Everything is contagious
I’ve been putting off writing a lengthy blog post on this topic for a while, but today I found that both the New York Times and Wired have new articles out on the same subject (see below), so I might as well point to them while at the same time offering some of my half-baked thoughts.
A couple of weeks back, I was listening to a podcast from the SmartData Collective podcast series where a guy named Korhan Yunak talked about predicting if and when a customer would cancel their mobile phone subscription and switch to another provider. All kinds of demographic information, behavioural data and other things have been used to try to extract features that predict such switches. Yunak explained that recent research had found that essentially, subscription switches propagate through social networks. What does that mean exactly?
Phone companies can construct a customer network by collecting “connections” between customers (for example, by linking everyone that has called or texted each other). By simply looking at a customer’s network neighborhood – their direct connections (often friends) and perhaps the friends of friends – the companies can get a huge boost in their predictive accuracy (I’ve forgotten the exact number and metric, but it was a major improvement) .
Now, it is not surprising in itself that people talk to each other and influence each other in different ways, but it was surprising to me that the effect was so strong. It made me think of earlier published work which showed that obesity, happiness and smoking are all “socially contagious” in the sense that they seem to spread through social networks.
As I mentioned above, there is a new Wired article by Jonah Lehrer which talks about these things and has nice visualizations of them as well. There’s also a New York Times article on the same theme by Clive Thompson, but I haven’t read it because of the paywall.
These findings, of course, suggest a new kind of “network marketing” (the “old kind” also goes by the name of multi-level marketing). The idea is that you can use information about a customer’s friends’ preferences and shopping behavior to construct more precise targeted ads and other marketing strategies. Companies based around such ideas include Media6°, which “…connects a brand’s existing customers with user segments composed entirely of consumers who are interwoven via the social graph.” Another company, 33Across, “…uses previously untapped social data sources, in combination with advanced social network algorithms, to create unique and scalable audience segments.” Both companies do this by capturing data from social network sites on the web, according to this article.