Customers are the important part of a direct selling business. For retaining the customers is a difficult task for a business. Companies are introducing discounts as an incentive method for retaining the customers. But every customer does not like discounts. Some of them like receiving recognition or any special status.  

With hierarchical Bayesian demand models, companies can understand what distributors and customers consider a priority, whether it is pricing, value, status, or convenience. They get clarity on each persona and their preferences on pricing and discounts. Persona-based pricing can improve average order value by 8-12% and cut down discount leakage by 15% along with an increase in profits. With this Bayes model for pricing analytics companies can understand the sensitivity levels of each persona to discounts and value add-ons. With this, companies can create different offers for everyone like discounts for segments who are price-sensitive, bundles for personas who prioritize value, exclusive offers for those who choose status, and services for segments who choose convenience etc. 

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