The Nature and Measurement of Marketing Productivity in Consumer

Durables Industries: A Firm Level Analysis

HAWKINS, DELL I, ROGER J. BEST AND CHARLES M. LILLIS (1987), “THE NATURE AND

MEASUREMENT OF MARKETING PRODUCTIVITY IN CONSUMER DURABLES INDUSTRIES: A FIRM LEVEL ANALYSIS,” JOURNAL OF THE ACADEMY

OF MARKETING SCIENCE, 15 (4), 1-8.

Authors

Del I. Hawkins Professor of Marketing Various marketing Journals and Textbooks

Roger J. Best Associate Professor of Marketing Journals and Textbooks

Charles M. Lillis Vice President of Strategic Marketing for

US WEST Inc. Various Journals Marketing executive

Develop a managerially relevant concept of marketing productivity

Construct an operational measurement of marketing productivity-a validity issue

Establish environment specific benchmarks with which to compare the marketing productivity of various businesses

Purpose of the Article

Model Development

How the authors develop the model step by step is a good learning exercise (this is one of the reason I have included this article in the reading list) Define the variables first Explain conceptualization and limitation of variables Identify their relevance in the area Operationalize the variables-validity Testing the model with credible data Explain limitations

Model has no meaning in isolation, relative to what is the question

The Nature of Marketing Productivity

Concept of Productivity: Output/InputMarketing productivity = marketing output

divided by marketing inputMarketing Output = (Relative market

share) x (Relative Price)Marketing input= (Marketing

Expenditures) /(Sales)Percentage or ratio measures, not in

absolute dollars

Marketing Productivity Formula:

Relative Market Share x Relative Price Marketing Expenditures/Sales

» Marketing Productivity Score (MPS) – In isolation it has no meaning !

» Marketing Productivity Index (MPI)

Marketing Productivity

Sources of data: firms pay a fee to join PIMS

Self reported data, multiplied by an unknown constant when supplied to PIMS

Questionnaire is provided by PIMSOperational Definitions of Variables

(ses Table 1)

PIMS Database(now Marketing Science Institute)

Variables Influencing Marketing Productivity

Variables InfluenceRelative Product Breadth (RPB) +

Number of Competitors (NC) -

Relative Product Quality (RPQ) +

Relative Customer Size Range (RCSR) +

Served Market Growth (SMG) +

Number of Immediate Customer (NIC) -

Importance of Auxiliary Services to End User (IASE)

-

Frequency of Product Changes (FPC) -

Purchase Amount Immediate Customers (PAIC)

+

Customization (C) +

Construction of the Model

Correlation Analysis

Model Evaluation

R² is significantModel is reasonably stableDurables, nondurables, split-half…..all

supports the modelSupports the overall structure of the

model developed for the durables industries

Variables that were collinear were removed before implementing the model

Critique of the Article

Positive Contribution: First of its kind Reasonable model Credible database Coming from industry

Questionable Issues Limitation in variable definition Variability in the dataset Collinearity

Future direction

Discussion Questions

What is marketing productivity? What problems do we face in measuring productivity? How can we overcome them?

What are the drawbacks/limitations of the Hawkins et al.’s (1987) marketing productivity score/index? Can we apply the index to measure productivity in other industries? How?

Write a critique of the article.