Discovering conjoint analysis
Conjoint analysis is used to quantify the drivers behind the choices that customers make when faced with different product, service and pricing options.
We provide a full range of conjoint analysis solutions, training and consultancy from basics like CBC upwards, to interactive models and forecasts to understand what drives purchase decisions and uncover customer price sensitivity to optimise your products and services.
Do customers go for high-price, high-quality or low-price, low-quality or somewhere in between? Identifying the right balance point is a classic business problem. Conjoint analysis quantifies and models this decision-making, measuring what customers really value to identify the best solution for the business.
This section explains all about conjoint analysis from principles to models, to advanced options and alternative methods. Discover our conjoint demonstration and pricing explorer to explore how these techniques improve business decisions. For any questions about carrying out conjoint analysis, contact our helpful team for advice or information.
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Conjoint analysis - introduction and overview |
Outputs from conjoint analysis are measurements of customer value called utility or part-worths. Utility scores can be combined to build build market models and forecasts to answer questions such as "Which should we do, build in more features, or bring our prices down?" or "Which of these changes will hurt our competitors most?" to allow the business to better optimise product and service design to customer needs. |
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Conjoint analysis demonstration |
The demonstration below is a simplified example of a conjoint exercise that uses a QuickLearn algorithm and works best if you are consistent in your choices. See the technical notes for more information and a comparison with full/commercial conjoint analysis. Alternatively look at a worked up conjoint analysis example using Excel to understand how calculations can be made. |
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Conjoint analysis design |
For conjoint analysis, in particular this means choosing the right flavour or type of conjoint to use and ensuring that the design of the attributes and levels, the way the profiles are shown and the number of choice tasks meets the research, analysis and business requirements. |
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Flavours or types of conjoint analysis |
Most conjoint analysis studies carried out professionally use Choice-based Conjoint (CBC) for pricing and brand value studies. Newer adaptive types of conjoint such as Adaptive Choice-Based Conjoint (ACBC) or menu-based conjoint are used for more complex studies. MaxDiff is a commonly used adjunct or substitute for conjoint analysis with large numbers of items. However, different types or "flavours" can be used, depending on the task at hand, and might incorporate Buy-your-own tasks, configurators or take the basic principles and extend them to create tailored designs for specific markets. |
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Conjoint analysis - market modeling demonstration |
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Conjoint analysis applications |
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Conjoint analysis for international markets |
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Alternatives to conjoint analysis |
Note that we would consider options such as Discrete Choice Modelling (DCM), stated preference research and elements like shop-display tests for pricing as 'flavours' of conjoint analysis rather than purely distinct. |
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History of conjoint analysis |
Key developers have been Paul Green (Marketing use of decompositional models), Jordan Louviere (Choice-based conjoint) and Rich Johnson (Sawtooth Software and Adaptive conjoint methods) and more recently Sawtooth has pioneered a number of new approaches. |
MaxDiff and hierarchy of needs studies |
MaxDiff and Hierarchy of Needs studies are used In new product development, concept testing and building marketing messages to identify what customer priorities are for development or marketing communications. Often businesses have a long list of potential product benefits and the key is in identifying which to prioritise and which work best with which audience. Our specialist MaxDiff or hierarchy of needs studies allow you to test up 40 or 50 benefits in one go, both singularly and in packages so you know where customer priorities lie. These are designed to be very quick and simple to carry out, but to produce market models that allow you to see how combinations of options compare against each other. | |
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Simple but complete full-profile conjoint analysis |
One of the original flavours or types of conjoint analysis is Full Profile and this is relatively simple to demonstrate. The attached Excel spreadsheet 📎 shows how a simple small full-profile conjoint analysis design can be built and analysed using Excel. |
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Conjoint demonstration - technical notes |
This article outlines some of the technical notes and issues around the demonstration. There are actually several "flavours" of conjoint analysis depending on the task at hand and we have a simple Excel-based spreadsheet to show the general principles of calculating utilities. |