Now, as a customer intelligence analyst, I preach a “consolidated view of the customer” to clients nearly every day. I advise retailers, CPGs, and others that creating an optimal experience for customers is nearly impossible without having a clear understanding of their needs and preferences, across all channels and lines of business. But what Google’s doing extends well past traditional “single view” and into “personal data locker” territory.
On the face of it, Google claims that it’s making these changes for the same reason: to improve the user experience. But to remain profitable and keep providing free services to several hundred million users, Google will also use its vastly increased insight about users to sell better targeted (read: more expensive) ads to advertisers.
Over the weekend, one of the most reputable online retailers in the US, Zappos, broke the news that its database was hacked and that the information for about 24 million user accounts was breached.
How do stories like this affect consumers’ attitude toward online privacy? In our August 2011 Community Speaks Qualitative Insights report, “Consumer And Online Privacy: How Much Information Is Too Much?” (available for Community Speaks subscribers only), we found that online privacy is one of the most concerning topics in online users’ minds. Two-thirds of US online consumers report being very concerned about the recording and collection of their personal details by websites.
Most marketers and customer intelligence (CI) pros tend to lump together most types of customer data. Sure, things like passwords and social security numbers are considered more "sensitive," but for the most part, the systems that protect all the data -- and the privacy policies that communicate their capture and governance -- are largely the same.
Individuals see different types of data differently -- they're most worried about what we consider individual identity data, and far less concerned about the capture and use of their behavioral data.
Most consumers are willing to share their data in exchange for value. But, what they consider "valuable" is very age-dependent -- in other words, the same consumer isn't equally motivated by discounts and cash rewards.
The ad network ecosystem will ultimately be forced the pull back the curtain of Oz to reveal to customers the machines and levers behind targeting technology. As illustrated in my paper, the predominant approaches are full targeting vesus opt out, but this is not enough choice. Segmentation strategies and targeting techniques used by ad tools are hidden within engines and will need to be surfaced to customers so that they may verify, modify, and importantly play with them.
This isn’t easy, however, as the mathematical vernacular of targeting technology with confusing terms such as graphs, nodes, and vectors are unintelligible to most. Metaphors will be needed to distill the complexity for customers. One of the approaches to take will be similar to how optometrists work by showing the customer different "lenses" (perceptions) held about them and subsequently allowing them to choose. These "lenses" may not just be rich segmentation concepts but will include social and individual assumptions too.
Where does this transparency and explanation rationale take us?