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CHAPTER. 1234 0001 897251 00000. Marketing Decision Support Systems and Business Intelligence. 7. 7-2. Value of the Marketing Decision Support System. Marketing Decision Support Systems are more cost effective than collecting primary data.

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1234 0001 897251 00000

Marketing Decision Support Systems and Business Intelligence



value of the marketing decision support system
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.
      • 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 minimizing risk.


characteristics of a marketing decision support system
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 evaluating alternative scenarios and identifying a “best” course of action for a decision- maker.
  • It is designed to focus on problems that are “narrowly” defined, profiling target markets for marketing actions with precision.
  • It emphasizes storing and categorizing information and generating solutions management can use in situations characterized by uncertainty.


a marketing decision support system




Marketing ResearchDatabase





Responses toDatabase Queries

A Marketing Decision Support System


information requirements for an mdss
Information Requirements for an MDSS
  • Environmental Information
  • Channel Information
  • Business Intelligence


environmental information
Environmental Information
  • Returns and procedures
  • Price terms and allowances
  • Timing of deliveries
  • Shipping and billing accuracy
  • Growth of dollar volume on an annual basis
  • Shrinkage of dollar volume on an annual basis
  • Dollar volume broken out by season and/or yearly


distribution partners
Distribution Partners
  • Level of service provided by wholesalers
  • Repairs, allowances, and adjustments by wholesalers
  • Costs of transportation
  • Minimum order levels maintained by wholesalers
  • On time delivery schedules
  • Levels of inventory carried by wholesalers


business intelligence transactional data
Business Intelligence & Transactional Data
  • “Good stuff” can be found in trade publications and journals
  • “Good stuff” can be found by talking to customers
  • “Good stuff” can be found by talking to internal stakeholders
  • “Good stuff” can be found by talking to external publics

Transactional data refers to:

  • Bar codes
  • Automatic Replenishment Systems (ARS)
  • Electronic Data Interchange (EDI)
  • Reader-Sorter


guidelines for hardware and software
Guidelines for Hardware and Software
  • The report design should reflect the needs of the decision-makers, not the analysts.
  • The software should be able to provide decision-makers with “user-friendly” reports in minutes.
  • The system must be “intelligent” – able to print highly specific data relevant to a decision problem or opportunity.
  • Data must be easy to digest and implement.
  • The system must be custom-made – a cookie-cutter or pre-written piece of software has but one benefit for a decision-maker… a low price.


types of mdss models
Types of MDSS Models
  • Static Models
  • Dynamic Models
  • Probability-Driven Models
  • Deterministic Models
  • Optimizing Models
  • Sub optimizing Models


gis systems
GIS Systems

A GIS is a spatial modeling technique. It allows us to capture, encode, edit, analyze, compose and display data in a spatial format organized or “layered” into a map format.


bip programs
BIP Programs

The following eight sources are used to capture data for a business intelligence program:

  • Governmental Agencies
  • Online Databases
  • Company and Investment Community Resources
  • Surveys and Interviews
  • Drive-by and on-site observations
  • Benchmarking
  • Defensive Competitive Intelligence
  • Reverse Engineering


summary of learning objectives
Summary of 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.
  • 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.