Unlocking Customer Data
Deep insight into your customers’ behavior is the fuel for driving connected marketing campaigns that resonate with your audience. Using the data that you already collect – purchase behavior, website behavior, email interaction – Autotarget compiles and analyzes these data on a periodic (nightly, weekly) basis to sort and categorize each of your customers into one of 125 distinct subgroups. This categorization – Recency, Frequency, Monetary (RFM) analysis – is an industry standard methodology for predicting future interaction based on individual’s level of engagement as represented by the subgroups or personas.
Each night, your customer database is analyzed and re-categorized based on that day’s activities: a click in an email, a website visit, a product purchase,, a social share or other meaningful interactions as defined by your business needs.
RFM Primer: Analyzing Customer Behavior
At its simplest, RFM is the mathematical basis for the marketer’s intuition about customer involvement. Recency (R) acts as the primary indicator of engagement. The more recently customers interacted with your brand, the more likely they are to do so again. Frequency (F) is the second indicator. Customers who often interact with your brand are more likely to do so in the future. Finally, monetary (M) value is the third factor. Customers who spend more with you are more likely to spend again in the future.

