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This is a question regarding an A/B Test that we are running in my department. We are doing dynamic pricing of a product using Machine learning and doing an A/B test to compare with the current mode of rule based/static pricing.

The hope is that the dynamic pricing using Machine learning will product an uptick in Revenue.

  • Control - will sell the Product at fixed set of price points (Mostly Rule based slab pricing)
  • Test - Will sell the same product at dynamic Price (Dynamic Pricing using Machine Learning)

A sample of how the products could be sold is below.

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Which test would be apt to check if our solution (Test) indeed provided revenue improvement or not?

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  • $\begingroup$ I feel some information is missing here... Probably you could share data sample to understand better. Is the "control" only one price associated to a given product? $\endgroup$
    – Pitouille
    Commented Aug 26, 2021 at 11:05
  • $\begingroup$ Sure, I will share a sample data for better understanding. The "control" is not one price always, that also changes but the changes are based on some written rules. The machine learning that we are doing challenge those written rules and claims to being more intelligent. $\endgroup$
    – sharathnatraj
    Commented Aug 26, 2021 at 11:27
  • $\begingroup$ @Pitouille - Added sample data $\endgroup$
    – sharathnatraj
    Commented Aug 26, 2021 at 11:37
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    $\begingroup$ @sharathnatraj Furthermore, what is your experiment's success criteria in terms of a concrete metric/evaluation criteria? Increasing ASP (average selling price) is good generally, except in the case where the total number of sales drops. $\endgroup$
    – B.Liu
    Commented Aug 26, 2021 at 12:51
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    $\begingroup$ @sharathnatraj Please consider updating your question with the clarifications you have provided - comments might be deleted without notice. $\endgroup$
    – B.Liu
    Commented Aug 26, 2021 at 13:57

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