Analytical Customer Relationship Management

• Structured and unstructured data
• Data integration, warehousing and marts
• Knowledge management

• Analytics
• Three ways to generate analytical insight
• Privacy issues

Upon completion of this course, you will be able to understand:

• The central role of customer-related data in the achievement of CRM outcomes.
• The importance of data quality to CRM performance.
• Issues that need to be considered in developing a customer-related database.
• How data integration contributes to CRM performance.
• The purpose of a data warehouse and data mart.
• Uses of knowledge management systems in CRM.
• How analytical CRM supports strategic and operational CRM.
• How analytics support customer management strategy and tactics, throughout the customer lifecycle, in the sales, marketing, and customer service functions.
• How standard reports, OLAP and data mining generate insights for CRM users.
• The data mining works in a number of ways: by describing and visualising, classification, estimation, prediction, affinity grouping and clustering.
• The types of analytics that apply to structured, unstructured and ‘big’ data.
• The three V’s of big data.
• Why it is important to understand the differences between nominal, ordinal, interval and ratio data before selected analytical procedures.
• The types of regulatory constraints that regulators impose to ensure the privacy of customer data.