ACS 3907 E-Commerce Instructor: Kerry Augustine November 10 th 2015 CUSTOMER RELATIONSHIP MANAGEMENT (CRM) SYSTEMS Managing materials, services and information from suppliers through to the organization s customers 2 Information Systems Roles in the Value Chain Customer Relationship Management (CRM) Systems 3 1
Value Proposition Revisited 3 general categories of value discipline 1. Customer intimacy Really try to understand individual customer s needs Establish one-to-one relationships, very personal Key: personal service is an expensive commodity 2. Product leadership State-of-the-art products, leading edge Keep customers interested and excited Key: state-of-the-art technology is expensive to produce/achieve 3. Operational excellence Excels in operational efficiency, but usually no customization or aftersales support if it s not on time, it s on us type slogans Key: time is very valuable to people Understand where your business fits in, and how it interacts with its customers 4 Customer Relationship Management CRM = strategy for optimizing the lifetime value of customers Importance: widely held belief that it costs businesses 10 times more to recruit a new customer than to retain an existing customer Net churn metric: # Customers at Year Start # Customers at Year End x 100 # Customers at Year Start Simple (approximate) measure of customers lost 5 Customer Relationship Management (CRM) Systems Capture and integrate customer data from all over the organization Consolidate and analyze the data Distribute results to various systems and customer touch points across the enterprise Provide a single touch point for the customer. 6 2
Customer Relationship Management (CRM) Systems CRM systems examine customers from a multifaceted perspective. These systems use a set of integrated applications to address all aspects of the customer relationship, including customer service, sales, and marketing. 7 The major CRM software products support business processes in sales, service, and marketing, integrating customer information from many different sources. Included are support for both the operational and analytical aspects of CRM. CRM Systems (con t) 8 Operational and Analytical CRM Operational CRM: Customer-facing applications, such as sales force automation, call centre and customer service support, and marketing automation Examples: Campaign management loyalty programs (Groupon), e-marketing, account and contact management, lead management, telemarketing, teleselling, e-selling, field sales 9 3
Operational CRM Systems Sales Force Automation (SFA) Tools Sales Process/Activity Management Include a sequence of sales activities Guide sales reps through each discrete step in the sales process Helps increase productivity by focusing sales efforts on most profitable customers Sales process Opportunity Opportunity Generated Generated Lead allocated Prospect contacted Prospect qualified Solution identified Order placed Sales activity 10 Operational CRM Systems Customer Loyalty Management Process Map 11 Analytical CRM Systems Analytical CRM: Applications that analyze customer data generated by operational CRM applications to provide information for improving business performance Examples: Develop customer segmentation strategies and customer profiles; analyze customer or product profitability; identify trends in sales length cycle; analyze leads generated and conversion rates 12 4
Analytical CRM Systems Analytical CRM Data Warehouse 13 Analytical CRM Systems Help identify the most important customers, predict future buying patterns, and position the correct resources to increase sales 14 CRM Systems Business Value of Customer Relationship Management Systems Increased customer satisfaction More effective marketing and reduced direct marketing costs Lower costs for customer acquisition and retention Increased revenue from identifying most profitable customers and segments for marketing, cross-selling, upselling Reduced churn rate (Number of customers who stop using or purchasing products or services from a company) 15 5
CRM Systems (con t) SalesForce.com - Performance Measurement Metrics may include: Cost per lead Cost per sale Number of repeat customers Reduction of churn Sales closing rate Customer Lifetime Value (CLTV): Difference between revenues and expenses minus the cost of promotional marketing used to retain an account. 16 CRM Portal Portal 17 The Challenge of Big Data Massive quantities of unstructured and semi-structured data from Internet and networked services and applications Big datasets provide more patterns and insights than smaller datasets, for example: Customer behavior Weather patterns Requires new technologies and tools 18 6
Business Intelligence Infrastructure Array of tools for obtaining useful information from internal and external systems and big data Data warehouses Data marts Hadoop 19 Data warehouse: Database that stores current and historical data that may be of interest to decision makers Consolidates and standardizes data from many systems, operational and transactional databases Data can be accessed but not altered Data mart: Data Warehouses Subset of data warehouses that is highly focused and isolated for a specific population of users 20 Data Warehouses, Data Marts, and Data Mining Dept Data Source A Business Dept Data Source B Dept Data Source C Dept Data Source D Dept Data Source E Dept Data Source F Data Mart Dept Data Source G Dept Data Source H Dept Data Source I Customer Relationship Sales Department 21 7
Dimensional Modeling/ Analysis Multidimensional Data Model Using Data Mart The view that is showing is product versus region. If you rotate the cube 90 degrees, the face that will show is product versus actual and projected sales. If you rotate the cube 90 degrees again, you will see region versus actual and projected sales. Other views are possible. 22 Dimensional Modeling/ Analysis Multidimensional Data Model Using Data Mart Region versus Actual & Projected Sales PRODUCT East Nuts Screws Washers Bolts REGION West Central Actual Projected 23 Open-source software framework from Apache Designed for big data Breaks data task into sub-problems and distributes the processing to many inexpensive computer processing nodes Combines result into smaller data set that is easier to analyze Key services Hadoop Distributed File System (HDFS) MapReduce 24 8
Business Intelligence Infrastructure A contemporary business intelligence infrastructure features capabilities and tools to manage and analyze large quantities and different types of data from multiple sources. Easy-to-use query and reporting tools for casual business users and more sophisticated analytical toolsets for power users are included. 25 9