What are the financial implications of a change in membership price structure or benefits?
Unfortunately, traditional research techniques do not provide sufficiently empirical data to answer these types of questions. As a result, Association executives are making substantive strategic decisions without adequate data.
In 2010, Association Laboratory introduced a novel research technique known as discrete choice analysis to help associations answer these types of questions. Discrete choice analysis more accurately reflects how people make “real” choices and thus provides more valid information to guide decisions.
Our Member Benefit/Price Optimizer process uses this technique to develop a simulator of market action to provide predictive models of membership acquisition, retention and to determine the optimal price.
Standard research asks participants to rate or choose their preferred item from a list of options but generally does not provide adequate information for optimizing the mix of options and benefits that will be most attractive and ensure the highest revenue.
Participants in the research make the same trade-offs they face in the work environment between cheaper, lower performance options and more expensive, more feature-rich ones.
The resulting data allows independent measurement of the utility or value of the features and prices tested. The output of a discrete choice effort is a model that allows testing a variety of “what if” scenarios to see how different options can affect choice.
Discrete choice modeling is a sophisticated, strategic research technique that is particularly well suited to optimizing membership categories, testing different iterations of new products, message evaluation and optimizing the features vs. costs of individual initiatives such as conferences.
The simulator that is produced allows for the analysis to be customized by audience so that products and promotional efforts can be tested in advance and customized for key target markets.
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