Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso 19-1 Chapter Nineteen Marketing Decision Support Systems and Marketing Research
Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso 19-2 Learning Objectives Understand the purpose of a marketing decision support system (MDSS) Describe the various information requirements used to design an MDSS Understand the role of transactional data in the MDSS Explain the relationship between information processing and the MDSS
Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso 19-3 Learning Objectives Understand the various models used in an MDSS Provide examples of output from an MDSS Discuss the relationship that exists between the decision support system and business intelligence
Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso 19-4 Introduction Customer data has been a major driver of the adoption of CRM systems Firms use technology to align operations, resources and strategies to maximise the value that customers can derive from offerings
Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso 19-5 Value of the Marketing Decision Support System Marketing decision support systems are more cost effective than collecting primary data. Marketing decision support systems provide decision makers with the information they need in a more timely and efficient fashion.
Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso 19-6 Value of the Marketing Decision Support System Marketing decision support systems can be used by decision makers at any functional level in the business enterprise. Marketing decision support systems can be used to simulate business decisions, increasing the window of available alternatives and minimising risk.
Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso 19-7 Characteristics of a Marketing Decision Support System It is designed for specific research problems to support individual marketing personnel. It provides information designed to facilitate a specific decision. Its main purpose is to evaluate alternative scenarios and identify the best course of action.
Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso 19-8 Characteristics of a Marketing Decision Support System It is designed to focus on narrow (semi-structured) problems such as facilitating the design of sales territories, evaluating outcomes of new-product or brand launches. Its emphases are information storing and categorisation, and resultant solutions.
Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso 19-9 A Marketing Decision Support System
Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso Information Requirements Environmental information Distribution partners Business intelligence Transactional data
Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso Environmental Information Dollar volume by season and year Growth or shrinkage of annual dollar volume Shipping and billing accuracy Price terms and allowances Timing of deliveries Returns and procedures
Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso Distribution Partners Levels of inventory carried by wholesalers On-time delivery schedules Minimum order levels maintained by wholesalers Costs of transportation Repairs, allowances and adjustments by wholesalers Level of service
Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso Business Intelligence and Transactional Data Business intelligence data can be found: In trade publications and journals By talking to customers By talking to internal stakeholders By talking to the public Transactional data can be found: Bar codes Automatic Replenishment Systems (ARS) Electronic Data Interchange (EDI) Reader-sorters
Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso Types of MDSS Models 1.Static Models 2.Dynamic Models 3.Probabilistic Models 4.Deterministic Models 5.Optimising Models 6.Sub-optimising Models
Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso Geographic Information Systems (GIS) A GIS is a spatial modelling technique. It allows us to capture, encode, edit, analyse, compose and display data in a spatial format organised or ‘layered’ into a map format.
Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso Business Intelligence Programs (BIP) The following eight sources are used to capture data for a business intelligence program: 1. Governmental agencies 2. On-line databases 3. Company and investment community resources 4. Surveys and interviews 5. Drive-by and on-site observations 6. Benchmarking 7. Defensive competitive intelligence 8. Reverse engineering
Copyright 2004 McGraw-Hill Pty Ltd. PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau Slides prepared by Tony Peloso The Internet and Business Intelligence SourceDescription of DataWeb Address AUSTLIICase law relating to Australian companies ABRWide range of services for gathering business intellience to business research sites with editorial comments CI Resource IndexListing of sites by category for finding competitive intelligence sources