Just read this article at Bloomberg “Walgreens Replaced Fridge Doors With Smart Screens. It’s Now a $200 Million Fiasco”. In summary, a startup promised Walgreens that its high-tech fridges would track shoppers and spark an in-store advertising revolution. Then the project fails miserably for a number of reasons.
It’s probably a terrible idea to block the view of soft drinks, which customers can literally touch anyway, with a digital screen. If the digital screens are offline for any reason, the contents are completely invisible (that’s why they had to put signs on the doors explaining what’s inside!).
But why was this idea even executed in the first place? Apparently, Walgreens signed a 10-year contract and initially had 10,000 smart doors installed. So why more than a limited experiment in the first place?
My answer is bad data, bad analysis: a poor understanding of causal modeling and data centricity.
Here is a four-sentence summary from the article:
Expectation vs. reality 1:
“Pilot data showed the screens resulting in more than a 5% incremental sales jump, and Walgreens committed to installing them in an additional 50 stores the next year as part of a decade-long deal.”
“Walgreens says each smart door ended up bringing in just $215 that year, or a mere 59¢ a day, about half the contractual minimum and a pittance when measured against the thousands of dollars each door cost to build and install.”
Expectation vs. reality 2:
“Cooler Screens had outsourced sales of available advertising slots for its fridges to Yahoo, then a subsidiary of its investor Verizon. But Yahoo barely topped $3 million in sales for the fridges in 2021, 91% lower than projected, a Cooler Screens court filing said.”
Grand finale:
The startup “claimed that its displays garnered almost 100 million monthly impressions and gave brands a healthy sales bounce, but these people doubted the math, which was tracked in spreadsheets.”