IBM Retail | Turn Insight Into Action:Point of Sales Systems Analytics


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Mining through droves of data for consumer shopping patterns and market insights can make or break a retail company. Market Basket analysis using IBM's Point of Sales System helps smart retailers deploy effective targeted product offerings that generate significant revenues. Find out more on how IBM clients drive higher returns from more precisely targeted campaigns.

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IBM Retail | Turn Insight Into Action:Point of Sales Systems Analytics

  1. 1. Data Sheet IBM SPSS Retail Market Basket Analysis Leverage POS data to understand sales patterns, customer preferences and buying patterns to create targeted and profitable promotions Overview Solution description “ Multiple purchases Bulk transaction data as a within Category W are high-value asset Retail operations generate a vast common, and customers In today’s highly competitive world, retailers struggle to differentiate amount of Point-of-Sale (POS) who make these themselves via their product offerings transaction data. The sheer bulk of purchases also tend to and by how they promote products to this transactional data – recording, at buy Product T.” customers across all channels. Smart the item level, every purchase through retailers deploy effective targeted stores, on-line store fronts, and other SPSS algorithms are highly scalable product offerings which can generate channels – makes it very hard to and able to process huge amounts significant revenues; poorly chosen understand the repeated patterns of of POS data efficiently. Our solution ones, though, waste money and purchase that give insight into customer includes powerful tools to let retailers opportunity. behavior and preference. browse and explore the associations discovered and decide which are the Retail operations generate huge In Market Basket Analysis, smart most relevant and potentially lucrative amounts of transactional algorithms analyze huge quantities to apply in their business. information, holding a wealth of of transaction data to reveal detail on product purchase “associations” – the patterns which Turning Insights into Action patterns. The sheer volume of data, show the linkage between products These patterns can drive decisions however, makes those patterns typically purchased together. Typical on how to differentiate assortment, obscure and impossible to detect by insights might be: merchandise stores and to develop manual inspection. combined offers of multiple products, “ Products A and B tend and within and across categories, to If retailers have insight into these to be bought together.” drive sales and profits. They can be patterns, they can ensure the implemented across an entire retail products they offer and promotions chain, by channel, or, if the data is “ If Products C, D and they run match shopper preferences analyzed at the store level, specific and behavior, and give maximum F are purchased, it is offers can be formulated and rolled out return on their marketing spend. extremely likely the at a local level. Retailers able to link purchases to customer will also buy individual purchasers can take this Product E.” even further, tailoring offers to specific customer segments and driving higher returns from more precisely targeted campaigns.
  2. 2. Offers might be implemented through • Interaction information that The high level of personalization of in-store displays. For example, two describes how they interact with the these offers, and the fact they are products showing a strong tendency retailer – for example, their use of based on robust predictive models, to be purchased together can be on-line facilities (e.g. e-commerce delivers high conversion rates and stacked together, with a special “buy and “loyalty club” websites) and increased revenue per shopper and both for…” offer encouraging combined order or service hotlines. per visit. purchases. • Attitudinal information that describes why they do what they Empower decision makers Alternatively or additionally, coupons do, such as satisfaction scores or SPSS Market Basket Analysis is based on these offers could be sent out net promoter scores, or ecological delivered to business users in the form of in a weekly mail drop to all households or other attitudes captured in dashboards, reports, alerts, and analysis in each store’s catchment area, surveys and in feedback at points of provided by IBM Cognos 8 BI. This encouraging store visits as well as the interaction. allows marketing and merchandising desired shopping behavior. executives to understand sales Apply predictive models to identify patterns, customer preferences and Getting Personal the most appropriate offers for each buying patterns so they can improve These offers, however, are “one size fits individual customer product sales and margins, and create all”. While they may generate significant SPSS algorithms analyze the whole targeted and profitable promotions. revenues by leveraging common range of customer data, relate that to The combination of IBM Cognos 8 BI purchasing tendencies, they don’t previous purchases, and build predictive and SPSS provides a complete view of differentiate between customers who models that for any customer and historical performance coupled with a may have different preferences and potential offer can be applied along with predictive view of the future. propensities to respond to different offers. business rules and other analyses to: A common integrated platform allows Retailers who have a closer relationship • Decide whether that offer is valid for for a single version of the truth to be with individual customers – for example, that customer disseminated throughout the retailer, through a loyalty card scheme or • Predict the probability that the unlocking data from silos within the on-line shopper registration – can refine customer will respond to that offer organization. This allows chains to this approach. In this case, they can • Calculate the value to the retailer of seamlessly combine information that combine analysis of all customers’ the customer accepting that offer was previously time consuming to pull shopping patterns with information on together, error prone, and in many the individual customer’s shopping Applying these models across offers cases led to decisions made on intuition habits. This behavioral information can enables retailers to select the best set as opposed to objective and data then be combined with any other data of offers for each customer or customer driven, which most retailers held on the customer, for example: profile. These are then delivered to the drive toward. customers in the most appropriate way. • Descriptive data, combining self- For example, loyalty card holders might These capabilities enable retailers to declared data with any bought-in receive several coupons enclosed with slice information in meaningful ways geo demographics based on ZIP or their monthly statement. in order to isolate specific challenges postal code or identify areas of opportunity. 2
  3. 3. This allows merchants, marketers, About SPSS, an IBM Company operations and others managers SPSS, an IBM Company, is a within the retail organizations to quickly leading global provider of predictive analyze mountains of information to analytics software and solutions. © Copyright IBM Corporation 2009 not only understand what happened The company’s complete portfolio of IBM Canada in the past but what they should be products – data collection, statistics, 3755 Riverside Drive doing going forward from a common, modeling and deployment – captures Ottawa, ON, Canada K1G 4K9 integrated IBM platform. people’s attitudes and opinions, Produced in Canada November 2009 predicts outcomes of future customer All Rights Reserved. Benefits interactions, and then acts on these IBM, and the IBM logo are trademarks of • Better understanding of customer insights by embedding analytics International Business Machines Corporation in preferences the United States, other countries or both. into business processes. IBM SPSS For a complete list of IBM trademarks, see • Increased basket size, with greater solutions address interconnected revenue per customer visit. business objectives across an Other company, product and service names • Higher product sales and margins may be trademarks or service marks of others. entire organization by focusing on through differentiated product References in this publication to IBM products the convergence of analytics, IT or services do not imply that IBM intends to offers. architecture and business process. make them available in all countries in which • Greater return on marketing spend IBM operates. Commercial, government and (product promotions, in-store offers, Any reference in this information to non-IBM academic customers worldwide rely on Web sites are provided for convenience targeted offers to web shoppers and IBM SPSS technology as a competitive only and do not in any manner serve as an loyalty card holders). endorsement of those Web sites. The materials advantage in attracting, retaining and at those Web sites are not part of the materials growing customers, while reducing for this IBM product and use of those Web sites is at your own risk. fraud and mitigating risk. SPSS was acquired by IBM in October 2009. For further information, or to reach a representative, visit com/software/data/ DOC NUMBER