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Group 5 Selvy letlora Ngoc Pham Javier gonzalez Chad verboom Juan SEBASTIAN GARZON

Nature and Measurement of Marketing Productivity in C onsumer Durables Industries: A Firm Level Analysis. Group 5 Selvy letlora Ngoc Pham Javier gonzalez Chad verboom Juan SEBASTIAN GARZON. Productivity. Productivity = Outputs Inputs A. 1hr = 3 Outputs B. 1hr = 5 Outputs

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Group 5 Selvy letlora Ngoc Pham Javier gonzalez Chad verboom Juan SEBASTIAN GARZON

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  1. Nature and Measurement of Marketing Productivity in Consumer Durables Industries: A Firm Level Analysis Group 5 Selvyletlora Ngoc Pham Javier gonzalez Chad verboom Juan SEBASTIAN GARZON

  2. Productivity • Productivity = Outputs Inputs • A. 1hr = 3 Outputs • B. 1hr = 5 Outputs • Mktg. Productivity = Mktg. Outputs Mktg. Inputs

  3. Factors that impact results in Market share and Price Inflation Different rates of inflation per individual factor Position and Operating environment in which the firm operates Market growth or decline Pricing below industry standards Stage in Product life

  4. A firm can “Buy” Market share Companies can sell the price at below Industry levels in order to gain market share They can also “harvest” market share by holding the same price, but lowering expenditures spent on the product

  5. How to Successfully Measure Output Relative Market Share Relative Price A firm’s share of the market divided by the marketshare of its three largest competitors Average selling price of a firm’s product divided by the average selling price of its three largest competitors

  6. Marketing Productivity Would an increase in raw materials purchases to increase the quality of the product as a direction from the marketing department be a marketing expense? Absolute dollars mean different things to each company Dollars over sales determines the best correlation illustration

  7. Marketing Productivity (cont’d) • Mktg. Prod. = Relative mkt. Shares * Relative Price Mktg. Expenditures / Sales

  8. Development OfMarketing Productivity Index (MPI)

  9. Data Base • PIMS Data Base • Function of PIMS Data Base • Sources of Data Base • Weakness is sensitive data

  10. Variables Influencing Marketing Productivity

  11. Model Construction“Multiple Regression”

  12. Correlation Analysis

  13. Marketing Productivity Model .212 -.153 .151 .151 .198 -.322 -.100 .113 .309 -.085 .142 .142 .091 -.134 -.133 -.095 .159 .151 Y= 0.212 X1 – 0153 X2 + 0.151 X3 + 0.151 X4 + 0.198 X5 – 0.322 X6 – 0.100 X7 + 0.113 X8 R2= .43 R2= .36

  14. Limitation/ Problems with the method Data are taken on PIM Data Base. All data comes from annual self questionnaire report Potential for measurement bias. Nonrandom nature of the PIMs data bases suggest caution in generalizing the exact findings. Not all of variables are operationalized Expenditure data exist only as a percent of sales

  15. Conclusion Complexity of marketing effort evaluation Marketing evaluation remains situational Consistency realized when MPS is analyzed with PIMS variables outside of marketing management control

  16. Discussion What is marketing productivity? What problems do we face in measuring productivity?

  17. Discussion (cont’d) What are the drawbacks/limitations of the Hawkins et al.’s (1987) marketing productivity index? Can we apple the index to measure productivity in other industries?

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