Can Walmart Machine Learn its Way to the Top?

In a war between Amazon and Walmart for the e-commerce crown, who will ultimately win?

With Amazon anticipated to capture 50% of 2018’s U.S. e-commerce market share, “” has become synonymous to “online shopping.”[i] Perhaps more surprising is the next-closest e-commerce competitor, eBay, has 7% and Walmart, at 4th place, only commands 4%.[ii] These statistics beg the question – can anyone catch Amazon?

Walmart’s mission is to “[help] people around the world save money and live better”.[iii] Walmart offers customers value through achieving price leadership. Digital innovation is critical to Walmart’s survival because with continued shifts to e-commerce, Walmart may find itself with a declining in-store customer base. During 2017 Black Friday week, U.S. retail in-store foot traffic declined 4% from 2016, while online sales increased 18%.[iv] Management understands that to win online, “[Walmart] needs to also win through logistics and supply chain.”[v] Walmart achieves price leadership through large-scale volume negotiating power with suppliers. However, if Walmart begins losing customers, then it will lose its negotiating power and ultimately, its low prices. It is crucial for Walmart to find ways to drive process improvement, win e-commerce customers, grow its customer volume, and continue to deliver on its promise.

Machine learning enables Walmart to efficiently parse through and analyze its wealth of data driven by a weekly customer base of nearly 270 million customers across all 28 countries.[vi] Walmart is able to drive process improvement through utilizing algorithms to predict preferences on product assortment, make personalized recommendations for individuals and better manage inventory levels.

Beginning in 2016, Walmart began investing billions of dollars in growing its online platform through various acquisitions and strategic alliances, after realizing its organic e-commerce investments were not sufficient to compete with Amazon.[vii] In August 2016, Walmart acquired for $3.3 billion in a move that many viewed as “defensive” and “reactionary” to Amazon’s accelerating share gains.[viii] While the deal is viewed as a longer-term play for Walmart, gaining’s dynamic pricing technology and experienced team, there are meaningful short-term benefits. Walmart gained immediate access to a “valuable urban, young, affluent demographic” that was vastly different than Walmart’s existing lower-income customers.[ix] Gaining 2 million new customers’ data and purchasing habits enabled Walmart to further feed its predictive algorithms.[x] Combined with’s dynamic pricing algorithms, Walmart poised itself to further provide customers with broader product assortment at even lower prices.

In May 2018, Walmart acquired Indian e-commerce site Flipkart for $16 billion.[xi] This investment was the largest acquisition Walmart made in 20 years.[xii] The deal rationale was simple – acquire an established e-commerce platform to grow customers and compete with Amazon. Like, in the near term Flipkart provides Walmart access to a new customer base with an established e-commerce platform. In the longer-term, Flipkart’s technology will enable Walmart to source e-commerce lessons from the Indian e-commerce arena and apply best practices and technological improvements to U.S. e-commerce.[xiii] Sharing teachings across geographies drives process improvement on multiple fronts and could pass on additional savings to customers.

Additionally, in July 2018, Walmart formed a five-year strategic partnership with Microsoft to further enhance its machine learning capabilities in the medium- to longer-term. The partnership helps Walmart “to improve operational efficiency through the application of machine learning”.[xiv] Through leveraging Microsoft’s artificial intelligence technology, Walmart will strive to improve website functionality, reduce in-store energy consumption and further strengthen its delivery systems, allowing Walmart to improve its process and continue in its price leadership position.[xv]

While Walmart’s foray into machine learning has been largely acquisitive, management could explore organically-developed avenues. Currently, Walmart does not yet have a system to link its online and in-store customers. Given the range of demographics (millennial customers vs. lower-income in-store shoppers), establishing a program connecting omni-channel shoppers would provide valuable additional data for Walmart’s algorithms to understand and predict purchasing habits. One recommendation would be a loyalty rewards program that enables tracking customers across various channels and further improve its algorithms, and provides additional cost savings to customers.

