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Conjoint analysis

Conjoint analysis is a highly regarded market research technique to quantify drivers behind the choices that customers make when faced with different product, service and pricing options. Used to understand purchase decisions and to calculate price sensitivity, conjoint analysis allows you to optimise your products.

Do customers go for high price, high quality or low price, low quality or somewhere in between? Conjoint analysis quantifies and models this decision-making, measuring what customers really value.

Find out all about conjoint analysis from the links below, or contact us for help, advice or information.

Conjoint analysis and choice models

Conjoint analysis modelling Conjoint analysis is an advanced market research technique that gets under the skin of how people make decisions and what they really value in products and services (it also known as Discrete Choice Estimation, or stated preference research). Conjoint analysis involves presenting people with choices and then analysing what were the drivers for those choices. Our interactive conjoint analysis demonstration shows a simplified example of this process at work or our simple conjoint in Excel example.

The output from conjoint analysis is a measurement of utility or value and is perfect for answering 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?" In addition these utilities are used to build market models that enables forecasts to be made of what the market would choose given different product or service designs.

Conjoint analysis demonstration

Conjoint analysis demonstration Below is our interactive demonstration to illustrate the principles of conjoint analysis. We have updated it to be javascript based now (our old version used Java applets). The aim of conjoint and choice research is to be able to predict how choices are made, by working out what a customer values from the decisions they make. If you know what people really value you know where to put your strategic effort (see the market modelling example).

The demonstration is a simplified conjoint example 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 fully worked up conjoint analysis example using Excel to understand the calculations involved.

Conjoint analysis design

Conjoint design breaking into attributes and levels Conjoint analysis and trade-off studies are amongst the most sophisticated forms of market research. The aim is to quantify the underlying values (utilities) that drive customers' decisions, and then to build models  of demand and market forecasts, in order to optimise product or service features. Like any form of research, the quality of the output depends heavily on the quality of the 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.

Flavours or types of conjoint analysis

Flavours or types of conjoint analysis For those new to the subject of conjoint analysis, it is easy to believe that there is only one type or version of conjoint analysis (the one type your agency knows). Or the reverse, and become bewildered by the number of abbreviations and names - eg ACA, CBC, MPC, ACBC, full profile, stated preference, DCE/discrete choice estimation among others.

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.

Conjoint analysis - market modeling demonstration

Modelling markets with conjoint analysis  This is a demonstration of the type of modelling you might get as a result of conducting a conjoint analysis market research study. The aim is to predict market share (strictly share of preference as the model doesn't take into account distribution or promotional effects) and possibly revenue or profit potential by changing product features.

There are other types of market models for other types of trade-off research such as Pricing research or Brand-Price Trade Off research. Models are a major benefit of trade-off studies over other forms of quantitative market research.

Conjoint analysis applications

Applications of conjoint analysis including shelf display for category management Conjoint analysis is used in a wide range of different market research and insight applications from copy testing, to pricing research to product and service design, to defining membership schemes. The list of applications is relatively long as conjoint gets adapted to different purposes. For instance it's possible to use some of the design principles to develop and test areas like website or promotional message design using live in-market testing. Below is a list of common uses.

Conjoint analysis for international markets

International conjoint analysis projects As an advanced market research technique, conjoint analysis is most commonly used by larger businesses and for multinationals operating across several countries where it is important that product design and business strategies reflect both global and local needs. In contrast to traditional scale-based rating approaches, conjoint analysis and techniques like MaxDiff are less affected cultural differences in the way people give ratings in different countries. Consequently international conjoint projects can be an effective method of understanding common needs and desires across global markets. We have expertise in running international conjoint across Europe, the US and into Asia.

Alternatives to conjoint analysis

Alternatives to conjoint analysis for trade-off estimation Conjoint analysis is a widely established market research technique for understanding how people value the component elements that make up a product or service - the attributes and levels. However, in certain circumstances, for instance where there are lots of attributes to consider, or where bundles are being built, it may be better to consider alternatives such as MaxDiff, Configurators, Simalto or a range of other more bespoke designs and choice tasks.

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.

History of conjoint analysis

Conjoint analysis history The earliest forms of conjoint analysis can be traced back to the 1970s having developed from the psychology of decision making and econometric choice theory.

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.

Simple but complete full-profile conjoint analysis

X25_1_excel_example1.jpg Many people ask how the elements of conjoint analysis relate to each other - how do you assign attributes and levels, build profiles and get to a calculation of part-worths or utility scores. In can be easy to talk about conjoint analysis in abstract without quite getting the practical 'this is how it works' element.

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.

Conjoint demonstration - technical notes

X25_1_scissors789895_19201.jpg Our conjoint demonstration is a simplified example of a conjoint exercise to illustrate how choices can be turned into estimates of value. The calculations it uses to estimate the "utility" values, or part-worths associated with the choices being made (as shown on the bars) are simplified.

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.

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