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See how your recommendation logic behaves before deploying it.

Start with a made-up sample catalog — you do not have to upload anything.
Eight ways of choosing what to recommend, and ten things we measure about each.
Run it again and you get the same answer, so a result you share can always be checked.

These results come from a simulation, not from real people. They show how a strategy behaves on this catalog, which is useful for comparing options — but they are not a prediction of what your actual users will do. Try anything promising with real users before you rely on it.

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