Game Store Employee Correctly Predicts Customer's Purchase Based On Outfit Alone
Six years of retail experience enables instant classification of customer intent from clothing choices

A board game store employee has correctly predicted a customer's purchase with 94% accuracy over the past year based solely on the customer's clothing and general demeanor upon entering the store.
Cassandra Retail, who has worked at The Game Shelf for six years, has developed what she calls "a taxonomy of the board game buyer" that allows her to identify customer intent within seconds of their arrival.
"Graphic tee with a strategy game reference: they want a heavy Euro, probably something by Uwe Rosenberg or Vital Lacerda. They will ask about player counts and weight ratings," Cassandra explained.
"Couple holding hands: Patchwork, Jaipur, or 7 Wonders Duel. They want something competitive but not relationship-ending. I steer them away from the Catan shelf."
"Parent with a child under ten: they want a 'fun' game, which means a game with dice and bright colors that lasts under thirty minutes. They will reject anything with a rulebook longer than two pages."
"Person in business casual, looking slightly lost: they need a gift. They will say 'I don't really play games but my nephew does.' I will sell them Ticket to Ride because it is always correct."
Cassandra's most reliable prediction: "Anyone wearing a Warhammer t-shirt will spend more than $100. This has never been wrong. Not once in six years."
Her one blind spot is the customer who enters wearing no identifiable signals — plain clothing, neutral expression, no companion. "Those people could want anything," Cassandra admitted. "They're the wildcards. Sometimes they buy a $200 legacy game. Sometimes they ask where the restroom is and leave."
AI-generated satirical fiction. Not real news.
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