If you have gone to a new web page and seen an advertisement based on things you looked at in your browser history, you have likely been impressed or creeped out. You can thank MIT for a lot of this “programmatic marketing” - and rocket science. It is also why you will probably never make any money on your blog. 

Marketing used to be an inexact science - and in many ways it still is. Print publications count on that, because it means companies have to spend a lot and Return On Investment (ROI) is fuzzy. But the Big Data world and the digital environment takes out the black magic. One company, called DataXU, uses software originally designed to help NASA plan Mars missions, and it rapidly analyzes user data — such as previously viewed advertisements and videos — and data from third-party providers on a user’s interests, demographics, and purchase history.

By mapping out a customer’s tastes and buying intentions, it takes less than one millisecond for the software to determine which advertisement from a pool of clients will most likely ensure that a user will act (by clicking an ad and perhaps purchasing a product) while calculating the cost of the advertisement down to fractions of a penny. It also learns patterns for advertisements that will work best for certain users, or groups of users.

MIT alumnus Bill Simmons PhD ’08, ’s co-founder and chief technology officer of DataXu, began his PhD in aeronautics and astronautics at MIT, working on systems architecture under Ed Crawley, the Ford Professor of Engineering, along with DataXu co-founder Sandro Catanzaro SM ’06. One project involved building a kernel called object-processing networks (OPN) that narrowed down best designs for system architecture based on numerous variables. An example, as described in Simmons’ PhD thesis, is sifting through countless combinations of crews and technologies to design successful rocket launches. 

This work soon earned the team a NASA grant to build software that could determine the most feasible manned Mars missions. Using OPN, they weighed every combination of mission parameter — such as orbit trajectory, crew, rocket size, and technology — and winnowed down a potential 35 billion missions to a mere 1,162.

The resulting 1,000-page report, presented to NASA, “totally blew them away,” Simmons says.

The MIT team’s algorithms could identify and immediately dismiss any logical mismatches that would render a combination of 35 billion missions even partially infeasible, which dramatically decreased the simulation times.

DataXu’s software makes roughly 1.5 million decisions per second to decide if an ad should be placed before a specific user. Then “real-time bidding” kicks in, and companies will have automated thresholds to compete. You're probably not special, companies are competing to show you an ad at the cheapest price, not the highest, because programmatic marketing means there are billions of opportunities per day, and transactions happen within 100 milliseconds.

They are not the only ones, of course, every remnant ad network claims a real-time bidding algorithm, but they are the only ones that got presented to NASA. By choosing the most relevant advertisements for users in real-time, companies see the greatest return on investment (ROI) in online marketing.  The downside to real-time bidding has been a collapse of online media the same way as in print. Big media-backed Vox just acquired Recode because neither is sustainable when everyone is competing for the bottom tier of revenue, and more will follow.

Who absolutely needs to be in front of a science audience? Fisher Scientific, maybe, but print journals will give the digital away for free if equipment companies will buy a paper ad. To everyone else, scientists are nothing special, not wealthy thought leaders like high-technology readers, and not valuable in policy since the political demographic is one-sided, They can just send ads into a remnant network and compete for the lowest price. In that environment, a site with a million readers has no more value than a site with 1,000, because a scientist is no more likely to be interested in a car they see on a science website than they are The Nation.

Universities who are not at the top of the prestige chain also need to be competitive to compete for all that student loan money, so even they use targeted marketing. Franklin University saw a 177 percent increase in requests for enrollment information using DataXu, the company says.