Data scoring is a technique used in data analysis to predict the future behavior of customers. It’s applied in a wide range of industries, including finance, insurance, real estate, and more.

 

Primarily, it focuses on the collection and analysis of historical data from specific situations. Subsequently, it employs statistical models to assign a score to each situation. This score is used to predict future behavior, such as the likelihood of a customer making a purchase, paying off a debt, or having an account delinquency.

 

Scoring is widely used in the financial industry to assess the credit risk of loan applicants. It is also employed in the real estate sector to predict the likelihood of a customer buying a house or maintaining a subscription to insurance.

 

One of the key advantages of this technique is its ability to assist businesses in making more informed and accurate decisions, which can increase profitability and reduce risks. Additionally, it is an efficient and cost-effective technique for analyzing large amounts of data.

 

Data scoring is a valuable technique for any company seeking to gain a better understanding of their customers’ future behavior and make more informed decisions.