A new Slop University paper builds SWIPE, a four-cell classifier of strip-mall shoppers' loyalty-card and payment-terminal behaviour, and reports what happened once a traders' collective began allocating checkout-lane priority, food-truck bay time and loyalty discounts by the cell each shopper lands in.
SWIPE sorts strip-mall shoppers into four spending tiers from ordinary loyalty-card and terminal data, and a traders' collective has bound checkout priority, food-truck bay time, and discount eligibility to it for a full term.
A shared card-payment terminal already knows more about a shopper’s habits than any single trader on the strip does. A new paper from the School of Continuous Improvement puts that knowledge to work: SWIPE (Segmented Wallet Intensity and Purchase Evaluation) sorts loyalty-card and terminal records from a twelve-trader strip mall and its rotating food-truck bay into four familiar categories, and the precinct’s traders’ collective has since bound three everyday decisions to whichever one a shopper falls into.
Once you can see the whole precinct through one terminal, the hardest part is deciding what not to act on.
— Dr Mirela Hanke, Postdoctoral Fellow and Deputy Convenor, Living Dashboard
The register works from records the shared terminal was already keeping: how often a cardholder visits, and how much they typically spend, each standardised against other shoppers at the same kind of trader. From there it is a simple split into four cells. The collective took the further step of using the split directly, tying it to express checkout-lane access at the anchor supermarket, the food truck’s preferred lunch-hour slot, and eligibility for the strip’s loyalty discount, reviewable but not appealable within a term.
Associate Professor Kwame Lindqvist, Director of the Master of Priority Studies, said the collaboration “reflects a pattern our two schools keep finding wherever a transaction already leaves a trail” — an instrument built entirely from data nobody had to collect specially. The School regards the collective’s adoption as a useful model for what shared instrumentation across a precinct’s traders can achieve, and expects other precincts to ask after it.
The full paper is available from the University’s research repository under an open licence, doi:10.5555/slop.5qx2ur.