White Paper Your Customer is Talking, Are You Listening? Faced with all the 'noise' and vast quantities of data generated through the fast growing retail systems, the pertinent question to retailers today is, 'Are you really listening? Weighed down by the quantity of data, retailers might be missing out on qualitative insights from data, which are essential for customer-focused merchandising, promotions and driving sales. This whitepaper discusses how analytics could help retailers in analyzing data collected from customers to build strategies that are more meaningful and relevant to customers and other stakeholders.
About the Author Shalini Rajan The author is a Subject Matter Expert in Multi-Channel Retailing and manages Brand Building activities within TCS Retail BPO domain. She has over 14 years of experience, which includes advertising, brand building and technology marketing. The author can be contacted at rajan.shalini@tcs.com. 2
Table of Contents 1. Introduction 4 2. Information or Noise? 4 3. Opportunities for Retailers 5 4. Information Imperatives for Retailers 5 5. Qualitative Perspective to Data 7 6. Conclusion 8 3
Introduction Eric Schmidt, the CEO of Google recently said, "Every two days, we create as much information as we did from the dawn of civilization up until 2003. The real issue is user-generated content. Retailers are also finding it difficult to make sense of the plethora of information generated through a retail transaction considering the various channel options and customization possibilities. The retail industry is undergoing a transformation as information regarding various products and customers purchasing behavior is growing exponentially. Information or Noise? New sales channels and additional customer touch points are leading to a profusion of data. Websites, mobile devices and social networks are the new media of interaction between retailers and customers, and also among various customers. Earlier the traditional data collected from Points of Sale (PoS) was the only source of information, but today data points such as items bought, volume, stores visited, are needed to understand the retail customer. Word of mouth has attained a completely new significance. Today, due to the amount of customer data that is available, we have come back full circle to the days where the corner shop grocer not only greeted us by name, but also set out our purchases even before we asked since he knew our habits and preferences so well. Now even big retailers can personalize their interactions with customers by understanding and using the customer data. Retailers are collecting information on customers from both traditional and emerging sales channels and customer touch points. According to a recent research by RSR Research, the primary source of customer data is still in-store, followed by email, e-commerce site and social networks. Consumers are also exposed to a wide variety of media through which they can access retail information. However, they can curate information sources either through search engines or smart mobile device apps. Consumers now have the power to control when, where and how they engage with their favorite brands, according to Phaedra Hise in the January 2012 issue of the loyalty marketing journal Colloquy, and instead of turning to companies for information, they increasingly rely on each other for recommendations in an explosion of customer-to-company and customer-to-customer discussions. Traditional retailers invested in legacy systems are unable to tackle the dynamics of e-commerce and agile competitors. These retailers consider this plethora of information as noise since they do not have adequate systems and processes to gain insights from this information. They are failing to address, analyze and integrate a host of new data sources such as social networks and location-based data from mobile devices. They are still pre-occupied with understanding the impact of e-commerce and m-commerce technologies and protecting their turf at physical stores. In the process, they are not paying attention to their consumers who are actually giving them answers to critical questions that can guide their merchandising, marketing, channel and pricing strategies, such as: What they want to buy? Why they are buying it? How much do they want to pay for it? What else do they want? 4
Opportunities for Retailers Customers are sharing more information about themselves and their purchasing behavior in public forums, providing retailers and product marketers a complete pattern of their preferences. Retailers, on the other hand, not only have new sales channels but also have new ways to fill in the gaps in the current shopping experience, like instant catalogs and sharing of product recommendations. They are exploring opportunities to provide additional customized product and service information to customers in preferred formats. Retailers are also able to measure the impact of their activities and get feedback on every aspect of business from merchandising to promotions to pricing thus localizing and customizing products, presentation, channel or store. Therefore the retailers are able to get: 1. More targeted promotions 2. Meaningful consumer insights 3. Accurate forecast of outcome of campaign and promotional offers 4. Localization and customization of merchandising at store level Information Imperatives for Retailers The huge amount of customer purchase information generated needs to be managed, compelling retailers to make changes in their business operations. These changes can be brought about by the use of certain analytical tools across the retail value chain. Buying & Category Management Promotion & Campaign Mgmt Retail Value Chain Supply Chain & Inventory Mgmt Store Operation Customer Relationship Mgmt Brand contribution Analysis Channel Profitability Inventory Forecasting* Market Basket Analysis* Promotion Response Promotional Planning Support Sales driver analysis Return Analysis Out-Of-Stock Analysis* Customer Profiling & Segmentation* Price Management Product - Channel Affinity* Supply Chain Efficiency Analysis Shelf Life Analytics Customer Behavioral Analytics* Demand Forecasting* Campaign Performance Analysis (Lift Channel etc) Logistic Planning & Analysis Store Clustering* Promotions Management Analytics* Product Affinity Analysis* Customer satisfaction, complaints analysis Churn model* Figure 1: Use of Analytical Tools across the Retail Value Chain 5
