Transactional Data

Price Optimization


Price optimization techniques focus on finding the price that maximizes a defined cost function (or company’s margin), considering many factors like flexibity of prices, location of the customer, seasonal effects, special events and competitor pricing.
Price automation without machine learning is based on pre-defined pricing rules, while with machine learning implies training a model capable of automatically pricing items adapting to changes in the environment in a much richer and dynamic way.

Benefits for the company

Selling a product at the right price is not just for the customer but also for the retailer or manufacturer is an important task. The price must not only include the costs to make the product but also should also take into account the ability of a customer to pay for that product while keeping in mind competitor prices as well in order to drive profits.



Type of expertise/ AI domain

Bayesian Approach, Price Elasticity, Market basket Penetration and Reinforcement Learning Model

Internal data required

Pricing History, Purchases

Research Paper

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