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Marketing Research: Within a Changing Information Environment, 2/e
Joseph Hair, Louisiana State University
Robert Bush, University of Memphis
David Ortinau, University of South Florida

Marketing Research and Database Development

Chapter Summary

Illustrate and define a marketing research database.


A marketing research database is a central repository of information on what customers are purchasing, how often, and in what amount. The fundamental purpose of any customer database is to help a firm develop meaningful, personal communication with its customers. Other, more specific purposes of this database are to improve efficiency of market segmentation construction, increase the probability of repeat purchase behavior, and enhance sales and media effectiveness.

Explain the interactive nature of marketing research and data enhancement.


A database is designed to serve as an information and intelligence resource for the company. Data enhancement allows a company to gain more knowledge of its customers, increase the effectiveness of its marketing programs, and predict responsiveness to changing marketing programs. Marketing research plays the critical role of gathering and collecting data relating to geodemographic factors, customer attributes, and target market characteristics.

Describe the dynamics of database development.


The development of a marketing research database takes into account numerous steps, including (1) assessing what information needs are required by the company; (2) identifying specific research needs; (3) collecting internal, external, and target market data; (4) profiling customers into purchase categories; and (5) developing predictive models to estimate the total lifetime value each customer represents to a business.

List the general rules of thumb in database development.


General rules of thumb exist in database development. First, collect data that will have the greatest amount of predictive power. Second view the data acquisition process in terms of the width and depth of the database. Third, make a commitment to long-term data acquisition and enhancement.

Demonstrate understanding of technology in a database context.


Database technology refers to the process of transforming data into predictive information. This is accomplished through a database management system which creates, modifies, and controls access to the database. The two most commonly employed database management systems are relational and sequential database systems.

Illustrate the development and purpose of the data warehouse.


A data warehouse, frequently termed an "information warehouse" is a central repository for all significant parts of information that an organization collects. Data from various functions of the organization are stored and inventories on a central mainframe computer so that information may be shared across all functional departments of the business. The major significance of a data warehouse is its purpose. From the standpoint of data collection, a data warehouse serves two purposes; (1) to collect and store data for the daily operations of the business and (2) to collect, organize, and make data available for analysis purposes.

Explain the process of data mining as it related to the data warehouse.


Simply defined, data mining is the process of finding hidden patterns and relationships among variables/characteristics contained in data stored in the data warehouse. Data mining is a data analysis procedure known primarily for the recognition of significant patterns of data as they pertain to particular customers or customer groups.

Understand the role of modeling in database analysis.


The purpose of database modeling is twofold: (1) to summarize what companies already know about their customers, and (2) to know companies what they need to learn about their customers. Two common modeling techniques exist in database analysis. A scoring model, using a gains table, is designed to predict consumption behavior. The lifetime value model is designed to measure the value customers represent to the firm. Both models rely on actually purchase behavior, not profitability estimates based on purchase intentions.