Using the tools /models mentioned in the diagram, retailers can bring about the following changes in their operations thus capitalizing the enormous value that can be derived out of relevant customer data. 1. Integrate External Customer Data Sources with Internal Purchasing Information This would give the retailer a very good idea of every single customer - the stores they shop from, the product categories that interest them, their demographic data, their overall value to the retailer and most importantly the opinions, views and recommendations of these customers in public forums. This can be effectively done through merging information collected from social media networks and POS data. Service providers with experience in customer profiling and segmentation, customer behavioral analytics, social media analytics can use insights from these analytical tools and combine them with POS behavior of a particular customer to provide a complete picture of every customer. This can be then effectively used for merchandising and promotional strategies. A specific example of how this can be done is through Recency Frequency Money (RFM) analysis. By analyzing customer behavior through data from POS transactions and customer profiling, retailers can target specific offers at customers who are more responsive thus increasing promotion response rate, saving promotional costs and increasing sales and profitability. 2. Apply Online Analytics Techniques to Brick n Mortar Retailing Strategies used to analyze online buying behavior can also be applied to physical retailing to analyze the why and how of shopping. The techniques of online traffic analysis, that is, what brought customers to a website and the pages they visited before making a purchase or abandoning a shopping cart can be used to analyze campaigns and promotions that bring customers to stores, the areas that they cluster around and the purchases they make. Online traffic analysis is carried out through deployment of relevant technology with analytics built into the system. Interactive digital signage and facial recognition technologies are aggregated with store and customer data to provide insights into the retail strategies that are working. Sales Driver Analysis, Product Channel Affinity, Churn Analysis are some of the tools that could be used for understanding brick n mortar customers. A specific example for this is Market Basket Analysis, which facilitated upsell and cross sell similar to e-commerce channels. This is a model for product bundling which also enables cross-selling and upselling through analysis of purchase behavior and identifying products that are bought together. This analysis provides insights on fast and slow moving products for product bundling and joint promotional activities thus influencing basket size and contents. Traditional retailers can improve their profitability using this model. 3. Customize Messaging and Messaging Channels Retailers cannot afford to send the same communication to all customers through all channels. They should understand each customer s preferred channel of communication, type of promotions that would appeal and product categories that customers are interested in. Both smart phones and tablets can be used for locationand action-triggered promotional events. For example, Best Buy offers specific promotions to shoppers who scan product barcodes in the store to their mobile devices. 6
Tools such as customer profiling and segmentation merged with earlier purchase behavior can help retailers develop customized promotions that will ensure more focused walk-ins to the store with better conversions. With intelligent use of the available data retailers can then predict what customers would need in the near future and how to persuade them to visit a particular retailer to make a purchase. 4. Use Metrics that Reflect New Data Realities Retailers need to identify the key performing indicators (metrics) to capture data that reflect the purchasing realities. Measuring incremental sales alone will not help retailers to understand the effectiveness of campaigns and promotional offers. What brought customers in? What all did they purchase? Why they didn t purchase? What sort of customers purchase? These are typical data points that would give retailers insights about their operations. Retailers today have all possible information about their customers, and the key is in choosing the right kind of metrics that will help define strategy and not getting bogged down by the information overload. For instance, in Product and Customer Profitability Analysis POS data aggregation of profile customers and products on revenue and margin performance will enable strategies to improve the contribution and margins of low-performing products. 5. Partner with Service Providers for Managing and Understanding Data Analysis of various data points can be a challenge for the retailers. Retailers cannot afford to invest in resources and skill sets and add to the burgeoning costs of retail operations. They would benefit by partnering with a service provider who has the expertise and the experience to provide similar services across multiple retailers. The new S2P implementation will require training both for use and associated workflows. That training should not be delivered in isolation; instead it should be part of communicating the new strategy and perceived best practice. That training also needs to reflect new roles, remits, responsibilities and relationships. S2P implementation, therefore, needs to be seen as a strategic procurement opportunity to introduce more effective approaches as opposed to making existing processes more efficient. Qualitative Perspective to Data Analyzing quantitative data without understanding the qualitative basis is not enough. Social Media success is not about the number of likes on Facebook or the number of Twitter followers. What would be deemed as success are the tone, quality and quantity of the number of positive interactions that happen through these channels. Technology alone will not help in this sort of analysis. The need to analyze both quantitative and qualitative data adds multiple levels of complexity which needs the services of expert retail and consumer behavior analysts, who bring together data generated through all collection points to form patterns, insights and thus make recommendations. Relevant and updated models are necessary to make sense of the humongous volumes of data in the system, and thereby listen to the customer. 7
Conclusion Retailers must listen to their customers despite the complexities and challenges of new technologies and sales channels. The January 2012 Deloitte Global Powers of Retailing report states that, the retail industry is evolving quickly in its data analytics capabilities and in its ability to develop personalized marketing campaigns and customer experiences. The ongoing challenge for retailers will be how to best analyze all this rich data and derive from it valuable insights about what consumers want and need. Consumers are proactive in interacting with retailers regarding who they are, what they want and do not want. Retailers not only need to harness this information with the help of technology and business processes but also partner with service providers, who not only help in managing these huge volumes of data but also help retailers understand the data and form meaningful insights. These insights would define strategies for growth within the retail industry and thus ensuring that Retailers are finally listening to their customers. References [1] http://www.sas.com/industry/retail/customer-insight/index.html [2] RIS Roadmap Series: Roadmap to Effective Promotions Management [3] http://www.tgrasaneh.com/upload/articles/25.pdf [4] http://www.retail-week.com/customer-data-track-and-treat/1947852.article 8
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