Price Optimization
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Price optimization techiniques 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
With AI, insurance providers can dynamically monitor the marketplace, boost their understanding of risks to cover, and offer the best risk-adjusted prices. This enables them to stay competitive and retain the trust and accounts of their existing customers.
Feasability
High
Type of expertise/ AI domain
Bayesian Approach, Price Elasticity, Market basket Penetration and Reinforcement Learning Model
Internal data required
Pricing History, Purchases
Pricing of products can impact a business in many ways when it comes to market share, revenues and profits. A key for retailers is to be able to figure out the right price and with big data analytics, they are not only able to determine that number for the market in general but also calculate it with some precision for individual customers.