Customers do not perceive the same value in your products and services.
Price Segmentation will differentiate your offering and optimize your prices according to the price each customer segment is willing to pay. Traditionally, price segmentation relies on marketing technics such as Price Perception Analysis or Conjoint Analysis, which are based on customer stated preferences (and not real buying behavior). These methods are valuable, but often have a high cost in complex sales environment (ex: B2B) and need frequent updates in dynamic markets.
Mining your data provides an easier and more practical alternative to get insight into customer willingness to pay. We have developed two types of methods depending on the available data sources:
- Transaction Data Analysis
- Choice Models (win/loss analysis)
These methods can use the outcome of traditional market research and refine/update their results based on real buying behavior. They enable to cluster transactions based on observed prices and win rates, as well as to predict a price response function (i.e. win probability as a function of price) for each segment.