Data is King. If you don’t believe me, consider this:
- Rental car companies and insurers are refusing service to people with poor credit scores because data mining tells them that credit scores correlate with a higher likelihood of having an accident.
- Nowadays when a flight is canceled, airlines will skip over their frequent fliers and give the next open seat to the mine-identified customer whose continued business is most at risk. Instead of following a first-come, first-serve rule, companies will condition their behavior on literally dozens of consumer-specific factors.
- The “No Child Left Behind” Act, which requires schools to adopt teaching methods supported by rigorous data analysis, is causing teachers to spend up to 45 percent of class time training kids to pass standardized tests. Super Crunching is even shifting some teachers toward class lessons where every word is scripted and statistically vetted.
(An excerpt from Super Crunchers, by Ian Ayers. Great video of him below - bottom of post. Worth a watch.)
The data validates the fact that data is King.
In the world of Online Advertising, marketers, web publishers and technologists alike are beginning to realize that data is hugely valuable. In the past, advertisements were served to websites based on the content of the website. Today, advertisements are served to websites based on data that is informing the ad server to show that advertisement. As a result of this paradigm shift, the digital media community is beginning to realize that media and data are separate commodities. Where you see your advertisement is very different than how or why that advertisement is there in the first place.
Being able to leverage the power of this online data is great -- but what does it really mean? Let’s take a look at the type of data that is available for digital marketers.
There are two types of data we should look at.
- Singular Data Points
- Multi-Variable Data Points
A “Singular Data Point” is a piece of data that is very cut and dry. It is a binary 1 or 0, “yes” or “no.” For example, if I recently went to an e-commerce travel site, configured a flight for 2 people from NYC to LA, and clicked “view price”, then you could make the argument that I am very interested in flying in the near future. The instant I click the “view price” button, a single data point can be obtained classifying me as “someone interested in domestic travel.” This may hold a ton of value for marketers at the bottom of the advertising funnel (see diagram below) who are looking to convert on a very specific type of user for a very specific product, and has been, still is, and will remain extremely valuable. Some examples of “Singular Data Points” include: Purchase Intent or In-Market Data, Age & Gender and Household Income.
These are data points that explicitly and intuitively describe certain consumer attributes. They are more or less declared characteristics or definitions of a consumer.
“Multi-Variable Data Points” however, tell a very different story. Imagine for example that someone, who happens to be female, 24 years old, and makes $40k/year, went to a social network, checked her inbox, wrote on a friends profile page about last night’s TV show, left that site to read and comment on an article about the New York Giants, uploaded a video about comedy, checked the price of a flight from NYC to LA, and finally, viewed another friend’s photo album who happened to have just returned from a trip to LA. What does this social data say about that user? Nothing? Is it completely arbitrary and meaningless? In fact, it’s exactly quite the opposite. Being able to leverage “dozens of consumer-specific factors” in real time gives a marketer the capability of executing and deploying various tactics such as:
- Influencer outreach strategies
- Creative optimization for advertising units
- Deeper visibility into brand engagement opportunities
- Custom optimization for various and wide ranging back end performance metrics
- Statistical data analysis and research
- Comprehensive search strategies
- Informative and cost effective media buys
Moreover, this social data presents huge opportunities for marketers looking to reach consumers at the top of the advertising funnel, but still has applications toward the bottom of the funnel as well.
Today, there is much debate around the value of social data vs. purchase intent data. How and when it should be used? How much should each cost? How should it be sold?
If we look at social data and purchase intent data as it might be applied in the advertising funnel, it would probably look something like this:
Now let’s consider social data and purchase intent data in terms of value vs. time. If we consider our previous example, we can make the argument that purchase intent data is hugely valuable for a short period of time. If I am looking to book a flight within 2 weeks, that does not necessarily mean I would like to travel a year from now. For a travel related company, that 2 week data point is again, hugely valuable.
Now if we consider our social data example, by demonstrating undeclared and implicit behavior over an extended period of time, we can make the argument that this data has tremendous value indefinitely. If we were to graph social data vs. purchase intent data on a value vs. time graph in today’s environment, the graph might look something like this.
But as companies become even more sophisticated, develop better applications of technologies and data mining, then someone’s day to day behavior might prove even more valuable in the future. This is certainly true when it comes to "creative optimization." It is the idea that a creative ad unit showed to a consumer will be directly linked to their “social data” and that the consumer GENERATES OR INFLUENCES some form of content, message, conversation, or engagement. “Consumer Creative” – or “Social Creative” is the next leap of value to marketers, and as we evolve in the creative evolution of social media/data, the value vs. time graph will probably look something like this.
At the end of the day, having the ability to make educated decisions using comprehensive data sets is what will differentiate businesses from their competitors. It will give the forward looking organizations a way to stay relevant, efficient, and strong, while other companies continue to use outdated and inefficient methodologies.
And as these technologies evolve, become more sophisticated, and create incremental value for marketers, web publishers and consumers, the “data” companies will have a responsibility to uphold the privacy rights of all parties involved. These safety and privacy measures will become, and are already, inherent features of the technologies, because with the power of data comes the responsibility to collect and use the data in ways that provide appropriate protections for user privacy. Responsible industry members will continue to develop practices and policies that can work for marketers, publishers and consumers in this arena (we are one of those companies).
Nevertheless, if companies and marketers want to make the best decisions possible for their clients, they should consult the data for the answers and throw the guess work away. In our world of digital media, find your exact target audience and save money on wasted impressions or eyeballs. It’s all about the data, as well as harnessing the power of consumer driven information.
Co-Authors: Andy Monfried - CEO/Founder of Lotame
Dan Reich - Business Development of Lotame
