The Beginning of the End to Privacy Debates?

  |  September 24, 2008   |  Comments

As privacy concerns fuel debate in Washington, DC, companies are providing alternative methods of targeting that use non-personally identifiable information.

Just weeks ago, NebuAd halted the deployment of its controversial tracking technology due to congressional concerns about privacy. As a result, more companies that provide technology for the purpose of audience assessment and measurement are coming up with solutions that don't store previous user history nor utilize personally identifiable information.

One such company is Baynote, based in Cupertino, CA. Its Collective Intelligence Platform eschews the need for tracking and storing an individual's browsing history. Scott Brave, Baynote's CTO and cofounder, in an interview said, "Traditional behavioral targeting relies on profiling an individual's past online actions and their geographic and demographic information for future analysis and segmentation. To me, that's more of a machine-oriented way of looking at the problem than a human-oriented way. People are primarily creatures of context, which is a socially constructed reality. What we seek to do at Baynote is understand how useful or effective a site and its content are by the behavioral patterns of groups of people."

The Collective Intelligence Platform analyzes information collected from thousands (and sometimes millions) of visitors. This proprietary technology steers clear of privacy concerns because the information is gathered on a visitor's behavior is completely anonymous. Baynote is looking at the bigger picture.

"We're all about understanding the context in which behaviors are happening online in the same way we understand context and behaviors as they happen offline," said Brave. "Social sites such as and Flickr have been hugely successful because they look at how a whole community assesses, interprets, and shares content. In a similar vein, we became experts in watching how everyone is behaving in an online space and understanding their intent within that context. By having curiosity and observing eye, we know how to best meet people's needs."

A Shift Away From Classic Behavioral Targeting

Baynote's approach to targeting appears to be a paradigm shift from other classic behavioral targeting approaches, which tend to focus on the individual. The premise is that the more a technology can learn about a person, the more it can predict what the individual wants. Although this is a valid way of looking at human behavior and interpreting intent, we all know (being human and all), people are simply unpredictable. Married couples can know one another like the back of their hands, yet husbands and wives can continue to surprise each other with their interests and the decisions they make throughout their lifetime.

Privacy concerns aside, there are other reasons to steer the focus of targeting away from previous user histories. "The goal of targeting is to make sure consumers receive the most relevant messaging," said Brave. "Using past purchase history or past online behavior is not the best way to predict what will be relevant to them now. For example, a mother who bought a pacifier online a year ago is not going to be interested in that same product. Her baby is way past that stage. What will be more helpful, instead, is looking at what she's interested in now by examining what she is searching for and where she's browsing. Real-time intent information, plus the collective behavior of other moms with similar intent-to-purchase, is the best way to understanding this mom and help guiding her to the best product."

Baynote uses an algorithm to gauge collective behavior and behavioral patterns. Not only is the approach to targeting unique, it enables real-time testing and adaptation to what people are searching for online. In turn, this enables fluidity in targeting since Web browsers aren't placed into buckets/categories. "By capturing implicit site behaviors and adapting its responses appropriately, Baynote automatically tailors the site experience for each visitor based on the information they and their like-minded peers would find helpful -- regardless of whether it is text content, images, videos, or animation," reads an explanation on Baynote's Web site.

Beginning of the End to Privacy Debates?

Companies such as Baynote are offering innovative solutions for assessing consumers' needs and desires. By tapping into the collective wisdom of online visitors, there's no need to track specific user history or personally identifiable information. As the privacy debates continue to happen in Washington, DC, it'll be interesting to see how companies in the targeting space will adapt to the changing rules with different technologies. In the meantime, identifying and leveraging virtual communities of like-minded visitors seems like a good way to keep targeting efforts anonymous and worry-free from privacy lawsuits.

Join us for a new Webcast, High-Touch Personalization, The Successful Marketer's Secret Ingredient, September 29 at 2 p.m. EDT.


Vicky Chen

Vicky Chen is a strategist at Sid Lee. Based in Amsterdam, she works with global clients such as Heineken, Red Bull, Swarovski, and Adidas to create and communicate desired brand experiences.

Vicky was previously a strategist at Naked New York, and started her career as a psychologist, focusing on socio-cultural dynamics and its influence on people's realities and behaviors.

COMMENTSCommenting policy

comments powered by Disqus

ClickZ Today is our #1 newsletter.
Get a daily dose of digital marketing.



Featured White Papers

2015 Holiday Email Guide

2015 Holiday Email Guide
The holidays are just around the corner. Download this whitepaper to find out how to create successful holiday email campaigns that drive engagement and revenue.

Three Ways to Make Your Big Data More Valuable

Three Ways to Make Your Big Data More Valuable
Big data holds a lot of promise for marketers, but are marketers ready to make the most of it to drive better business decisions and improve ROI? This study looks at the hidden challenges modern marketers face when trying to put big data to use.