Understanding Conjoint Analysis: Predicting Choice by Joseph Curry
Bringing a new or reconfigured product to market involves a number
of complex, interrelated decisions. Marketers must decide what features
a product should have, how to price it, and whom to target. And,
all of this must be done against a background of anticipated competition.
Conjoint analysis has become a popular technique for making these
types of decisions because it lets marketers predict choice behavior.
I described the basics of conjoint analysis in my last article,
"Understanding Conjoint Analysis in 15 Minutes"
(Quirk's Marketing Research Review, June/July 1989). Because I touched
only briefly on choice models in that article, I expand on that
subject here using the same example. I will describe three of the
most widely used models: First Choice, Share of Preference, and
Likelihood of Purchase.
Suppose we want to market a new golf ball and have decided that
the salient features and feature alternatives are:
| AVERAGE DRIVING DISTANCE |
AVERAGE BALL LIFE |
PRICE PER BALL |
| 275 yards |
54 holes |
$1.25 |
| 250 yards |
36 holes |
$1.50 |
| 225 yards |
18 holes |
$1.75 |
Also suppose we have interviewed golfers to determine their preferences
for these features. For one buyer these preferences are reflected
in the following "utilities:"
| AVERAGE DRIVING DISTANCE |
UTILITY |
AVERAGE BALL LIFE |
UTILITY |
PRICE PER BALL |
UTILITY |
| 275 yards |
100 |
54 holes |
50 |
$1.25 |
20 |
| 250 yards |
60 |
36 holes |
25 |
$1.50 |
5 |
| 225 yards |
0 |
18 holes |
0 |
$1.75 |
0 |
A utility has the property that the higher its value, the more
desirable its corresponding feature. Utilities can be added to yield
a total value for a combination of features.
Suppose we were considering marketing one of two golf balls:
| |
DISTANCE BALL |
LONG-LIFE BALL |
| DISTANCE |
275 yards |
250 yards
|
| LIFE |
18 holes |
54 holes |
| PRICE |
$1.50 |
$1.75 |
One way to predict which ball our buyer will choose is to add up
the buyer's utilities for each ball; the one with the higher total
is expected to be the buyer's first choice.
| |
DISTANCE BALL |
|
LONG-LIFE BALL |
|
| DISTANCE |
275 yards |
100 |
250 yards |
60 |
| LIFE |
18 holes |
0 |
54 holes |
50 |
| PRICE |
$1.50 |
5 |
$1.75 |
0 |
| TOTAL UTILITY |
|
105 |
|
110 |
Given these two choices, we'd expect our buyer to choose the Long-Life
Ball. Repeating this for the 100 buyers in our hypothetical sample,
we might get:
| |
DISTANCE BALL |
LONG-LIFE BALL |
| FIRST CHOICE |
23% |
77%
|
We can use this approach to answer "what-if" questions.
For example, suppose we dropped the price of the Distance Ball from
$1.50 to $1.25. Which ball would our buyer prefer? Let's recompute
the totals and see.
| |
DISTANCE BALL |
|
LONG-LIFE BALL |
|
| DISTANCE |
275 yards |
100 |
250 yards
| 60 |
| LIFE |
18 holes |
0 |
54 holes |
50 |
| PRICE |
$1.25 |
20 |
$1.75 |
0 |
| TOTAL UTILITY |
|
120 |
|
110 |
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