentation. Interviews with the IT department and the business units are mandatory: the interviews and the data, never one in place of the other. We analyse usage, never people. Data is pseudonymised and aggregated by design.
LVMH: design and operation of a generative AI agent platform in production. L'Oréal: deployment and governance of usages in the group's Microsoft ecosystem. More than 40 AI assessments in under a year across more than 10 large enterprise clients. Across the estates we analyse, 20 to 40 % of paid AI seats go unused.
