B2B sellers can charge their customers different prices for the same products, and often can even change the price from one purchase to another with little notice. Obviously, this kind of "price discrimination" creates plenty of opportunities to increase short-term profit. However, it can negatively impact the development of trust needed to establish a long-term relationship with buyers. For this reason, a good statistical methodology should be able to predict the short-term impact of pricing as well as the long term effects of pricing decisions.

B2B pricing decisions differ substantially from those within the business-to-consumer (B2C) market because of the high complexity of the business transactions, where the customer needs to make several-interrelated decisions, and the salesperson needs to be able to "read" the customer mindset before generating a quote.

At Dunn Solutions, we realized that it is this complexity that creates tremendous potential for increasing profits by leveraging machine learning.

This video shows how machine learning can be leveraged to accurately model all these interdependent decisions and maximize profit in B2B!