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Dan Cohen @dancohen.bsky.social · 22/09/2026

Our research found that other companies use the same fundamental technologies as in the article (see screenshot) to target customers and drive profits. Sainsbury's calculates a 'customer potential sales value score' for their rewards program with higher potential spenders receiving more discounts.

Figuring this out required machine learning. Unlike traditional data analytics, where researchers decide which patterns to look for, machine learning models can sift through hundreds of variables on their own to find combinations that help predict particular behaviors.

Data scientists had trained the new casino model on historical data. It was Mr. Butts's job to test it on real customers. Each week, the model vacuumed up information about a user's recent activity. The score it calculated was known internally as "elasticity," a term borrowed from economics.

Users with below-average scores were deemed "inelastic" and marked for fewer incentives. The "elastic" bettors remained.

Visual description of Sainbury's program

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Dan Cohen @dancohen.bsky.social · 22/09/2026

Our paper is currently under peer review, but we argue this is the development of an even-more stratified economy, with a 'personal strikes' approach to discounts/prices that leverages informational asymmetries and digital enclosures (e.g. apps) to drive profitability at the expense of consumers.

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