Big Data Management and Predictive Analytics as-a-service for the Retail Industry

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1 Big Data Management and Predictive Analytics as-a-service for the Retail Industry

2 Serendio Predictive Analytics for the Retail Industry 2 Executive Summary The biggest and most successful retailers today, guys like Amazon, ebay and Apple have long been increasing response rates to their offers and driving profitability by using Big Data and predictive analytics to make relevant, personalized, and precisely timed offers to their customers. Until recently, only the big guys could afford the vast investment in technological and human resources required to store, manage and analyze the massive amounts of customer data that enables them to treat every customer as an individual based on insights into their preferences and future behavior. By 2014, 30% of analytic applications will use proactive, predictive and forecasting capabilities. Gartner Forecast However, a few nibble start-ups are now leveraging the latest advances in public and private cloud computing - and a few brilliant Data Scientists with retail domain expertise by offering Big Data Management and Advanced Analytics-as-a-Service solutions to small and mid-sized retailers - as well as the giants of the industry. These solutions are not only affordable for the small and mid-sized retailer, but also provide all the technological and advanced analytics capabilities that the big guys have been using for years to build and maintain their competitive advantage. Companies like Serendio, based in Santa Clara CA, help retailers increase profits and reduce costs by eliminating the overhead and burden of building managing and maintaining the IT infrastructure to collect, aggregate and analyze massive amounts of internal transactional and 3rd party raw data. They then apply their extensive background in retail operations and data science to filter out the noise and transform raw data into actionable insights. Predictive modeling is used to identify and exploit the not-so-obvious patterns hidden within the data that can be leveraged to make profitable business decisions By taking advantage of the capabilities of Serendio s predictive analytics, retailers can more easily acquire and retain customers, optimize merchandising assortments, and better understand the true demand for their products. Retailers can then identify those variables that have the most significant impact on business performance and customer behavior and leverage them to their advantage. The tremendous value of the Serendio service-based model lies in achieving the economies of scale and scope necessary for identifying actionable insights and building flexible predictive models that can be leveraged across multiple channels. Models are continuously tuned and maintained by Serendio to operate at maximum efficiency against an ever increasing volume, variety and velocity of data - all with no investment in IT infrastructure on your part, or the expensive human resource of hard to find, and even harder to hire, data scientists. The US will face a shortage of 190,000 people with analytical skills by 2018 expect demand for data scientists to outstrip availability over the next five years. McKinsey Global Institute

3 Serendio Predictive Analytics for the Retail Industry 3 Experts Speak and Agree! For years predictive analytics has been suitable only for a limited audience with expertise in statistics and math. But today that is changing. In a recent survey of dozens of retail technology vendors, Retail Touchpoints asked for predictions on what the future of retail technology holds for the next several years. There was overwhelming agreement that Big Data and predictive analytics will revolutionize the industry. Here are a few samples of where the leading experts in the field of retail technology see the industry headed. In 2013 mobility and Big Data analysis will have the largest impact on the retail industry. Dick Cantwell VP, Internet Business Solutions Group for Retail, Cisco Recent research from Cisco confirms that we re now in an era of mobile commerce. Whether at home, on the go, or in a store, shoppers increasingly are accessing the Internet through smartphones and tablets for product research or to complete transactions. In addition, we re now in an era of Big Data as a competitive advantage. Retailers now routinely gather both structured (POS, as an example) and unstructured (for instance, WiFicaptured store traffic flows) data, and are able to rapidly obtain new and deeper insights into consumption trends and shopper behavior. In order to remain competitive with a growing variety of shopping alternatives, retailers must seek new ways to deliver the most value, revenue and loyalty. To do so, they must harness the increasing volume and availability of data using technology to process large amounts of data into meaningful reports and insights as quickly as possible. Consumers have become more comfortable sharing information digitally and online than most will in person. While retailers all had an eye on the customer in 2012, how we take action based on this vast amount of customer information across channels will be the focus for Aside from historical transaction data already in-house, retailers now have access to an amazing amount of social data. This unaided information allows retailers to get a glimpse into what customers want in terms of offerings, marketing promotions and services, which products work and which don t, what offerings customers want in the future and even when and how they plan to spend their money.

