“You could just grab stuff and walk out. It’s such a foreign concept to me…it feels like I’m shoplifting.”[i]
– Customer Melody Coleman describing Amazon Go
Amazon Go is a cashier-less convenience store that leverages, “hundreds of cameras on the ceiling, plus sensors in the shelves…[to] record what each person picks up, so they can walk out without having to visit a checkout” (see Exhibit 1).[ii] The concept represents a strategic shift for Amazon as it looks to address the 90% of U.S. retail transactions occurring in physical stores.[iii]
Exhibit 1: Amazon Go Launch Video[iv]
Machine Learning’s Impact on Amazon Go’s Process Improvement & Product Development
Amazon Go’s utilization of hardware and machine learning algorithms represents a step-function change in process improvement relative to traditional retailers. Customers enter an Amazon Go store, “by scanning a QR code in [its] mobile app.” Sensors then track each customer, dynamically updating their basket as items are added and automatically bill them upon exit, thus eliminating the traditional process bottleneck (checkout lines) and improving throughput times.[ii] As described by Dilip Kumar, Vice President of Technology for Amazon Go, “You control the amount of time that you’re actually spending at the store.”[v] Additionally, Amazon Go’s machine learning algorithm enables superior inventory management as it can, “make demand forecasts based not just on historical sales data but also on other influencing parameters: internal factors such as advertising campaigns and store-opening times, and external factors such as local weather and public holidays.” McKinsey observed similar technologies reduce out-of-stock rates by 80% and improve gross margins by 9%.[vi]
The technology underlying Amazon Go’s operating model also has implications for product development. Amazon drives 35% of its e-commerce purchases through product recommendations generated by machine learning algorithms.[vii] Similar potential exists at Amazon Go as the company can generate customer-specific recommendations and personalized marketing messages by leveraging data associated with users’ unique QR codes. Such data will enable Amazon to design new food offerings based on consumer preferences and perform highly-focused product trials by targeting discrete customer segments.
Management’s Short- and Medium-Term Strategy
In the short-term, Amazon’s management is looking to aggressively build Amazon Go locations to gain share in the $28.5B U.S. convenience store industry.[viii] There are currently 6 locations across Seattle, Chicago, and San Francisco, with ambitions for 10 by year end, 50 by 2019, and 3,000 by 2021.[ix] [x] Adding scale will be critical to the project’s success as powering Amazon’s predictive model with increasingly large data sets will enhance statistical power and improve product recommendations, furthering customer loyalty.
In assessing management’s medium-term strategy for Amazon Go’s technology, we must consider the firm’s $13.7B acquisition of Whole Foods, an organic grocery chain, in June 2017.[xi] IBIS World estimates that the U.S. grocery industry is $633.2B, over 20x larger than the U.S. convenience store market.[xii] The Whole Foods acquisition provides Amazon with a sizable brick-and-mortar footprint representing over 470 locations.[xiii] Upon demonstrating proof of concept within the Amazon Go stores, management is likely to target rolling out similar technology across the Whole Foods network to drive innovation against a largely complacent competitive set.
Recommendations to Management
To achieve its ambitious strategic vision, Amazon must approach traditional problems in an innovative way. Below are a few recommendations that would facilitate management’s objectives.
- Drive Inventory Management with Machine Learning – Inventory shrinkage resulting from food spoilage and product theft costs U.S. retailers $46.8B in 2017.[xiv] Grocers experience the impacts of shrink particularly strongly (3.6% of sales vs. 1.4% on average), which provides Amazon an opportunity to leverage machine learning to predict demand and lower costs relative to competitors.[xv] Exhibit 2 summarizes how machine learning algorithms can leverage demand probabilities and expected costs to determine optimal inventory levels.
Exhibit 2: Inventory Management with Machine Learning[vi]
- Reduce Capex Investment – The inaugural Amazon Go store in Seattle required a $1M investment in hardware alone.[x] Meanwhile, grocery stores can be up to 100x larger than the 1,800-square-foot Amazon Go store with exponentially more customers and products to monitor simultaneously.[i] Management should focus on lowering the upfront investment to make scaling the technology feasible.
- Personalized Recommendations – Management should introduce location-based item recommendations to spur impulse add-on purchases. Research shows that grocery stores’ profitability could increase ~40% if each customer purchased one additional item on impulse.[xvi]
- Experiment with Store Design – Amazon should leverage its data on customer paths through a store to test different layouts and product placements to maximize basket size.
