1. Chapter 4 Marketing Intelligence and Database Research

2. 1. What kind of relationships will add value to customers (e.g., loyalty programs, preferred customer status, etc.)? 2. What is the value perception of the customer segment, and how can the value be enhanced (e.g., direct communication to customers, new services, etc.)? 3. What products and services and mode of delivery have value to the customer segment (e.g., stock market alerts via Web-enabled mobile phones)? 4. What are customers’ responses to marketing and sales campaigns? Market Intelligence Questions 4-2

3. 1.Develop meaningful communication with customers. 2.Improve efficiency of market segmentation. 3.Increase probability of repeat purchase behavior. 4.Enhance sales and media effectiveness. Customer Database – Purposes 4-3

4. How products compare with the competition? Relationship between perceived value and price of the product? How satisfied customers are with the service level and support for the product? What are the comparisons among lifestyles, demographics, attitudes, and media habits among heavy, medium, and light users of the product? Other Questions Answered from Databases 4-4

5. Database Information Profitability Recency Frequency Affinity (Liking) Customer Characteristics Customer Characteristics 4-5

6. View the total process of database development as a commitment to a long-term data acquisition plan. View the data acquisition process in terms of the depth and width of the database. Avoid jumping onto the database bandwagon and then failing to commit the necessary resources. Database Development 4-6

7. Geodemographic (Geographic, residential) Geodemographic (Geographic, residential) Attribute (attitudinal) Target Market (demographics, usage) Three Types of Database Units 4-7

8. oCentral repository of data. oTwo Purposes: Collect and store data Operational Data Online Transactional Processing (PLTP) Collect, organize and make data available Informational Data Online Analytical Processing (OLAP) oComparable to a library. oCentral repository of data. oTwo Purposes: Collect and store data Operational Data Online Transactional Processing (PLTP) Collect, organize and make data available Informational Data Online Analytical Processing (OLAP) oComparable to a library. Data Warehouse 4-8

9. Data Warehouses Types of Data to be Stored Secondary data Primary data Real-time transactional data Customer-volunteered data 4-9

10. Data Mining Analysis procedure – identifies significant patterns of data relationship for specific customers or customer groups. Data Mining – process of finding hidden relationships among variables contained in data stored in the data warehouse. Data Mining – process of finding hidden relationships among variables contained in data stored in the data warehouse. Transforming Data Into Knowledge 4-10

11. Enable researchers to determine which factors separate customers into purchase groups... Use weights to multiply assigned values Use actual purchase behavior data Key variables  Assign weights or scores depending on ability to predict purchase behavior Enable researchers to determine which factors separate customers into purchase groups... Use weights to multiply assigned values Use actual purchase behavior data Key variables  Assign weights or scores depending on ability to predict purchase behavior Scoring Models 4-11

12. Lifetime Value Model Premise – need to determine value of customers to your company Lifetime value models – examples of variables... Price variables Sales promotional variables Advertising expenditures Product costs Relationship-building efforts Database Information Used to identify most profitable customers over the span of their relationship with the company 4-12