P R O V I D I N G I N - D E P T H I N S I G H T , D A T A , A N D A N A L Y S I S O F E V E R Y T H I N G D I G I T A L THE FUTURE OF RETAIL: IN-STORE EXPERIENCE BUSINESS INSIDER INTELLIGENCE 

Brick-and-mortar is still the dominant driver of retail spend in the US Source: Business Insider Intelligence estimates, US Census Bureau, PYMNTS, Criteo, eMarketer, CPC Strategy, Worldpay, Digital Commerce 360, comScore Channel share of US adjusted retail 2017 2018 2019 Estimated 2019 US retail sales by method, billions ($) 8.7% 9.0% 9.2% 9.4% 9.6% 9.8% 10.0% 10.1% 10.5% 10.8% 11.2% 91.3% 91.0% 90.8% 90.6% 90.4% 90.2% 90.0% 89.9% 89.5% 89.2% 88.2% Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 E-commerce Offline retail 4,845 390 126 54 2019 Other Smartphone PC In-store 

But in-store sales aren’t growing fast enough to keep the doors open 2,600 1,700 1,300 2,800 6,100 4,400 3,900 2,500 2,100 1,800 3,100 5,100 2,400 7,800 5,500 9,271 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 YTD Total announced store closures in the US Note: 2019 closures are as of November 29, 2019. Source: Business Insider, CNBC, USA Today, Credit Suisse, Yahoo Finance, Coresight Research 

A major focus point for retailers is in-store product discovery Source: Dunnhumby, Business Insider Intelligence Store layout and appearance Data collection Personalized experiences Example customer journey 

Industry Uptake Size Of Business Impact Research Assessment (Early days of testing) Trialing (Tested in a fraction of stores) Mainstream adoption Low High And there’s a bevy of technologies retailers can consider to help Source: Gartner, Business Insider Intelligence Algorithmic merchandise optimization Customer-facing in- store self-service applications Unified merchandise planning Real-time store monitoring platform Autonomous inventory management and cleaning robots Virtual reality retail experiences Automated in-store order collection Augmented reality in- store product try-ons Mobile augmented reality that presents product information Blockchain-driven product histories 

Industry Uptake Size Of Business Impact Low High Of those on the cusp of mainstream, a few technologies hold the most promise Source: Gartner, Business Insider Intelligence Algorithmic merchandise optimization Customer-facing in- store self-service applications Unified merchandise planning Real-time store monitoring platform Autonomous inventory management and cleaning robots Virtual reality retail experiences Automated in-store order collection Augmented reality in- store product try-ons Mobile augmented reality that presents product information Blockchain-driven product histories Research Assessment (Early days of testing) Trialing (Tested in a fraction of stores) Mainstream adoption 

Robots can be used to keep aisles clean and well stocked Robots can keep stores clean, facilitating longer customer visits, which aids product discovery. Robots can manage inventory tracking, ensuring that products are on shelves for customers to find. Source: Walmart, Bossa Nova, Brain Corp., ARC as cited by Forbes Example • Bossa Nova Robotics’ signature device is being deployed in 350 Walmart stores. • Can scan aisles with 94% accuracy. Industry average for inventory- scanning accuracy in-store is 88%. Example • Brain Corp’s robots were planned to be in 1,860 Walmart stores by February 2019. • Without Auto-C, store associates have to spend 2 hours per day cleaning floors. 

Store-monitoring tools can also have a big impact on the shopping experience 

Shopper data can be collected in many ways Example technologies for capturing customer data Camera networks Beacons and geofences Facial recognition + cameras Required logins at cashierless stores Voluntary Wi-Fi logins Apps In-store tracking In-store recognition 

And better data can improve aspects of the store experience, like advertising and store layout Info used for different purposes Ads Product selection Store layout Consumer moves around store Location and actions are tracked Data gathered from shopping behaviors 

The shopping data creates a virtuous cycle, as each shopping visit generates insights that improve the next Locations/ actions tracked Data gathered from shopping behaviors Ads/product selection/ store layout tweaked Consumer begins shopping 

Finally, technologies like sensors, data, and robots can make stores easier to browse 

But technology can also help stores take advantage of brick-and-mortar’s greatest differentiator: human associates 

Employees armed with devices are better equipped to answer customers’ questions of associates agree consumers are better connected. of associates say tech- equipped associates would improve customer service. of shoppers feel they are better connected than in- store associates. Source: Zebra, n=5,000 global shoppers; n=1,000 global retail associates, 2019 56% 74% 51%