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Getting Started with MaxDiff Projects

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Qtip: MaxDiff Projects are an additional purchase. Please contact your Account Executive if you are interested in learning more about this product.

What is MaxDiff analysis?

MaxDiff (Maximum Difference) is an advanced survey research technique that is used to obtain preference and importance scores for multiple items. This is done by presenting respondents with samples of the full list of items you wish to assess, and then having them mark the items they prefer the most and the items they prefer the least in each set.

MaxDiff is a type of best-worst scaling that relies on paired comparisons. Thus, as respondents mark their preference for specific items against a list of other items, MaxDiff seeks to find the maximum difference in preference in order to identify the features your program should be most focussed on providing for customers, and which you can set aside.

Attention: MaxDiff projects must have less than 10k responses. Any responses over this limit will not be included in analysis.

When is MaxDiff analysis used?

MaxDiff should be used when trying to measure the relative importance of a product or service’s feature in influencing your customers. With this information, you can identify trade-offs vs. areas of focus for developing your product or service.

Example: In trying to run a MaxDiff on the products offered in a shoe store, you may include the following:

  • Reasonable prices
  • Formal wear options
  • Many color options
  • Weather-proof materials
  • Comfortable soles
  • Durability

Features (or attributes) are the aspects of the product or service you hope to find the importance of or preference for. In general, we recommend you have a minimum of 12 features and a maximum of 25.

Qtip: While you can adjust these features to fit your experimental model, MaxDiff projects will not allow you to have less than 8 features or more than 30.

What is the value of MaxDiff analysis?

The value of MaxDiff analysis is that by asking respondents to make choices rather than expressing strength of preference by using some type of numeric scale, you are eliminating scale use bias. For example, if you provide respondents with a matrix table and ask them to simply rate importance on a 5-point scale from “Not Very Important” to “Very Important,” you may find that respondents are generally high-rating or neutral on all features, making it difficult to determine where to make trade-offs. MaxDiff forces respondents to make these trade-offs so that when it’s time to allocate company resources, you can make decisions that have a positive influence on your customers.

The MaxDiff question is also simple, so respondents from various backgrounds and demographics can provide reliable data.

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