Recommending Discount Levels for B2B Customers

The Opportunity

A large animal health company wanted to create more rational discount structures for their B2B customers in order to improve retention while limiting excessive discounts. However, they did not know how many discount tiers to create, which customers should belong to each tier, or how customers would respond to changes in discounts.

Our Approach

We brought together a variety of advanced analytics techniques to:

Estimate each customer’s likely response to discount changes using price elasticity modeling (for those with sufficient purchasing history).
Identify groups of customers that were similar across a dozen important characteristics. This suggested that twelve discount groups would be appropriate.
Recommend discount levels for each customer based on their discount history, elasticity, and the difference from their group.
Build a visual tool with all relevant data to allow management to make judgment calls for individual customers.

The Impact

The largest discounts in low-elasticity groups were reduced.

The range of discounts was reduced so that customers within a group were similar.

Sales reps were given guidance on the appropriate discount tier for new customers based on their key attributes.