Facebook is able to predict with great accuracy the probability for two people exchanging casually on the network to become romantically involved, says Frederic Filloux, writing in Monday Note about how Big Data can change the economics of digital publishing.
The internet already provides the necessary tools to see who is visiting a web site, what he (she) likes, etc. The idea is to know the user with greater precision and to anticipate its needs.
Let’s project an analogy with Facebook. By analyzing carefully the “content” produced by its users — statements, photos, links, interactions among friends, “likes”, “pokes”, etc. — the social network has been able to develop spectacular predictive models. It is able to detect the change in someone’s status (single, married, engaged, etc.) even if the person never mentioned it explicitly. Similarly, Facebook is able to predict with great accuracy the probability for two people exchanging casually on the network to become romantically involved. The same applies to a change in someone’s financial situation or to health incidents. Without telling anyone, semantic analysis correlated by millions of similar behaviors will detect who is newly out of job, depressed, bipolar, broke, high, elated, pregnant, or engaged. Unbeknownst to them, online behavior makes people completely transparent. For Facebook, it could translate into an unbearable level of intrusiveness such a s showing embarrassing ads or making silly recommendations — that are seen by everyone. (Emphasis Ed.)
It’s good to see more people talking about Facebook’s ability to make predictions based on all the data they collect. However, I have not seen examples of these predictions, am I missing something? Would an example be Recommended Friends? But you haven’t exchanged casually with them yet. Where is an example of this Relationship prediction on Facebook?
It will take a while for the dating industry to reach a matchmaking capability that approaches Minority Report-level precognition. Until then, effective and efficient matchmaking has and will continue to to be the achilles heel of the dating industry.
Without reported results from companies like Match, eHarmony and POF, all the technology in the world doesn’t mean squat if we can gauge how one site performs against another. Matching people is orders of magnitude more difficult than discovering which car you want to buy, but its my belief that the future of the industry depends on better matching, and little else.
This doesn’t mean that the industry won’t grow to perhaps $10 billion over time, but with thousands of sites and very few companies able to do seriously complex matching, sites like Match will continue to outgrow the competition, while leaving plenty of opportunity for the social and niche sites. At this point there are two handfuls of top niche sites and the rest are simply competing based on small-market advertising which often brings about lower customer acquisition costs.
Prediction: Facebook will release a relationship discovery API of some sort that accesses their internal algorithms targeting relationship potential. This will happen after they figure out ads, wall exposure spam and a few other show-stoppers related to exposure and revenue.