Chapter 4 Marketing Intelligence and Database Research

1. Chapter 4Marketing Intelligence and Database Research

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

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

4. Other Questions Answered from Databases • 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? 4-4

5. Database Information Affinity (Liking) Customer Characteristics Frequency Recency Profitability 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) Attribute(attitudinal) Target Market(demographics, usage) Three Types of Database Units 4-7

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

9. Secondarydata Primarydata Types of Data to be Stored Real-timetransactionaldata Customer-volunteereddata Data Warehouses 4-9

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

11. Scoring Models • 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 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