Let's assume that your company is interested in entering a market that currently consists of just two competitors. There are just three attributes that adequately describe the products and account for preference in the market: Brand, Style and Price. The two players are:

1) BrandA, StyleA, $100

2) BrandB, StyleB, $200

Your company has developed a new style (StyleC) that you think may appeal to buyers, and you want to investigate its potential with respect to the two existing products.

The first step, typically, is to simulate the existing market scenario. You use the choice simulator to define the two existing products:

Product Specifications:

Product Name Brand Style Price

"BrandA" 1 1 1

"BrandB" 2 2 3

When you run the choice simulator, the following shares of preference are displayed:

Shares of Preference for Products:

BrandA 64.3

BrandB 35.7

Note that the buyers in the simulation are all assumed to choose a product, so the shares of preference across products in the simulation sum to 100%.

Let's assume that you have actual market share information about these two brands. You note that the shares reported above do not necessarily match the actual market shares. You accept this, however, recognizing that many factors influence market shares in the real world that cannot be captured through conjoint analysis. You are principally interested in relative preferences, assuming that the marketplace is an equal playing field: equal distribution, awareness, effectiveness of sales force, and equilibrium long-range demand (of course if you have data on distribution and awareness of the products, the choice simulator has ways to incorporate this information via External Effects).

In the second stage of this simulation example, we'll define a new scenario that includes your company's proposed product: BrandC, StyleC, $150. You add another row to the simulation specification grid:

Product Specifications:

Product Name Brand Style Price

"BrandA" 1 1 1

"BrandB" 2 2 3

"BrandC" 3 3 2

After running the choice simulator, the following shares are displayed:

Shares of Preference for Products:

BrandA 42.5

BrandB 21.3

BrandC 36.2

You note that BrandA is still the most preferred product, but that your brand is preferred to BrandB.

Like any market research statistic computed from samples, shares of preference are not estimated without error. It is common to estimate a confidence interval, to gain a feel for the degree of uncertainty due to sampling and measurement error associated with a given share of preference. If your simulator is based upon part-worth utilities generated by a method other than aggregate logit, the choice simulator displays standard errors of the shares of preference as well as the 95% confidence interval. Let's assume that the standard error reported for BrandC for the simulation above was 1.53. The 95% confidence interval is computed by adding plus and minus 1.96 times the standard error to the estimated share of preference. In this example, the 95% confidence interval is 36.2 plus and minus (1.96)(1.53) = 3.0 share points, or the interval [33.2, 39.2].

You next may ask yourself what price you would need to charge to capture the same relative preference as BrandA. To simulate this, you lower the price slightly for your brand. The choice simulator lets you interpolate between levels, so you can investigate even the smallest of price changes. As a first step, you decide to lower the price to $130 for BrandC (while holding the specifications for BrandB and BrandA constant). The new simulated shares are:

Shares of Preference for Products:

BrandA 39.2

BrandB 19.0

BrandC 41.8

You have overshot the mark (BrandC's share exceeds BrandA's share), so you try a slightly higher price than $130 and run the simulation again. You make repeated attempts until BrandA and BrandC's shares are equal. Let's assume that after a few more attempts, you discover that the price that makes your company's offering match the share of preference of the market leader is $136. Another way of thinking about this finding is that your proposed product commands a $136 - $100 = $36 premium over BrandA's product. (Respondents are indifferent between BrandA, StyleA at $100 and BrandC, StyleC at $136).