Behavioral Modeling

What is Behavioral Modeling?

Behavioral modeling is an approach used by companies to better understand and predict consumer actions. Behavioral modeling uses available consumer and business spending data to estimate future behavior in specific circumstances. Behavioral modeling is used by financial institutions to estimate the risk associated with providing funds to an individual or business and by marketing firms to target advertising. Behavioral economics also relies on behavioral modeling to predict behaviors of agents that fall outside of what would be considered entirely fact-based or rational behavior.

Understanding Behavioral Modeling

Behavioral modeling simply tries to capture some of the psychology of decision making to provide a better simulation of how decisions are made by a consumer and the probability of a particular consumer making one choice over another. Behavioral modeling is used by companies to hone their value propositions or target marketing campaigns based on the outputs of the model. In this sense, behavioral modeling mainly consists of analyzing data to categorize subsets of people who share similar habits and purchase triggers.

Financial institutions, such as banks and credit card companies, use behavioral modeling to segment and profile the users of their services. For example, a credit card company will examine the types of businesses that a card is normally used at, the location of stores, the frequency and amount of each purchase to estimate both future purchase behavior, and whether a cardholder is likely to run into repayment problems. This data is usually aggregated to clump customers in groups that have similar needs and usage patterns. The customers in a particular group may be offered different promotions to either encourage more card usage or even consolidation of other debts into the existing account.

Real World Examples of Behavioral Modeling

Once you are a customer of a company, they generally want you to be consistent or increasing your interaction and purchases. This is also true of credit card providers. A credit card company may notice, for example, that a cardholder has shifted from making purchases at discount stores to high-end stores over the last six months. By itself, this may indicate that the cardholder has seen an increase in income, or it could mean that the cardholder is spending more than they can afford. To narrow down the options and create a more accurate risk profile, the card company will also look at other data points, such as whether the cardholder is only paying the minimum payment or if the cardholder has made late payments. Late payments may be an indicator that the cardholder is at a greater risk of insolvency.

Behavioral modeling is also used by retailers to make estimates about consumer purchases. A retailer could, for example, examine the types of products that a consumer purchases in-store or online and then estimate the likelihood that the consumer will purchase a new product based on how similar it is to their previous purchases. This is especially useful to retailers who provide customer loyalty programs, which allow them to track individual spending patterns with more granularity. For example, if a store determines that consumers that purchase shampoo will also purchase soap if provided a coupon, the store may provide a coupon for soap at a point-of-sale terminal to a consumer who only purchases shampoo. This type of behavioral modeling has been refined into a subfield known as behavioral analytics.