Conjoint preference share simulator
Conjoint.ly allows you to simulate shares of preference for different market offerings. Specifically, you need to describe offerings that are available on the market in the language of the attributes and levels that you chose to include in the study, and the system will estimate the percentages of preferences for these offerings. Please keep in mind that:
If you would like to test out a new product, add it to the list of existing concepts.
If two or more offerings share exactly the same levels, input each offering separately. For example, if there are two brands each offering identical products, put in both brands in two separate lines.
The market shares are only approximate and may be affected by constrained availability of some products (e.g., not available in all geographies), shelf space (in case of FMCG).
Automated preference share simulations for what-if scenarios
Brand Specific Conjoint and other types of experiments provide outputs allowing estimation of preference shares, revenue projections and price elasticity for specific market scenarios.
Below are the predictions for a baseline scenario of four car brands:
This baseline assumes the following features of the four car models:
|Make and model||Drive-away price||Transmission||Engine type|
Now that we have established a baseline, we can check what happens if we change the attribute of
Manual for the Ladina Klubnika model:
Price elasticity of demand in two clicks
Price elasticity of demand can be calculated for multiple scenarios by clicking on two points of a preference share simulation.
In this scenario, when clicking on both the
$25,000 price points for Ladina Klubnika a message will be displayed stating that the price elasticity of demand is elastic.
Price elasticity of demand between $23,000 and $25,000 is -4.6.
Demand is elastic (i.e., an increase in price by 1% leads to more than 1% drop in volume).
New product launch simulations
New product launches (NPDs) can be simulated to see redistribution of preference and revenue shares.
Advanced settings in the simulator
The Conjoint.ly simulator comes with several advanced features, including:
- Applying adjustments to bring preference shares closer to observed volume shares,
- Running simulations for specific segments rather than the whole market,
- And more.
Models for calculating market shares
There are two models for calculating market shares:
Share of preference model, which is appropriate for low-risk or frequently purchased products: FMCG, software, etc. This model is applicable in the vast majority of applications.
First choice model, which is suitable for high-risk or seldom purchased products: education, life insurance, pension plans, etc.
In most cases, both simulation models produce substantially the same results. However, at times, simulations results will differ greatly from actual market shares, hence adjustments may be needed.
The “Segregate” function
The “segregate” function creates a variable based on people who would buy certain concepts within each scenario. It allows you to then segment your report to view the preferences of respondents who are willing to buy certain products. To use the “Segregate” function:
- Open the “Simulations” tab in your survey report.
- Click the “Show advanced settings” button at the bottom of your screen then click the “Segregate” button next to the “Enable segmentation based on preferences for concepts in this scenario” heading. A message will appear in the left panel once segmentation is complete.
- Open the “Segmentation” tab and click the “Add a new condition button.
- Click the “Segregation based on simulation” option.
- Select your desired Variable, Type of match, and Value from the respective drop-down menus before clicking the “Save and apply these segments” button in the bottom right corner. A message will appear in the left panel once segregation is complete.
- Open the “Compare segments” tab to view respondents’ profile and preferences from your new segment.
What are the default formulas and revenue based on preference shares?
Preference shares and revenue projections (assuming
1000 units offered) can be simulated to assist in adding or modifying product features.
By default, we estimate
Volume = 1000 × (Preference share). We use the factor of
1000 for convenient scaling. However, if you know the actual volume of units sold in the market, you should use that instead of
Revenue = Price × Volume.
Can you simulate preference shares based on MaxDiff studies?
Using the simulator for MaxDiff should be done with caution because the simulator answers the question “What % of time would a particular option be chosen?”. Choice-based questions (i.e. Conjoint or Claims Test) can accurately answer the simulator’s question because they are about choice among several options, whereas MaxDiff asks both “best” and “worst” choices and uses the “worst” choice in calculating utilities as well.
This means that an option that is occasionally named “worst” in a choice set will have a lower predicted preference share in MaxDiff than it would in conjoint (where we do not consider “worst” options), which can cause overestimation of preference shares for the topmost preferred options.
For this reason, we suggest using simulations for choice-based exercises only as these are robust whereas MaxDiff simulations are only indicative.
Can you build a custom Excel simulator?
Yes, preference share simulators are commonly customised for specific conjoint studies. It is particularly useful for more complicated types of conjoint analysis.
Is an interactive Excel simulator included in Conjoint.ly outputs?
Yes, as well as the user-friendly online simulator, Conjoint.ly also allows you to export an interactive Excel simulator. To use it, please refer to the
Additionally, you can explore its inner workings by looking at the hidden sheets labelled
SimXXX. For example:
Sim1contains individual preferences.
Sim2translates the simulator parameters into
Sim3is a matrix obtained by
Sim6calculates the individual share of preference through the multinomial logit formula:
To see the above features of Conjoint.ly in more detail you can start experimenting with the Conjoint.ly simulator using “Example experiment 2: Preferences in cars (brand-specific)” in your example experiment library.
Here are also some suggestions for further reading:
- What is conjoint analysis?
- Top tips for specifying attributes and levels in conjoint analysis
- Example report on preferences in ice-cream
Would you like to see more example conjoint reports? Log in to explore example reports.