4 Serendio Predictive Analytics for the Retail Industry 4 Predictive analytics and big data will be another technology focus area in Brendan O Mear Managing Director, Worldwide Retail Sector, Microsoft Corporation The opportunity for retailers is in finding the right tools and technologies to pare down and analyze data, get more granular and then define proactive campaigns to maximize customer interactions across all channels a true multichannel approach based on real data. This strategy, which combines the power of predictive analytics with the ability to personalize the shopping experience for individuals, is the key to getting closer tocustomers, driving purchases and increasing revenues. Already today we can gather and analyze social data. We can target promotions to select customers based on purchase data. We can personalize online marketing messages based on search history. Retailers that are able to integrate all aspects of that data into actionable and relevant campaigns that anticipate and deliver on customer shopping needs will be the big winners in It s an old truism that retail starts and stops with the shopper. Understand why shoppers behave the way they do and you can inform and influence their shopping behavior. Influence their buying behavior and you can get them to spend more at your store and less at your competitor s store. Sales go up, out of stock go down and all stakeholders are happy. a Big Data approach that integrates traditional sources of information like the transaction log and ASNs with social media and other unstructured data gives the retailer a quick and true picture of the business. Tim Simmons VP, Global Industry Marketing, Retail, Travel, Hospitality & Transportation, Teradata Unfortunately, shoppers are fickle and unpredictable, and they are constantly changing their minds and the way they shop. The advent of mobile marketing adds to an already crowded mix of options for information that includes television, print, Internet and more. This

5 Serendio Predictive Analytics for the Retail Industry 5 makes the retailer s job of buying what is going to sell less intuitive and more dependent on data-driven insight. It is clear that the omnichannel world of retailing is requiring marketers and merchandisers adjust the way they attack the point where there is a consumer interaction. They need to message and promote to that segment of one to gain ultimate relevancy. And along the way they still need to do the basics of adjusting assortment to local market, optimizing replenishment and anticipating challenges throughout the supply chain. The question has become How can I better understand and engage the shopper? the power of predictive analytics with the ability to personalize the shopping experience for individuals is the key to getting closer to customers, driving purchases and increasing revenues. Lori Mitchell-Keller Vice President and Head of Global Retail Industry, SAP While there is no panacea for this new world of retailing, there is something that s close a Big Data approach that integrates traditional sources of information like the transaction log and ASNs with social media and other unstructured data to give the retailer a quick and true picture of the business. By providing the marketers and merchandisers with the technology that delivers a full view of the potential impact their programs will have on sales and profits, retailers can close in on the goal of giving shoppers what they want, when and where they want it. Innovative retailers will use Big Data analytics to derive intelligence from the new and emerging data types that had previously strained their systems. While creating the new applications for analysis of multi-structured data requires a strategic investment in specialized resources and tools, the payoff is immense. The technology will help brick and mortar retailers to effectively combat the challenges of showrooming. It will help e-retailers enhance their personalization of offers to customers. And it will help multi-channel retailers cross-sell a mobile shopper who happens to be in a physical store. Using advanced analytics technology is critical to leveraging data to improving the promotional interaction with shoppers. The use of a data warehouse to analyze both structured and unstructured data is critical for all retailers with the goal of being the store of choice for shoppers. By using Big Data analytics to better understand behavior, retailers will optimize the way they go to market because shoppers are not committed to a specific store or online retailer-they will go to wherever their needs are met best.

6 Serendio Predictive Analytics for the Retail Industry 6 Big data presents both an opportunity and a threat to retailers. Those companies that are able to capture and analyze complex data streams to extract new insights with precision will have a major advantage over their less-informed competitors. On a positive note, I believe more retailers will realize the need to integrate the varieties of data to create insight for personalized experiences on any and every channel. Conclusion Predictive analytics within the retail industry can be used for many business objectives. For instance, predictive analytics can be used to better understand the purchasing behaviors of your customers, to help you understand your high- and low-margin customers, to help you understand which customers are most likely to respond to a marketing campaign, or to help you identify which customers are likely to leave. Predictive analytics can enhance and amplify the knowledge of all of your assets, from customers to suppliers to employees, and even the presentation of merchandise within the store. To stay competitive, retailers must understand not only current consumer behavior and past trends, but must also be able to accurately predict future consumer behavior. As retailers add more data to their analytic efforts, they increase the number of decision points for differentiating between customers and making more targeted decisions. But just as having lots of data can be overwhelming and of little value in and of itself, so it is with the analytic predictions drawn from Big Data. Their business value depends on the retailer s ability to operationalize them. Retailers of all sizes are bringing analytics into their operations. The key to making choices and investments that deliver on expectations is to understand what various types of analytics do and how they fit (or don t fit) what the business is trying to accomplish. It s also important to think about analytics as an incremental process rather than a packaged solution. No one approach serves all purposes. Wherever a company is in the spectrum of analytic sophistication and experience, there s a next step to take to achieve even greater benefits. Serendio is changing the way retailers view Big Data and predictive analysis. Organizations large and small can now take advantage of a complete predictive analytics platform as a managed service offering. About Serendio Contact Us The name Serendio is derived from the expression Serendipitous Discovery. Unearthing the not-so obvious and seemingly unrelated from data-structured and unstructured, is a hallmark of our technology and our name merely reinforces that. Our Big Data Science solutions help in driving Decisions and Actions for a wide variety of businesses in Retail, Insurance, Media, Education, and Healthcare. Our mission is to help every Company transform itself into a Data-driven organization. Website: Headquarters: 4677 Old Ironsides Drive Suite 450 Santa Clara, CA United States Phone: Follow us on:

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