Given the formidable, entrenched competition in the convenience and grocery segments, I continue to wrestle with two key questions:
- How can Amazon develop a sustainable competitive advantage against other data-driven competitors such as Walmart (the world’s largest retailer and grocery chain by sales)?[xii]
- What are the implications of a shift in consumer preferences to ordering groceries online instead of purchasing in-store?
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[i] Bullinger, Jake. “Amazon’s Checkout-Free Store Makes Shopping Feel Like Shoplifting.” The Atlantic, January 24, 2018. https://www.theatlantic.com/business/archive/2018/01/amazon-go-store-checkouts-seattle/551357/, accessed November 9, 2018.
[ii] Simonite, Tom. “Stepping into an Amazon Store Helps it Get Inside Your Head.” Wired, October 23, 2018. https://www.wired.com/story/stepping-into-amazon-store-helps-get-inside-your-head/, accessed November 5, 2018.
[iii] U.S. Census Bureau News. “Quarterly Retail E-Commerce Sales: 2nd Quarter 2018.” August 17, 2018. https://www.census.gov/retail/mrts/www/data/pdf/ec_current.pdf, accessed November 9, 2018.
[iv] Amazon. “Introducing Amazon Go and the world’s most advanced shopping technology,” YouTube, published December 5, 2016. https://www.youtube.com/watch?v=NrmMk1Myrxc&t=8s, accessed November 5, 2018.
[v] Metz, Rachel. “Amazon’s cashier-less Seattle grocery store is opening to the public.” MIT Technology Review, January 21, 2018. https://www.technologyreview.com/s/610006/amazons-checkout-free-grocery-store-is-opening-to-the-public/, accessed November 5, 2018.
[vi] Glatzel, Christoph, Matt Hopkins, Tim Lange, and Uwe Weiss. “The secret to smarter fresh-food replenishment? Machine learning.” McKinsey, November 2016. https://www.mckinsey.com/industries/retail/our-insights/the-secret-to-smarter-fresh-food-replenishment-machine-learning, accessed November 5, 2018.
[vii] MacKenzie, Ian, Chris Meyer, and Steve Noble. “How retailers can keep up with consumers.” McKinsey, October 2013. https://www.mckinsey.com/industries/retail/our-insights/how-retailers-can-keep-up-with-consumers, accessed November 11, 2018.
[viii] Source: Convenience Stores in the US, IBISWorld, accessed November 8, 2018.
[x] Soper, Spencer. “Amazon Will Consider Opening Up to 3,000 Cashierless Stores by 2021.” Bloomberg, September 19, 2018. https://www.bloomberg.com/news/articles/2018-09-19/amazon-is-said-to-plan-up-to-3-000-cashierless-stores-by-2021, accessed November 5, 2018.
[xi] Debter, Lauren. “Amazon Is Buying Whole Foods For $13.7 Billion.” Forbes, June 16, 2017. https://www.forbes.com/sites/laurengensler/2017/06/16/amazon-to-buy-whole-foods-for-13-7-billion/#10c2d7719589, accessed November 12, 2018.
[xii] Source: Supermarkets & Grocery Stores in the US, IBISWorld, accessed November 8, 2018.
[xiii] Amazon.com, Inc. December 31, 2017 Form 10-K. https://www.sec.gov/Archives/edgar/data/1018724/000101872418000005/amzn-20171231x10k.htm, accessed November 5, 2018.
[xiv] National Retail Federation, “2018 National Retail Security Survey” (PDF file), downloaded from NRF website, https://cdn.nrf.com/sites/default/files/2018-10/NRF-NRSS-Industry-Research-Survey-2018.pdf?_ga=2.88235231.557395974.1542055811-36604989.1542055811, accessed November 12, 2018.
[xv] National Retail Federation, “The 2016 National Retail Security Survey” (PDF file), downloaded from NRF website, https://cdn.nrf.com/sites/default/files/2018-10/NRF_2016_NRSS_restricted-rev.pdf?_ga=2.118200269.557395974.1542055811-36604989.1542055811, accessed November 12, 2018.
[xvi] “Amazon Go: Stores Worth Less Than Tech,” The Battle of Giants (blog), Seeking Alpha, May 18, 2018, https://seekingalpha.com/article/4175386-amazon-go-stores-worth-less-tech, accessed November 12, 2018.