Estimation of Price Elasticity for New Customers in Home Insurance


A large provider of home and car insurance in the US


The increase in competition in the insurance market has led insurers to consider a more demand-based approach for pricing. Insurance companies need a better understanding about their consumers’ behavior in order to increase the conversion rate and retain the current consumers. In particular, the premium amounts play a crucial role in decision making of insurance consumers.

For this aim, estimating the elasticity of price during insurance purchase and renewal is very crucial for insurance companies. It is not practical to offer multiple prices to a consumer, and thus the best solution is to estimate the elasticity using data science methods based on quotes data.


  • A range of information about the consumer is recorded in a quote and it is necessary to rank them based on their importance for decision making of consumers to purchase/renew the insurance
  • Using an open source analytic framework such that it is possible to automate and productionalize the modeling process with a high efficiency.

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