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鈥檚 U.S. e-commerce market share, 鈥淎mazon.com鈥 has become synonymous to 鈥渙nline shopping.鈥[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 鈥 can anyone catch Amazon?
Walmart鈥檚 mission is to 鈥淸help] people around the world save money and live better鈥.[iii] Walmart offers customers value through achieving price leadership. Digital innovation is critical to Walmart鈥檚 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, 鈥淸Walmart] needs to also win through logistics and supply chain.鈥[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 Jet.com for $3.3 billion in a move that many viewed as 鈥渄efensive鈥 and 鈥渞eactionary鈥 to Amazon鈥檚 accelerating share gains.[viii] While the deal is viewed as a longer-term play for Walmart, gaining Jet.com鈥檚 dynamic pricing technology and experienced team, there are meaningful short-term benefits. Walmart gained immediate access to a 鈥渧aluable urban, young, affluent demographic鈥 that was vastly different than Walmart鈥檚 existing lower-income customers.[ix] Gaining 2 million new Jet.com customers鈥 data and purchasing habits enabled Walmart to further feed its predictive algorithms.[x] Combined with Jet.com鈥檚 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 鈥 acquire an established e-commerce platform to grow customers and compete with Amazon. Like Jet.com, in the near term Flipkart provides Walmart access to a new customer base with an established e-commerce platform. In the longer-term, Flipkart鈥檚 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 鈥渢o improve operational efficiency through the application of machine learning鈥.[xiv] Through leveraging Microsoft鈥檚 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鈥檚 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 Jet.com customers vs. lower-income in-store shoppers), establishing a program connecting omni-channel shoppers would provide valuable additional data for Walmart鈥檚 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鈥檚 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 鈥渙n [Amazon鈥檚] home turf,鈥 then there is 鈥渁 real possibility that [Walmart] could disrupt Amazon鈥檚 standing.鈥[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] 聽聽鈥淎mazon Now Has Nearly 50% of US Ecommerce Market,鈥 eMarketer Retail, https://retail.emarketer.com/article/amazon-now-has-nearly-50-of-us-ecommerce-market/5b48c542ebd4000b24140992, accessed November 2018.
[ii] Ibid.
[iii] Walmart Inc., January 31, 2018 Form 10-K, https://www.sec.gov/Archives/edgar/data/104169/000010416918000028/wmtform10-kx1312018.htm, accessed November 2018.
[iv] Sarah Nassauer and Laura Stevens, 鈥淚nside the Wal-Mart vs. Amazon Battle Over Black Friday,鈥 The Wall Street Journal, November 26, 2017, www.wsj.com, accessed November 2018.
[v] Oliver Chen et al., 鈥淚nvestor Day: An Intense Customer Focused Transformation, Reit. Outperform,鈥 Cowen and Company, October 6, 2016, p. 2, via Bloomberg, accessed November 2018.
[vi] Walmart Inc., January 31, 2018 Form 10-K, https://www.sec.gov/Archives/edgar/data/104169/000010416918000028/wmtform10-kx1312018.htm, accessed November 2018.
[vii] Simeon Gutman et al., 鈥淚s Walmart Flying the Right Jet?鈥 Morgan Stanley & Co. LLC, August 8, 2016, p. 1, via Bloomberg, accessed November 2018.
[viii] Simeon Gutman et al., 鈥淚s Walmart Flying the Right Jet?鈥 Morgan Stanley & Co. LLC, August 8, 2016, p. 3, via Bloomberg, accessed November 2018.
[ix] Daniel Binder et al., 鈥淲al-mart (WMT) Interesting Acquisition and Interesting Price,鈥 Jefferies LLC, August 8, 2016, p. 1, via Bloomberg, accessed November 2018.
[x] Greg Melich and Michael Montani, 鈥淲MT: Invest & Evolve,鈥 Evercore Group LLC, October 7, 2016, p. 1, via Bloomberg, accessed November 2018.
[xi] Rishi Iyengar and Sherisse Pham, 鈥淲almart is buying India鈥檚 Flipkart,鈥 CNN Business, May 9, 2018, www.money.cnn.com, accessed November 2018.
[xii] Vindu Goel et al., 鈥淲almart, With Billions to Spend, Seeks Flipkart E-Commerce Site in India,鈥 The New York Times, April 26, 2018, www.nytimes.com, accessed November 2018.
[xiii] Jon Russell, 鈥淲almart says Flipkart is 鈥榓 key center of learning鈥 for its entire global business,鈥 techcrunch.com, May 9, 2018, https://techcrunch.com/2018/05/09/walmart-says-flipkart-is-a-key-center-of-learning-for-its-entire-global-business/, accessed November 2018.
[xiv] Randal Konik et al., 鈥淒ept. Stores & Specialty Softlines CLICKS vs. BRICKS Vol. 30: Dream Come True – Casper Brings Naptime to Nordstrom,鈥 Jefferies LLC, July 19, 2018, p. 1, via Bloomberg, accessed November 2018.
[xv] Mike Robuck, 鈥淲almart, Microsoft are teaming up to take on Amazon,鈥 Fierce Telecom, July 17, 2018, https://www.fiercetelecom.com/telecom/walmart-microsoft-are-teaming-up-to-take-amazon, accessed November 2018.
[xvi] Harshita Rawat et al., 鈥淎mazon at the gates – what we worry (and don’t worry) about,鈥 Sanford C. Bernstein & Co. LLC, October 10, 2018, p. 11, via Bloomberg, accessed November 2018.
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.
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 Jet.com 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!