Last weekend the New York Times Magazine cover story tackled one of the hot topics in the marketing world: predictive data. The Times article by Charles Duhigg focuses on retail shopping, specifically on how Target collects data on their customers and then uses that data to make predictions about what sort of offers might entice customers to change their buying habits and spend more at their stores. Target statisticians have even figured out how to predict when a women is in the second trimester of a pregnancy based on her buying habits -- lotions and nutritional supplements are important clues.
While the article doesn't explore the rise of using predictive data in online advertising, it's a story AdSafe knows well. Just as Target uses data to predict which offers will appeal to their customers, AdSafe provides online data and analysis to help constituents in the real time trading space determine the most effective ways to optimize their advertising effectiveness. And we tell them before they ever place a bid.
In Target's case, the store is working directly with data about specific individuals. While AdSafe doesn't leverage user cookies, we look at the larger context of ad engagement: the content of a given webpage, the volume of users who engage with the ads, the length of time users see the ads, and so on. This approach allows us to see the broader trends that help buyers and sellers alike. For example, we recently sampled billions of impressions to figure out that users view ads on sports pages for over 4X as long as the average across all categories. That number increased 1.5X on Football-related pages on game day Sundays during the play-offs.
And so while we're doing something a bit different than Target -- and doing it online -- the principle is the same. And the principle is that brands benefit tremendously when they are given the tools to proactively zero in on the most engaged customers in the optimal environment.
