Behavioral targeting is a learning based investigation of consumer behavior. There are three basic ways that consumer behavior can be followed and targeted marketing can be initiated:

Based on the consumers navigation of a website.
In this case, behavioral segmentation can be aggregated by analyzing specific web pages or sites that have been visited, that display targeted content. Based on the content, desired actions can be targeted to that consumer in response of their actions.

Based on content submitted.
In this case, behavioral segments can be made by the analyzation of real-time data entry entered by the consumer. Based on the data entered, subsequent web pages or data being collected, can be specific to the input of the user and targeted upsells or co-registrations, can be displayed.

Based on anayzing return customer behavior.
The most useful information in a marketing database is that which adds to the predictability of buyer behavior. Recency, Frequency, and Monetary Value (RFM) analysis is a method used by LeapLab to conduct analysis and rank a client's customers from least to most likely to buy. RFM predicts buyer behavior as reliably as possible with an analytical marketing tool. It is most effective within a large population, so a client's database must have a universe of at least 100,000 customers who have made a purchase from or through the client before RFM can perform to its potential.