CBC market simulator

Introduction

The Market simulator (also known as the choice simulator) is often considered the most crucial decision-making tool in a conjoint project. It transforms conjoint utilities into actionable insights by simulating market choices between different product alternatives.

By introducing products defined by the attributes and levels in your study, the simulator generates projections of the percentage of respondents likely to choose each product (or choose "None," if the None option was included in your questionnaire). The market simulator allows researchers to conduct "what-if" analyses, exploring scenarios such as new product design, product positioning, and pricing strategy.

Cbc Simulator

Think of the simulator as a "voting machine." After estimating the utility scores from your CBC exercise, you can simulate how your market might "vote" for each of the products you configure in the software. The results, or "shares of preference," represent the percentage of respondents likely to choose each product, and the total shares will always sum to 100%.

A warning about interpreting the output of market simulators

Under favorable conditions (such as mature markets with equal information and distribution), market simulators often report results that closely match long-range equilibrium market shares. However, conjoint analysis cannot account for many real-world factors that shape market shares, such as differences in the length of time on the market, distribution, out-of-stock conditions, advertising, sales force effectiveness, and awareness. Conjoint analysis predictions also assume that all relevant attributes influencing share have been measured.

Therefore, the share of preference predictions should generally not be interpreted as market shares. Instead, they should be seen as relative indications of preference, reflecting how respondents might rank products based on the attributes and levels included in the study.

Building products

Once you have collected your conjoint data and estimated utilities, you may begin building a market scenario of competing product concepts. The simulator starts out with two empty products, allowing you to quickly start comparing two alternatives. You need at least one product alternative to start a simulation.

To begin, select the desired level from each attribute for each product alternative. Once a level has been selected for all attributes in the first product, the simulation will start to run. You can continue to build additional products, and the simulation will restart with each new product added.

It is usually a good idea (and the most proper use of the simulator) to specify a number of products that closely resemble the number of product alternatives per task that were included in the CBC questionnaire.

The first step in using the market simulator is typically to define a base case scenario. This base case usually reflects a current or future market scenario: your brand versus the relevant competition. If there is no relevant competition or your conjoint study was designed to model only your product, the base case may consist of a single product versus the "None" alternative, reflecting a likely configuration.

After modifying the base case, add additional scenarios by clicking the scenario selector in the top right corner and clicking the plus (Plus icon) button in the fly out. This allows you to explore different market scenarios and compare various product configurations.

The scenarios fly out is open showing a few scenarios have been created.

Simulation method

Share of preference

The share of preference method “splits” votes proportionally across multiple product alternatives for each respondent according to their likelihood of choice. For example, if two product alternatives are equally desirable, it can split a respondent’s vote 50/50.

Advanced note: The share of preference model uses the logit equation for estimating shares. The product utilities are exponentiated (the antilog) and shares are normalized to sum to 100%.

Confidence intervals

Should you desire, you can check the option to display 95% confidence intervals.

Assuming your respondents are representative of the population from which they were drawn randomly, you are 95% confident that the true population's share of preference falls within this interval.

You can also use the 95% confidence intervals to assess whether one product alternative is preferred to another. If the confidence intervals do not overlap between two product alternatives, you are at least 95% confident that one is preferred to the other.

Downloads

There are two files that are available for download:

  • Scenario: This is a .xslx file that contains the products created along with a table of their preference scores, the standard error, and the upper and lower 95% confidence intervals (identical to the tables viewable in Discover). Scores are rescaled.
  • Charts: This exports a .png image of the scenario.

Segmenting

In analysis it's common to compare groups of people using their exercise scores. Segmenting allows you to take the results from a scenario simulations and split them into groups. These groups come from different responses/values for one of your questions or defined variables.

For example, you could use a demographic question or variable in your survey (like the respondent’s location) to segment the results to see how people in North America responded versus people in Europe.

Cbc Simulator Results Segmenting

To apply segmenting, click the Segmenting dropdown and select a question or variable from the menu. When a variable is selected, the chart will automatically update and the Segmentation icon turns green. Scenario results are then split into groups according to the selected variable. Respondents that don’t have any response (or value for defined variables) will be missing from the results. Similarly, segment groups that are empty are not included in the results.

Segmenting Dropdown in Max Diff Analysis

To clear the segmenting or apply a different one, click the dropdown and select No segmenting or choose another option from the menu.

Simulator settings

Attribute configuration

For attributes that are quantitative in nature (e.g., speed, price, weight), you can configure them in the simulator to be used more precisely, such as for simulating values between the levels shown to respondents in the CBC questionnaire (interpolation). To access these settings, click the settings icon next to the simulator tab.

Continuous attributes

 

Some attributes, such as speed, price, and weight, are quantitative or continuous in nature. For example, weight could be 30 kilos, 40 kilos, or 50 kilos. It is both common and reasonable to simulate preferences for products defined between the levels of quantitative attributes. Extrapolation—entering values outside the range of those tested in the conjoint exercise—is also permitted, but the results can be unreliable since respondents did not evaluate these values in the questionnaire.

Marking an attribute as Continuous allows you to assign numeric values to each attribute level, enabling more intuitive specification of product alternatives and easier linear interpolation and extrapolation between attribute levels in market simulations.

In the Attribute settings area, after marking the attribute as Continuous, you can assign each level a value. For example, if weight is marked as continuous, you can add values like 30, 40, and 50 to the table next to the corresponding weight levels.

In the attribute settings overlay, weight has been marked as continuous and values of 30, 40, and 50 have been added to the table opposite the corresponding weight.

Now, when configuring products, you can either select a predefined value from the list or enter a custom numeric value within the specified range (e.g., 46) or even outside this range for extrapolation.

A product in the simulator configured with a weight of 46.
Technical details

Linear interpolation is applied, for each respondent, on the part-worth utilities prior to simulating shares of preference. For example, if level 1 of weight is "30 kilos" and level 2 is "40 kilos", specifying 33 kilos means to interpolate using straight-line projection a utility 30% of the way between the utility of 30 and 40 kilos. For example, for respondent #1, if the utility for 30 kilos is 1 and the utility for 40 kilos is 0, a simulated utility for 33 kilos returns a value of 0.7.