Fujitsu Statement January 2016

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As information-savvy online retailers move to the ‘offline world,’ the race to be among a new generation of ‘connected stores’ is now on, says Rowan Cape, Vice President, Retail Software Solutions at Fujitsu. We live in a world where we are accustomed to having information at our fingertips. Encyclopedia that used to fill shelves can now be accessed from devices we carry in our pocket. Whole industries have been reshaped by changes in access to information. In early e-commerce, new entrants outsmarted traditional retailers with business models based on information: they precisely tracked who visited their online store, their search journey, and what they eventually bought. Today’s e-commerce leaders are using aggregated customer information to start predicting customers’ purchases. Omni-channel retailers took these data-driven approaches on board for their online sales, but it is taking a long time to transfer that knowledge back to their physical stores – even though that is where quite often a lion’s share of all their sales deals are made1. Closing the knowledge gap Until fairly recently, store managers often knew little more than how many customers walked through their front door, and their departmental sales. This is in dramatic disparity to the level of actionable intelligence available to e-commerce vendors. The subsequent digitalization of in-store environments saw retailers adopting digital video cameras, sensors, even Wi-Fi. This, combined with the increase in customer smart phones and the usage of GPS, Wi-Fi and Bluetooth within stores, created the first ecosystems for in-store analytics. Despite the relatively short time since the introduction of these solutions, pioneers have already achieved a number of significant improvements to daily business processes. The cost for physical store space is under rigorous scrutiny, so the first initiatives typically looked to optimize operational costs and efficiencies. Actionable, real-time data on elements such as footfall, peak shopping times, and customer movements – linked together with conversion rates 2 – helps to distribute sales staff and products more efficiently. Real-life customer examples show that by getting this right, sales can jump by up to 20 percent. But to create truly future-proof business models, a customer-centric approach is needed to uncover the full transformative potential of in-store analytics. Adding a personal touch As the digital mind-shift continues, enterprise technology will be the primary catalyst for changes in the shopping experience. Big data will play an increasingly integral role in how stores’ customer interactions

enable new ways of shopping by engaging mobile platforms and elements of the Internet of Things, such as smart sensors. Retail is ready for the next act, and so is in-store analytics. Enter personalization, the next evolutionary step in a retail world less and less constrained by the boundaries of store walls. Retailers worldwide are getting a first glance of what the future holds as roughly half of all consumers want to receive real-time promotions (i.e., while they are in the store) but only 5 percent of retailers assessed have this capability. And only 40 percent of retailers assessed let customers redeem loyalty points both in store and online. 3

At the same time, we are already seeing loyalty programs being turned upside down. These days, new players have already started to reward customers simply for visiting stores rather than purchases. These are exactly the behaviors that intelligent in-store analytics systems track – how often, what times of day and whether they visit based on a promotion. Future programs could even reward customers for not paying visits to competitors But to really take these two approaches for personalized, in-store customer interaction to the next level, retailers require a more granular degree of individual customer understanding than could be derived from traditional methods. Measuring the immeasurable: creating a unique in-store experience to raise retailer brand profile And there is more: As store retailers are striving to build new competitive differentiators that change customer expectations, in-store analytics can provide hard facts to support critical decisions in the quest for customer mind and wallet share. Already sheer store size and the number of items stocked per square foot have become less of a priority versus providing a unique shopping experience. Retailers have taken different approaches to address this trend. Food retailers are trying to ‘season’ customer experience by adding live cooking islands, organic food options and pick-up counters for online shopping. With a higher cost-per-square-foot of retail space, sports retailers are now experimenting with ‘extras’ such as in-store rain cabins to test outdoor gear. Electronics chains are expanding service offerings beyond the traditional repair service – despite potential added staff costs. The goal is to get the customer through the door and into a mood to buy. After all, shopping remains a social and emotional experience! In-store analytics help retailers evaluate whether these enhancements are a customer magnet or a money drain. A timely 360-degree view of how well changes are accepted is very powerful. For example, store managers can now track initial and continuous increases in footfall in response to changes in floor space and layout. They can also get more

Fujitsu Statement January 2016

Better smart than sorry: intelligent in-store analytics for a new generation of connected stores Rowan Cape, Vice President, Retail Software Solutions

Fujitsu Statement January 2016

Page 2 of 2 www.fujitsu.com

data-driven clues as to why comparable stores perform differently. Using the store’s location-based services, retailers are able to record whether new merchandise selections or current promotions draw in a new client base or increase repeat visits from coveted regular customers. When customers opt into programs to receive personalized offers, the store managers can build up a rich profile and deliver much higher value directly to each shopper. Analytics also enable retailers to understand whether there is a sales increase if customers stay in stores for a longer period to browse4: advanced systems can link up the period of stay, individual customer hot spots and actual purchases. These detailed insights are especially valuable as former online pure players have started experimenting with offline stores to add perhaps the only element that e-commerce can’t (yet) provide: touching the actual products. As the field of offline and online retail competitors continues to expand, retailers need to grow by building on their assets – their stores, their customers and their data. Today, retailers have access to more comprehensive data than ever before about their business and their customers. Data management and data analytics are maturing and expert knowledge and trusted partners are available to help pave the way to maximize the value of the available data and to act in real time on that insight to best effect. It is time to use smart in-store technology to focus and respond to facts rather than a gut feeling. Better smart than sorry!

Rowan Cape Vice President, Retail Software Solutions 1 For the US, for example, The Omnichannel Consumer Preferences Study summarizes the findings and input from a variety of retailers and property developers, and A.T. Kearney retail sector analysis. The independent survey of more than 2,500 consumers and dozens of retail executives was funded by, and completed in cooperation with, leading US shopping mall real estate developers. It states that for the US, today 90% of all US retail sales still occur within the four walls of a physical store. In comparison, eMarketer’s Worldwide Retail Ecommerce Sales: Updated Estimates and Forecast Through 2019 indicates that in 2015, retail ecommerce accounted for just 7.1% of all retail sales in the US, while in Western Europe, 7.5% of retail sales were transacted online. 2 Traditionally an e-commerce benchmark, the technical term conversion rate means converting online site – or in this case in-store – visitors - into paying customers 3 Source: Accenture Seamless Retail Research Report 2015: Maximize mobile to increase revenue, downloadable from accenture.com 4 Also known by the technical term dwell time