Understanding Conjoint in 15 Minutes

This white paper arms you with the basics of conjoint analysis using a simple example.

Conjoint analysis has become popular because it is far less expensive and time consuming than concept testing.

Conjoint analysis is a popular marketing research technique that marketers use to determine what features a new product should have and how it should be priced. Conjoint analysis became popular because it was a far less expensive and more flexible way to address these issues than concept testing.

The basics of conjoint analysis are not hard to understand. I’ll attempt to acquaint you with these basics in the next 15 minutes so that you can appreciate what conjoint analysis has to offer. A simple example is all that’s required.

Suppose we want to market a new golf ball. We know from experience and from talking with golfers that there are three important product features:

• Average Driving Distance
• Average Ball Life
• Price

We further know that there is a range of feasible alternatives for each of these features, for instance:

assuming that it costs less to produce a ball that travels a shorter distance and has a shorter life.

Here’s the basic marketing issue: We’d lose our shirts selling the first ball and the market wouldn’t buy the second. The most viable product is somewhere in between, but where? Conjoint analysis lets us find out where.

A traditional research project might start by considering the rankings for distance and ball life in Figure 1:

This type of information doesn’t tell us anything we didn’t already know about which ball to produce.

Now consider the same two features taken conjointly. Figures 2a and 2b show the rankings of the 9 possible products for two buyers assuming price is the same for all combinations.

Both buyers agree on the most and least preferred ball. But as we can see from their other choices, Buyer 1 tends to trade-off ball life for distance, whereas Buyer 2 makes the opposite trade-off.

The knowledge we gain in going from Figure 1 to Figures 2a and 2b is the essence of conjoint analysis. If you understand this, you understand the power behind this technique.

Next, let’s figure out a set of values for driving distance and a second set for ball life for Buyer 1 so that when we add these values together for each ball they reproduce Buyer 1’s rank orders. Figure 3 shows one possible scheme.

To read the rest of this white paper on the Sawtooth Technologies website, click here.

This content was provided by Sawtooth Technologies. Visit their website at www.sawtooth.com.