Understanding Behavioral Analytics
Overview
Behavioral analytics refers to the ability to uncover meaningful patterns of behavior in human interaction data, uncovering clusters of people that demonstrate a propensity to go through similar sequences of actions, such as clicks on web pages, online or offline purchases, responses to marketing offers, etc. The payoff from understanding these behavioral patterns is huge: you can use this insight to optimize your web site, influence purchasing behaviors, increase response rates, and ultimately drive actions that you care about.
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Examples of Behavioral Analytics
Look at a website as an example. On a first visit, a visitor came to a web site, performed a search, looked at a few pages, and then left the site. Upon their subsequent return, they made a purchase.
Through Quantivo's Affinity Finder, you can take this behavior along with hundreds of millions of other customers' behaviors and discover the significant patterns related to the purchase event. For example, you might discover that visit number is the best predictor of the likelihood of a purchase, uncovering the fact that visitors first come to this site to do product research, continue their research elsewhere, and come back later when they are closer to a decision. Armed with that information, you can now optimize your website, focusing on first-visit content and enticing visitors with a discount to purchase on a repeat visit.
Another popular example of behavioral analytics is market basket analysis (MBA), also known as product attachment or product affinity analysis. Quantivo enables you to uncover the significant relationships of what sold with what under different scenarios, for example with seasonal products, with products on promotion, from loyalty customers, etc.
If your data contains demographic or other information about your customers, the value of behavioral analytics can be increased even further. Quantivo's segmentation and pattern finding capabilities help you combine behavioral and demographic information to sort out which variables - age, gender, location - are the most significant for yielding predictive clues to future actions.
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Behavioral Analytics vs. Operational Reports
Operational reports provide ample information about past performance: purchases, number of responses, page views, click-throughs, etc. They tell you how well you performed yesterday, last week, or last month, and allow you to compare to previous periods. This information is critical for reporting on the health of your business, what might be expected if the trends continue unchanged, and areas/metrics to which you should paying attention.
However, the important difference between behavioral analytics and operational reports is that the latter gives you little guidance on what to do next. Behavioral Analytics provides you with the insights necessary to truly understand how customer behaviors can be used to guide your customers to the desired outcome, whatever that may be.
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