B2B marketing and product teams use bundling and pricing strategies to maximize revenues and market share. Setting those strategies raises many questions: Are we leaving money on the table? If we increase prices how many customers will we lose? Will the higher margins make up for it? If we lower prices, will we win enough new customers to offset the loss of margins? Should we use a good-better-best bundling strategy? Is there a slimmed-down version of our product that appeals to cost-sensitive prospects? Will it cannibalize our other offerings? Is there a market for a premium bundle of features and services?
Isurus uses standard research approaches and tools to help clients answer these questions and identify the optimal bundling and pricing strategies for their offerings.
Our preferred method to bundling research is to use choice-based modeling such as conjoint or discrete choice. In these approaches, rather than rating the importance of individual features, buyers make choices between product configurations, which is closer to real-world decisions. When choice-based modeling is not viable due to budget limitations or other considerations, Isurus employs traditional quantitative research to deliver more directional, but as statistically reliable, bundling data.
When the question is purely one of pricing, we use two standard pricing techniques: The Gabor-Granger series and the Van Westendorp Price Sensitivity Meter. The data from these techniques can be used to plot demand curves, calculate price elasticity, and identify optimal price points and ranges.