Data collection affords many benefits, primarily to consumers. When companies know who they’re talking to, people get better experiences over time, and even privacy pundits recognize and benefit from this fact.
This isn’t hypocrisy on anyone’s part. It stems from confusion about what it means to respect privacy while using data effectively. To do that well, it’s critical to understand a few things about what behavioral targeting and anonymity really mean, and how they work together.
Let’s start with the first truth: Smart behavioral targeting engines don’t need personally identifiable information (PII) like names, dates of birth and addresses, though people may believe the opposite because they are often asked for it.
Anonymized data can yield relevant, cross-device messages that don’t have to tie back to a specific person; it can draw information from behaviors, patterns and anomalies, which a smart platform uses to make predictions about what they are likely to do, or to be interested in, in the future. This is less work and more precise. Plus, once data is anonymized, it can’t tie back to an individual, guaranteeing a level of security.
The question is, when data is anonymous, what kind of behavioral data can be collected? Behavioral data—or super data—can include gender, what platform someone’s using, pages they’ve visited and relevant affinities, which reveal more about what people will like than gender or generation. All of this is fed into machine learning (or artificial intelligence, for sci-fi lovers) platforms that need human data to learn, creating content increasingly defined by a given viewer’s interests.
It’s not a luxury to expect an app to tailor its content based on what you last did; it’s an expectation. It saves time and enhances experiences.
We have established that you don’t need PII to create those rich, tailored experiences. While some privacy concerns focus on that, the problem is far more subtle. The current technology available is rich enough that we are able do plenty to target prospects without even knowing their names. With this comes an immense responsibility: not only to ask prospects just what would make things easier for them, but what level of engagement they’re comfortable with.
When consumers abandon a shopping cart online, then get a reminder from the company the day after, that is a coherent and valuable behavioral strategy. It has a logical cause: I was on a Web site, I started shopping, I abandoned a cart. I might even still want that stuff, so being reminded is pretty nice. Geolocation can also be a major ally, enabling you to offer a discount to people with an affinity for your brand, who happen to be in the vicinity (something Foursquare, or Facebook, occasionally take advantage of).
The key is not to use these tools so often that it begins to make people more conscious of your strategy than of your value-add.
Using data intelligently, and in a privacy-safe way, isn’t just about shooting adverts to whoever walks by or mentions your name on Twitter; it’s about asking what those metrics mean, and whether you need more information before assuming interest.
The tools are there. It’s up to us to use them wisely. But data and privacy aren’t enemies. They go hand in hand. Respecting the pact with the customer isn’t just protecting an individual’s data; it’s also in the little ways we are mindful of them.