MaxDiff

What is MaxDiff (best-worst scaling)?

MaxDiff is ideal for obtaining preference/importance scores for multiple items such as brands, product features, ad claims, side effects, etc.  MaxDiff is also known as "best-worst scaling" and because of its versatility has become the measurement equivalent of the Swiss army knife for surveys in marketing research and economics.

Why Use MaxDiff?

MaxDiff makes it easy for researchers with only minimal exposure to statistics to conduct sophisticated research for the scaling of multiple items. The resulting item scores are also easy to interpret, as they are placed on a 0 to 100 point common scale and sum to 100.

How does MaxDiff work?

We start with a list of items (brands, features, claims, etc.).  Rather than show the respondent all items at once, we show a subset (typically 4 or 5) of the possible items in each of multiple MaxDiff questions.  For each question, we ask respondents to indicate the best and worst items (or most and least important, etc.)

List items are shown to respondents in a MaxDiff

Respondents typically complete eight to fifteen such MaxDiff questions. The combinations of items are designed very carefully with the goal that each item is shown an equal number of times and pairs of items are shown an equal number of times. MaxDiff exercises focus on estimating preference or importance scores for typically about 15 to 40 items—though hundreds of items could be accommodated in advanced applications.

Analysis of respondent data

We typically estimate item scores for each individual using a hierarchical Bayes (HB) methodology. The HB tool is built right into the point-and-click interface. The default settings are robust, so users with very little background in statistics can obtain good results.  We also offer a built-in Latent Class capability for discovering segments of respondents with similar needs/preferences.

TURF (Total Unduplicated Reach and Frequency) is a portfolio optimization approach that is often applied to MaxDiff data.  For example, TURF can help determine the optimal set of 5 flavors to offer to appeal to the largest number of customers.  The MaxDiff Analyzer tool makes TURF analysis easy.

Use Cases for MaxDiff

Although MaxDiff shares much in common with conjoint analysis, it is easier to use and applicable to a wider variety of research situations. Common use cases include:

• Measuring the importance of product features
• Testing ad claims
• Cross-cultural research studies
• Needs-based market segmentation
• Package design
• Optimizing product lines
• Assessing benefits vs. side effects in health care applications