1. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin TURNING MARKETING INFORMATION INTO ACTION

2. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Marketing research questions asked in test screenings of movies and how they are used

3. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin What Marketing Research Is and DoesMarketing Research A Means of Reducing Risk and Uncertainty Why Good Marketing Research is Difficult THE ROLE OF MARKETING RESEARCH

4. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Steps in Making Effective DecisionsDecisions  1. Define the problem  2. Develop the research plan  3. Collect relevant information  4. Develop findings  5. Take marketing actions THE ROLE OF MARKETING RESEARCH

5. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Marketing research process

6. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Ask the “right” question - management Set the Research ObjectivesObjectives Identify Possible Marketing Actions  Measures of success Measures of success STEP 1: DEFINE THE PROBLEM

7. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Specify ConstraintsConstraints Identify Data needed for Marketing Actions Determine How to Collect Data Concepts Methods  Probability sampling Probability sampling  Nonprobability sampling Nonprobability sampling  Statistical inference Statistical inference STEP 2: DEVELOP THE RESEARCH PLAN

8. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Types of marketing information STEP 3: Types of marketing information

9. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Secondary Data Internal Secondary Data External Secondary Data Advantages and Disadvantages of Secondary Data STEP 3: COLLECT RELEVANT INFORMATION

10. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Primary Data Observational Data STEP 3: COLLECT RELEVANT INFORMATION

11. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Nielsen People Meter Observational data

12. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Nielsen ratings of the top 10 national television programs from Jan 28, 2002 to Feb 3, 2002

13. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Nielsen//NetRatings of the top 10 Internet websites from Jan 21, 2002 to Jan 27, 2002

14. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Primary Data Questionnaire Data STEP 3: COLLECT RELEVANT INFORMATION

15. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Typical problems in wording questions

16. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Primary Data Panels and Experiments Advantages and Disadvantages of Primary Data STEP 3: COLLECT RELEVANT INFORMATION

17. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Using Information Technology to Trigger Marketing ActionsInformation Technology The Marketing Manager’s View of Sales “Drivers” STEP 3: COLLECT RELEVANT INFORMATION

18. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Product and brand drivers: factors that influence sales

19. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Using Information Technology to Trigger Marketing Actions Key Elements of an Information System The Challenge in Mining Marketing Data Data Mining: A New Approach to Searching the Data OceanData Mining STEP 3: COLLECT RELEVANT INFORMATION

20. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin How marketing researchers and managers use information technology to turn information into action

21. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Analyze the Data Present the Findings STEP 4: DEVELOP FINDINGS

22. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Identify the Action Recommendations Implement the Action Recommendations Evaluate the Results STEP 5: TAKE MARKETING ACTIONS

23. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Basic Forecasting Terms Market or Industry Potential Sales or Company Forecast Two Basic Approaches to Forecasting Top-Down Forecast Buildup Forecast MARKET AND SALES FORECASTING

24. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Buildup approach to a two-quarter sales forecast for Apple Computer products

25. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Specific Sales Forecasting Techniques Surveys of Knowledgeable Groups  Survey of buyers’ intentions forecast Survey of buyers’ intentions forecast  Salesforce survey forecast Salesforce survey forecast  Jury of executive opinion forecast Jury of executive opinion forecast  Survey of experts forecast Survey of experts forecast MARKET AND SALES FORECASTING

26. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Linear trend extrapolation of sales revenues of Xerox made at the start of 1999

27. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Marketing research is the process of defining a marketing problem and opportunity, systematically collecting and analyzing information, and recommending actions to improve an organization’s marketing activities. Marketing Research

28. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin A decision is a conscious choice from among two or more alternatives. Decision

29. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Objectives are specific, measurable goals the decision maker seeks to achieve in solving a problem. Objectives

30. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Measures of success are criteria or standards used in evaluating proposed solutions to the problem. Measures of Success

31. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin The constraints in a decision are the restrictions placed on potential solutions by the nature and importance of the problem. Constraints

32. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Probability sampling involves using precise rules to select the sample such that each element of the population has a specific known chance of being selected. Probability Sampling

33. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin In nonprobability sampling researchers do not know the chances of selecting a particular element. Nonprobability Sampling

34. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin The method of statistical inference involves drawing conclusions about a population from a sample. Statistical Inference

35. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Secondary data are facts and figures that have already been collected before the project at hand. Secondary Data

36. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Primary data are facts and figures that are newly collected for the project at hand. Primary Data

37. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Data are the facts and figures pertinent to the problem. Data

38. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Facts and figures obtained by watching, either mechanically or in person, how people actually behave are observational data. Observational Data

39. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Questionnaire data are facts and figures obtained by asking people about their attitudes, awareness, intentions, and behaviors. Questionnaire Data

40. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Information technology involves designing and managing computer and communication networks to provide a system to satisfy an organization’s needs for data storage, processing, and access. Information Technology

41. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Data mining is the extraction of hidden predictive information from large databases. Data Mining

42. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Market potential (or industry potential) refers to the maximum total sales of a product by all firms to a segment during a specified time period under specified environmental conditions and marketing efforts of the firms. Market Potential

43. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Sales forecast (or company forecast) refers to the maximum total sales of a product that a firm expects to sell during a specified time period under specified environmental conditions and its own marketing efforts. Sales Forecast

44. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin A top-down forecast involves subdividing an aggregate forecast into its principal components. Top-Down Forecast

45. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin A buildup forecast involves summing the sales forecasts of each of the components to arrive at the total forecast. Buildup Forecast

46. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin A direct forecast involves estimating the value to be forecast without any intervening steps. Direct Forecast

47. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin A lost-horse forecast involves starting with the last known value of the item being forecast, listing the factors that could affect the forecast, assessing whether they have a positive or negative impact, and making the final forecast. Lost-Horse Forecast

48. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin A survey of buyers’ intentions forecast involves asking prospective customers whether they are likely to buy the product during some future time periods. Survey of Buyers’ Intentions Forecast

49. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin A salesforce survey forecast involves asking the firm’s salespeople to estimate sales during a coming period. Salesforce Survey Forecast

50. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin A jury of executive opinion forecast involves asking knowledgeable executives inside the firm about likely sales for a coming period. Jury of Executive Opinion Forecast

51. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin A survey of experts forecast involves asking experts on a topic to make a judgment about some future event. Survey of Experts Forecast

52. © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin Trend extrapolation involves extending a pattern observed in past data into the future. Trend Extrapolation