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Conjoint analysis demonstration

Conjoint analysis demonstration The aim of conjoint analysis and choice research is to predict how purchase decisions will be made by working out what customers value based on the choices they make. If a business knows what customers really value, they can use this focus their strategic effort on the areas that matter most to customers (see the market modelling example).

The demonstration below is a simplified example of a conjoint exercise 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.

How to use this conjoint demonstration

Suppose you are buying a Pizza to eat tonight. Below are two options, Pizza A and Pizza B. Use the scale below to show your preference. If you strongly prefer Pizza A select a low number, if you strongly prefer Pizza 2 select a high number. If you have no preference choose 5. Then click [Enter] to see the next choice.

The graph below shows what you value - utilities or path worths - based on your previous choices. To start with everything is valued the same, but slowly the estimator will learn your preferences. Your expected choice is shown under the graph below, so you can see how accurate it gets.

Pizza A

  • size
  • type
  • base
  • price

Pizza B

  • size
  • type
  • base
  • price
  • Strongly prefer A <--
  • --> Strongly prefer B
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
Select a point on the scale then click ...
Your expected choice:

Graph of expected utility values

  • size1
  • size2
  • size3
  • type1
  • type2
  • type3
  • base1
  • base2
  • base3
  • price1
  • price2
  • price3

The graph shows the elements (size, type and base are each attributes, the component parts are levels) that make up the pizza (see conjoint design) and how much the computer believes you value each of them - the utilities or part-worths - the longer the bar the more you value the item when making a choice. As you make choices, the software adjusts what it thinks is driving your choice and calculates what it expects to be the next decision.

For businesses, the value of these types of results comes in the ability to fine tune product and service offering against cost and pricing considerations. People always have to choose between high price, high quality and low price, low quality, but this means there is a sweetspot somewhere in the middle. How do you optimise the value you can deliver for the customer against the costs involved? How much more should you charge for a larger pizza for instance? And do different types of base have different values to customers and so indicate different willingness to pay?

The demonstration is a simplified version of conjoint analysis and will continue indefinitely. In particular it is using a full-factorial selection method. In a standard conjoint analysis, the number of items you select from is more limited (fractional factorial). And the calculations are made after every choice, rather than at the end. However, after 10-12 choices you should see a fairly good representation of the items you like against the items you don't like. It is simplified for illustration and more information can be found in our conjoint demonstration technical notes. A fuller history of conjoint analysis describes the development and progress behind conjoint analysis.

For a live on-line demonstration using full software visit our dedicated on-line research site SurveyGarden. This shows a full real demonstration, but won't show the calculation part.

For more bespoke work we have our own designer which allows us much more control over the display and tasks that can be used. This extends conjoint to emotional association techniques and makes it more applicable for things like repertoire purchasing where a customer is buying a bundle of products, not just individual products.

For expert help and advice on carrying out conjoint analysis for your market contact our conjoint analysis experts

Previous article: Conjoint analysis and choice models Next article: Conjoint analysis design
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