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

by Robert Hetu  |  March 13, 2018  |  Submit a Comment

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:

Will People or Machines Rule Algorithmic Retailing?
Business leaders are understandably overwhelmed by artificial intelligence due to its complexity and disruptive workplace implications. Retail CIOs must take active leadership in setting the course for this critical technology as part of an overall retail digital business strategy.
Published: 21 Dec 2017

Using Algorithmic Retailing to Drive Competitive Advantage
Retailers gain competitive advantage through the application of algorithms that reduce costs and grow top-line revenue. CIOs can use this research to identify use cases that will improve business performance in the unified commerce retail marketplace.
Published: 21 Sep 2016

Algorithmic Retailing: Using AI to Drive Smart Automation
Retailers must use AI to automate and deliver better decisions and make it possible for associates to be customer experience differentiators. CIOs can use this research to identify opportunities to use AI to drive smart automation.
Published: 12 May 2017

Algorithmic Retailing: Merchandising Leads the Way
Leveraging algorithms is the only way that merchandising can meet the customer centricity challenges of digital business and the digitalization of retail. This research describes algorithmic merchandising and its impact on the business.
Published: 09 Mar 2016


Additional Resources

100 Data and Analytics Predictions Through 2024

Gartner’s annual predictions disclose the varied importance of data and analytics across an ever-widening range of business and IT initiatives. Data and analytics leaders must consider these strategic planning assumptions for enhancing their vision and plans.

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Category: ai  data-and-analytics-strategies  smart-machines  

Tags: advanced-analytics  ai  algorithmic-retailing  algorithms  analytics  retail  trends  walmart  

Robert Hetu
VP, Analyst Retail
7 years at Gartner
29 years IT Industry

Bob Hetu is a Research Director with the Gartner Retail Industry Services team. His responsibilities involve tracking the technology markets and trends impacting the broad-based retail merchandising and planning areas. Mr. Hetu is an expert in the areas of brand, vendor and assortment management, merchandise planning, allocation, and replenishment. Read Full Bio

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