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Walmart’s Freshness Algorithm; A Great Example of Algorithmic Retailing

By Robert Hetu | March 13, 2018 | 0 Comments

Smart MachinesData and Analytics StrategiesAI

When I introduced the concept of algorithmic retailing two years ago my definition was simple. The application of big data through advanced analytics across an increasingly complex and detailed retail structure to deliver an efficient, flexible, yet unified customer experience.

Algorithmic Retailing Defined
Gartner 2016

In a recent blog post, Walmart announced Eden, a solution that “leverages sophisticated technologies such as machine learning, but we’ve made it simple enough for all of our associates to use. Eden’s suite of apps helps Walmart associates better monitor and care for fresh fruits and vegetables that are waiting to be shipped from distribution centers to stores. That could mean more efficiently ripening bananas, predicting the shelf life of tomatoes while they’re still on the vine, or prioritizing the flow of green grocery items from the back of the store to the shelf.”

This is a great illustration of how algorithmic retailing will enhance customer experiences and improve retailer performance.  By enabling associates to extract knowledge from big data through machine learning via an algorithm, they are embracing the KISS method, Knowledge, that leads to Innovation and Strategy, at the Speed required to deliver results.

Gartner 2016
Gartner 2016

Walmart indicated that it has already prevented over $86 Million in waste and that it expects to save $2 Billion over five years.  What a great example, made even better since it rose from ideas within the ranks of its associates.  Gartner clients can read more on algorithmic retailing here:

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