Walmart’s investments in machine learning and digital innovation are necessary steps in the ongoing battle to win online retail, or at least, to catch up to Amazon. Wall Street believes that if Walmart could attack Amazon in both price and assortment “on [Amazon’s] home turf,” then there is “a real possibility that [Walmart] could disrupt Amazon’s standing.”[xvi] The biggest question now is how Amazon will respond. Perhaps Amazon is not worried about its competitors. However, with a forward-thinking leader at its helm, no one would believe that Amazon is happy to concede market share it painstakingly won.

Ultimately, the winner of this e-commerce war is the end customer.

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[i]   “Amazon Now Has Nearly 50% of US Ecommerce Market,” eMarketer Retail,, accessed November 2018.

[ii] Ibid.

[iii] Walmart Inc., January 31, 2018 Form 10-K,, accessed November 2018.

[iv] Sarah Nassauer and Laura Stevens, “Inside the Wal-Mart vs. Amazon Battle Over Black Friday,” The Wall Street Journal, November 26, 2017,, accessed November 2018.

[v] Oliver Chen et al., “Investor Day: An Intense Customer Focused Transformation, Reit. Outperform,” Cowen and Company, October 6, 2016, p. 2, via Bloomberg, accessed November 2018.

[vi] Walmart Inc., January 31, 2018 Form 10-K,, accessed November 2018.

[vii] Simeon Gutman et al., “Is Walmart Flying the Right Jet?” Morgan Stanley & Co. LLC, August 8, 2016, p. 1, via Bloomberg, accessed November 2018.

[viii] Simeon Gutman et al., “Is Walmart Flying the Right Jet?” Morgan Stanley & Co. LLC, August 8, 2016, p. 3, via Bloomberg, accessed November 2018.

[ix] Daniel Binder et al., “Wal-mart (WMT) Interesting Acquisition and Interesting Price,” Jefferies LLC, August 8, 2016, p. 1, via Bloomberg, accessed November 2018.

[x] Greg Melich and Michael Montani, “WMT: Invest & Evolve,” Evercore Group LLC, October 7, 2016, p. 1, via Bloomberg, accessed November 2018.

[xi] Rishi Iyengar and Sherisse Pham, “Walmart is buying India’s Flipkart,” CNN Business, May 9, 2018,, accessed November 2018.

[xii] Vindu Goel et al., “Walmart, With Billions to Spend, Seeks Flipkart E-Commerce Site in India,” The New York Times, April 26, 2018,, accessed November 2018.

[xiii] Jon Russell, “Walmart says Flipkart is ‘a key center of learning’ for its entire global business,”, May 9, 2018,, accessed November 2018.

[xiv] Randal Konik et al., “Dept. Stores & Specialty Softlines CLICKS vs. BRICKS Vol. 30: Dream Come True – Casper Brings Naptime to Nordstrom,” Jefferies LLC, July 19, 2018, p. 1, via Bloomberg, accessed November 2018.

[xv] Mike Robuck, “Walmart, Microsoft are teaming up to take on Amazon,” Fierce Telecom, July 17, 2018,, accessed November 2018.

[xvi] Harshita Rawat et al., “Amazon at the gates – what we worry (and don’t worry) about,” Sanford C. Bernstein & Co. LLC, October 10, 2018, p. 11, via Bloomberg, accessed November 2018.


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Student comments on Can Walmart Machine Learn its Way to the Top?

  1. Great points on connecting a customer’s offline and online date to understand and predict purchasing habits. Using omnichannel data to retarget customer would be very valuable. Walmart has a lot of physical touch-points with customers. If it can leverage those touch-points and target these customers online, it stands a chance at disrupting Amazon’s standing.
    Also, I believe Personalisation – which Amazon currently does very well- with the help of AI/ML is the key to staying ahead in this battle. Weeding out irrelevant data will help the customer and shorten the purchase journey, making the product funnel a lot better. Machine Learning can also be used along with this data to improve customer service and enable round the clock support.

  2. I think Walmart has a lot to gain when it comes to machine learning, but it also seems like Amazon has a bit of a lead/advantage. I think partnering with Microsoft is huge for them and makes them a much more credible threat to Amazon’s livelihood, so it will be interesting to see how it plays out. I am also interested to understand how the perception of and Walmart as a brand factors into the overall success since their image is seemingly very different from that of Amazon’s. Well written piece and a good read!

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