“Data Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Eric Bosco, COO of ChoiceStream.
Massive amounts of data, combined with state-of-the-art computing power, has allowed for one of the most interesting and direct ties between digital advertising and the world of science – behavioral monitoring. Sound familiar? It’s the same way that the Human Genome Project, a large-scale international scientific research project, approaches modeling.
There are 23,000 genes for any human and each person has or doesn’t have various genes that determine specific characteristics such as appearance, personality traits, risk of disease and more. As a result, there are billions of possible genetic combinations – making each person unique.
Similar to DNA formation, a consumer’s personal, behavioral and environmental data shapes potential purchasing behavior which can be translated into "consumer DNA." This level of insight can help brands target consumers who are most likely to respond to a campaign and reach the consumers that are most likely to benefit from their product.
But what if you had 23,000 attributes? Is that realistic? How far can we take the link between genetics and advertising? Farther than you might think. Here’s why:
Variety of Possibilities
There are well over 23,000 behavioral attributes or segments available for purchase on exchanges today. The number is closer to 70,000 including all private data segments. Obviously not all attributes are available for all users in the real-time marketplace, but many of them are. If you look at all the different combinations of attributes, you get trillions of combinations. Additionally, like the genome, the only way to have a comprehensive picture of this landscape is through mapping the entire landscape of attributes, which are collected and multiplied to the entire population. It’s a process and a long-term approach, just like the way genes were mapped nearly a decade ago.
Mapping Attributes to Action
Once you have a view into the complexity of an audience landscape, it’s possible to connect that complexity to the action of an actual campaign. It’s the same way scientists map and explain the relationship between a genetic profile and a specific disease or behavior.
In genetics, there’s a scientific term called a “fitness function.” Based on what scientists know about your genetic profile, this leads to various predictions about your future health and behavior. It’s similar to the correlations scientists make between Mediterranean ethnicity and a lower risk of heart disease, for example.
Looking at a map to predict numerous actions is 100 percent applicable to an advertising campaign. Traditionally, if you were targeting people interested in women’s jewelry, you would only target women. But men also buy women’s jewelry as gifts– and a wide variety of men, for a wide variety of women. It’s a complicated picture and you need a map to analyze and predict the number of relevant audiences. That’s called behavioral genetics, and it’s equally applicable to advertising.
If the first step is to map the complexity, the second translates into action, and then the third constantly updates and adapts profiles based on the dynamic nature of the environment. Over a number of years, people with various ancestries and attributes change. People with Mediterranean backgrounds change their diets and become at-risk for heart disease after all. The same goes for advertising. Audiences change every day. You need to be constantly updating and analyzing your targets in order to maintain the map of which behaviors are most likely to respond to your campaign.
These three arguments aside, the connection is not a complete mirror image. The algorithms and mathematical approaches are different, and there are other influences in biological study that are more complex than buyer behavior. Advertising practitioners need to be expert in advertising as well as complex math. But regardless of the exact closeness of the connection, there is an innate complexity of the current ecosystem that should not be ignored.
Advertisers are not going to get to the ideal campaign overnight, but they need to deal with this complexity in order to get there at all. The complexity needs to be mapped, predicted and analyzed continuously in order to keep up with a growing myriad of choices, attributes and behavior. Smart advertisers must begin making these connections in order to take advantage of this complex, but tremendous, opportunity.