Dynamic pricing deserves attention now because three developments have converged. Artificial intelligence has made individualised pricing accessible, allowing for the possibility of a different price for every consumer. The growth of e-commerce has supplied both the behavioural data and the repricing infrastructure to act on it. Meanwhile, regulation is beginning to take shape, and the rules that will govern individualised pricing are being written before most retailers have decided where they stand.
As individualised pricing spreads, the question for department stores is not whether to run a data operation — they already run one, through their loyalty programmes, apps and data partnerships — but what to do with it. Two answers follow, and only one is defensible. The first is to point that operation at customers the way big tech does, personalising prices to extract the most each will pay but its failure mode is defeat by big tech itself. IADS argues that the second is to run the same machinery under a public commitment that it will only ever move a customer’s price downward, and to make that transparency the differentiator.
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