The document discusses developing a concept of marketing productivity, how to measure it using ratios of marketing output to input, and establishing benchmarks by considering factors like relative market share, price, number of competitors, product changes. It develops a marketing productivity index model using consumer durables firm data and validates it can also apply to nondurables industries.

1. The Nature and Measurement of
Marketing Productivity in Consumer
Durables Industries:
A Firm Level Analysis
Spring 2012: Group
2
Huy Dang
Oanh Nguyen
Jeffrey Gritton
Liman Ha

2.  Marketing Productivity emerged in the early 80s
as a major concern of American business
 The purpose of this article is to develop a
managerially relevant concept of marketing
productivity, its operational measurement, and a
procedure for establishing environment specific
benchmarks to compare with various business

3.  Productivity is perceived as a ratio of output from
some activity to the input required by that activity.
Thus, marketing productivity is: marketing output
divided by marketing input.
 Bucklin's definition of marketing productivity
adjusted Sevin's formula for inflation over time
became more adequate to the macro study but
not to the firm level.

4.  What does top management expect the marketing
function to deliver?
Answer: The combination of relative market share
and price position.
 Marketing output for an individual firm as:
Marketing Output=(Relative market share) x (Relative Price)

5.  Using absolute dollars allows one to measure the
marketing output purchased with one dollar of
marketing input
 Using marketing cost as a percent of sales allows
one to measure the marketing output purchased
with one percent of sales.
 Minimize the impact of inflation over time
Marketing input= Marketing expenditures/sales

6. Relative Share x Relative Price
Marketing =
Productivity Marketing expenditure/Sales

7. • Steps
– Marketing variables are defined
– Marketing variables measured
– Marketing productivity ratio measured
– Marketing productivity score calculated
• Comparison
– Last year’s MPS
– Competitor’s MPS
– Standard

8.  Words of caution
◦ PMS comparisons may not be “apples to apples”
◦ PMS may give credit to marketing when credit belongs to
other departments
 Marketing Productivity Index (MPI)
◦ Regression
◦ “Predicts an average firm’s MPS given a specified
operating environment.”

9.  PIMS Database
 Scientifically-managed
 Sensitive sales data was hidden
 Some weaknesses
 “The only data base in existence that allows us to
develop a solution to the indexing problem.”

10.  Relative Product Breadth (RPB)
◦ Require more marketing effort
◦ Meet more customer needs than competitors
◦ Produce high market share
◦ Secure high price
◦ Allow shared costs
 Number of competitors (NC)
◦ Requires low markeitng productivity
◦ Large NC produces unlikely market share

11.  Relative Customer Size Range (RCSR)
◦ High RCSR requires more marketing effort
◦ Allows firm to obtain relatively high market share
◦ Allows firm to change differential price
 Served Market Growth (SMG)
◦ High SMG requires more marketing effort
◦ Concerned more with building capacity than stimulating
demand

12.  Number of Immediate Customers (NIC)
◦ High NIC requires low levels of marketing productivity
◦ Higher costs to serve large numbers of customers
◦ Serving large NIC does not necessarily correlate to large
market share
 Purchase Amount Immediate Customers
◦ Requires relatively high level of marketing productivity
◦ Suggests few customers, less frequent purchases and
indirect distribution

13.  Purchase amount Immediate Customers (PAIC)
◦ Requires high level of marketing productivity
◦ Suggests few customers, less frequent purchases and
indirect distribution
 Frequency of Product Changes (FPC)
◦ Associated with low level of marketing productivity
◦ Costly when introduced to the market
 Customization
◦ Associated with high marketing productivity
◦ Limited number of customers

14.  Focused on businesses that dealt in consumer
durables
 Limited number of firms due to capacity limitation
 135 firms total
 Variables within 0.10 were retained in the model

15.  1)R²=0.43
 2) R² for each split half remain above 0.40 level;
Auxiliary services did not meet 0.10; NC,RCSR, and
FPC missed the 0.10 criteria in one of the split
halves but were included in the other.
 3)All of the hypothesized relationships are reflected
in the overall durables market except two. Custom
production in durable goods does not lead to a high
level of MP;
 4) Durable goods industries characterized by
frequent product changes tend to have a higher
level of marketing productivity than do industries
with less frequent change.

16.  5)Replication of the process with 206 consumer
nondurables firms in PIMS data base that were
not constrained by capacity. The split half analysis
produced results similar to those obtained for the
durable industries model.
 6) In total, this replication in a different industry
strongly supports the overall structure of the
model developed for the durables industries.

17.  Expenditure data only exist only as a percent of
sales in the PMS database
 Absolute expenditures would have been useful in
allowing more confidence in the comparison of
firms with large share differentials.

18.  Management should explicitly define marketing
performance objectives in terms of relative price
and relative share.
 If all the major firms in the market are similar on
the firm specific variables (RPB,RPQ, CSR and
NIC), no adjustments need to be made.
 If the firm is substantially above or below the level
of key competitors, an analysis should be
conducted .

19.  Causes of variations can be:
 1) 1 or more uncontrollable variables not
discovered in the study.
 2) Short term competitive strategies such as
buying market share.
 3) Particularly effective or ineffective uses of
marketing expenditures.

20.  1. What is marketing productivity?
◦ What problems do we face in measuring productivity?
◦ How can we avoid them?
 2. What are the drawbacks/limitations of the
Hawkins et al.’s (1987) marketing productivity
index?
 3. Can we apply the index to measure productivity
in other industries?