Proclivity’s Sheldon Gilbert discusses the nuances of behavioral targeting
Q: What does the future hold for behavioral targeting now that several marketers have pulled the plug on programs in the face of growing scrutiny from federal regulators?
A: There are really two different kinds of online behavioral targeting. One, which I call site scraping, looks at consumer behavior across different Web sites. This is what has been getting all the attention this year because consumers have no idea about how the information is being collected, how it will be used down the line or what the inherent value of collecting this data is. This area may have to be reconstituted. The other area, where Proclivity operates, is permission-based and driven by the need for retailers to better understand how consumers interact with their own brand. This area, predictive shopping behavior analysis, is currently underserved, and one we expect will see a lot of growth in the next few years.
Q: Do you think behavioral targeting has been targeted unfairly by the media and government?
A: Behavioral targeting warrants a certain amount of scrutiny to make sure consumer privacy is not being breached. But behavioral targeting may have become too much of a pejorative lately. Once consumers are educated about how targeting stops marketers from sending them irrelevant messages and start sending them messages that are more relevant, behavioral targeting is no longer threatening. Younger consumers, in particular, are less concerned about the extent to which data about them is used by marketers.
Q: What is new in predictive shopping behavior analysis?
A: It is incumbent upon marketers to have more relevant interactions with customers, because those interactions are less obtrusive and more engaging. This changes everything, with less opt-outs, lower customer turnover rates and more loyalty. We are going to see more granular behavioral analysis with propensity to buy and price preference driving the notion of relevancy. Retailers also need to integrate search engine marketing behavior into any predictive analysis in order to create a more robust way to acquire new customers. There is massive untapped potential in trying to understand unstructured online behavior like blogging and listening to music and trying to make inferences from this to create a richer profile of customers.
Q: Can online shopping behavior be tied to in-store activity?
A: There is an opportunity to tie together the online and offline world with predictive shopping behavior analysis. This would help retailers understand the economic impact of targeting a customer in a store vs. online. We could identify, for example, that a customer is in the exploratory stage online and is just about to convert to an in-store sale. The question for the marketer then becomes, “How do you close the loop? Do you send an e-mail, a piece of direct mail or use some other means?”
