After the big bang. How retailers can harness the big data explosion. A report from the Economist Intelligence Unit. Sponsored by

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1 After the big bang How retailers can harness the big data explosion A report from the Economist Intelligence Unit Sponsored by

2 After the big bang: How retailers can harness the big data explosion Savvy retailers are avoiding a race-to-the-bottom by using big data to win customer loyalty The potential to profit from big data massive sets of data that are accumulating at hyper speed in the digital era looms large for businesses today. But what does it mean for retailers vying to win and hold on to customers who are themselves hugely empowered by digital information? Some retailers may conclude that the data deluge is overwhelming, shrug and stick to their knitting. But those retailers that face the challenges, raise their game and harness this explosion of information are enjoying unique opportunities. Indeed, in time, the line between the data haves and data have-nots will likely be the line between retail s winners and losers. Where we are today The good news is that retailers are ahead of other businesses in recognising the potential of big data, which some 93% are already leveraging, compared with 84% of businesses in other sectors. That is according to a survey of 752 executives conducted by the Economist Intelligence Unit in March 2012 as part of a larger big data research programme sponsored by SAS. The findings remain fully valid today, according to our research. Retailers are, however, more likely to express concern about data security, perhaps because of the sensitive consumer information they often possess. Only 43% of respondents in retail organisations say they have the security infrastructure needed to exploit their data, compared with 51% of respondents overall. They are also far more likely to cite security concerns as the main impediment preventing them from adopting cloud computing and data storage. This may be hurting their profits; 29% of companies that say they outperform their peers on profitability also say they have a welldefined strategy for the cloud, compared with just 11% for underperforming companies. In addition, retail s ability to process big data is stalling. Half of retailers say the speed at which they are processing data has stayed the same over the last three years, compared with 34% for business more widely. The hold-up is not technological; it is cultural. The gap between what the best companies are doing and what retailers are doing points the way to an advantage for early movers. Where the best retailers are leading the industry Savvy retailers armed with the right data and algorithms now regularly offer personalised promotions and tailor their marketing by using data gleaned from, potentially, billions of transactions. For instance, Kroger, the US grocery group, uses its loyalty-card data to mail personal offers to customers based on what they like and are likely to buy. This means the costly one-size-fits-all 1

3 Where has your organisation benefitted from the data produced by smart systems? Where could it see benefits? (% of retail respondents) Have seen benefits Has potential benefits Operational efficiency Customer experience Strategic decision-making Customer service Regulatory compliance Systems for identifying and developing new products and services Go-to-market speed Source: Economist Intelligence Unit survey The Holy Grail for us is [understanding] what someone is looking for before they have bought it. Steve Willett, Kingfisher s chief executive for group development 2 sale event is often replaced by a more precise, targeted approach. Kroger also uses big data to stock its shelves with the products that its best customers want, thus rewarding their loyalty. If we didn t have the data, we could look at how many people bought a particular brand, and make decisions based on that, says Christopher Hjelm, chief information officer. But key questions would remain unanswered: Were those customers buying it because it was on promotion or a special price? Are the customers buying this product loyal, good customers? Unsurprisingly, online stores are at the forefront of using data. FreshDirect, a New York online food retailer, cannot rely on a product catching a shopper s eye while wandering the aisles. But it can continually rearrange its online store around the customer s preferences. If a shopper selects a steak, the site can supply ideas for a worthy side dish, based on that person s past purchases and those of other shoppers. To do this, FreshDirect leverages data that ranges from things that relate to the shopping trip that the customer is currently on, to insights from past trips, to models of customers who are similar in an array of different ways, says John Leeman, chief marketing officer. Kingfisher, the UK home-improvement retailer, is determined to know its customers, however they shop. It is shifting to a single technology platform that will channel all sales online, online for store collection, by telephone or in-store and create a single profile of the customer. The system is being rolled-out from its Screwfix business, which already offers customers tailored offers based on triggers gleaned from their purchase histories. We try to identify if someone is doing a [homeimprovement] project, but we also try to identify someone s propensity to do a project, says Steve Willett, Kingfisher s chief executive for group development. Kingfisher then entices the customer to buy related items. On the horizon and beyond The next frontier for many retailers is social and mobile. Retailers are particularly eager to mine data from social networks more effectively, for the real-time insights they can offer into what customers are thinking. However, unstructured social data can be difficult to integrate into customer relationship management (CRM) systems and challenging to analyze in an automated fashion. Social and mobile represent two great opportunities for us, says Ryan Davis, senior director for customer relationship management at Abercrombie & Fitch. If you think about our target customers day-to-day lives, it s just a natural step. That s where we would place some of our big bets

4 in the hope of delivering personalised messages to customers quickly and easily. For Kroger, the frontier is location-based mobile targeting. It is piloting a technology in stores in Cincinnati that allows it to provide offers relevant to customers when they are in the correct aisle of the store, says Mr Hjelm. We re going to see massconsumption within the next 24 to 36 months. It s going to come fast and serious, because consumers are going to want it. Many retailers would also like to use big data to improve cross-selling. But some experts believe their effectiveness will be limited, because heavily relied-upon transaction data come too late in the customer s shopping journey. For big ticket spending especially, a transaction may be the final act in a process that began weeks or months earlier. The big question is: can retailers recognise browsing habits and respond pre-emptively? The Holy Grail for us is [understanding] what someone is looking for before they have bought it to identify what they re attempting to do, says Kingfisher s Mr Willett. Conclusion Too often, retailers cast the Digital Age as a raceto-the-bottom, in which consumers are encouraged to find the cheapest option with the stroke of a touch screen, making it nigh on impossible to preserve profit margins. But retailers at the vanguard are using big data to win customers loyalty by providing greater convenience and more salient offers. In an age of price transparency and increasingly capricious consumers, only retailers who take data seriously will be in control of their fates. So what does an embrace of big data mean for the retail executive? Will data scientists replace the traditional, instinct-led retailer? That seems unlikely. What is clear is that data must be allowed to escape the IT department and flow to other departments if retailers are to benefit fully. But vision and strategy come first, executives insist. Data are a means, not an end. 3

5 Whilst every effort has been taken to verify the accuracy of this information, neither The Economist Intelligence Unit Ltd. nor the sponsor of this report can accept any responsibility or liability for reliance by any person on this white paper or any of the information, opinions or conclusions set out in the white paper. Cover: Shutterstock 4

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