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Research Decisions and the Value of Marketing Information The meaning of “limited by budget and time constraints.”

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Presentation on theme: "Research Decisions and the Value of Marketing Information The meaning of “limited by budget and time constraints.”"— Presentation transcript:

1 Research Decisions and the Value of Marketing Information The meaning of “limited by budget and time constraints.”

2 Value of Marketing Research Estimating gains from the “right” marketing decisions, developing market forecasts. Framing marketing decisions and the value of information.

3 Overlapping Information Needs Planning: Market Opportunity Analysis Implementation: Refining Marketing Actions Control: Monitoring

4 Forecasts vs. Potential Market Potential: Sales of all competitors, if all gave maximal marketing efforts. Market Forecast: Sales of all competitors if competitors gave historic effort. Sales Potential: Sales of your firm, with maximal effort, maximal market share ever. Sales Forecast: Sales of a firm given projected efforts.

5 Forecasts vs. Potential “Market Potential” is a frequently used expression, but is an “upper limit” of consumer expenditure with maximum marketing efforts. “Market Forecast” is a more realistic projection of consumer expenditure with current competitive efforts.

6 Women in the U.S. 35 to 39 years11,387,968 40 to 44 years11,312,761 45 to 49 years10,202,898 50 to 54 years8,977,824 55 to 59 years6,960,508

7 Conversion Factors Market forecasts convert population and household counts for geographic areas into estimates of: –Number of buyers –Sales for a particular product category, or consumer expenditures Sales forecasts convert market forecasts into share of the market or sales for a particular brand

8 Placing a Value on a Sales Forecast Contribution Margin Discounted Time Stream

9 Market research should be conducted only when the expected value of information to be obtained exceeds the costs of obtaining it. What then, is the value of information?

10 Value of perfect information: Expected payoffs under uncertainty Choose between 40% probability of scoring two points, versus 98% probability of scoring one point. Expected payoffs are.80 versus.98, respectively.

11 .98 “kick”.40 “go for two” 1 point 2 points “kick” “go for two”.98 point.80 point Decision Tree

12 98 “kick”.80 “go for two” 1 point 2 points “kick” “go for two”.98 point 1.6 points Decision Tree with research

13 Framing research costs: Expected value of perfect information equals: The value of information under certainty (gained from market research)... minus the value of information under uncertainty (operating without market research, trial and error,“learn by doing.”)

14 1.0 Success. $4 million Introduce “A” Do not introduce Case A1 $0 Value of information under uncertainty—how much would you pay for marketing research if this were your situation?

15 .60 Success.40 “Failure” $4 million $1 million Introduce “A” Do not introduce Case A2 $0 Value of perfect information: How much would you pay for certainty that the product will be successful?

16 Success Failure $2.4 million (.6 x $4m) $.4 million (.4 x $1m) Introduce A Do not introduce Case A2 $0 Value of perfect information: Nothing, we would introduce the product regardless of marketing research. On average, the firm would make $2.8 million in gross margins. +

17 .60 Success.40 Failure $4 million -$2.5 million Introduce B Do not introduce Case B $0 Value of perfect information: How much would you pay for certainty that the product will be successful?

18 Success Failure.6*4=2.4m.4*(-2.5)= (-$1m) Introduce B Do not introduce Case B $0 One year’s perspective: Company would still choose to introduce because on average, on average net would be +1.4m, but information could prevent an average loss of $1m.

19 Expected value of perfect information: The value of information under certainty, (discovered through research), prevents a $2.5 million loss 40% of the time ($1m), minus the value of information under uncertainty, worth $0, 60% of the time. Expected value of “perfect” information is $1m, or an upper limit for expenditures on research.

20 Success Failure.9*4=3.6m.1*(-2.5)= (-$.25m) Introduce B Do not introduce Case B $0 Across years: Research reduced probability of failure from.4 to.1, providing an average return of $3.35m, a gain of 1.95m over $1.40m.

21 As probabilities and costs of failures increase, the expected value of information increases. Costs come from accounting records. Probabilities come from past experience.

22 .20 Success.80 Failure $0.8 million (.2*4.0 =$.8 m) -$2 million (.8*-2.5 = -$2m) Introduce C Do not introduce Case C $0 The product would not be introduced (net -$1.2.m) without research, prevents a $2.5m loss 80% of the time, or $2m on average. More realistic scenario

23 More simply put… The dollar value of any given research project depends on the amount of money riding on the decision If a decision has already been made and research will not affect it, research has zero value (“window-dressing”). The value of research depends on its ability to provide clear direction—formulating the research problem correctly.

24 “The Company's expenditures for research and development were approximately $121.9 million in 1998, $106.1 million in 1997, and $84.3 million in 1996.” (From Kellogg’s 10-K. Sales and operating profits were $6,762.1 and $895.6 million, respectively.)

25 Kellogg’s Research and development expense (millions): $110.2, $118.4, $104.1 (2001, 2000, 1999, respectively) Sales $8,853.3$6,954.7$6,984 % 1.5%1.7%1.5% Operating profit $1,167.9 $989.8 $828.8 % 9.4%11.9%12.5%


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