How Social Data Will Save the World
Any economics text book is no light read. The weight of their pages are magnified when viewed against the backdrop of a 140 character world. Yet, social media and economics actually have a lot in common – no one really knows what their good for. To the uninitiated, a tweet is a conundrum – and why anyone would feel the need to “share everything” with “the whole world” is just baffling. For the social savvy, we’re organizing the data of our lives – 24/7 scrap-booking, if you will. Why anyone would keep a box of fading photos under the bed is just ridiculous, to us. The same dichotomy describes the difference between modern and traditional economics – the younger generation, just doesn’t get the old and vice versa. All of this is changing. Economics is becoming the applied science of the 21st century and Social Media is producing a quantity that will soon out rank gold as the most valuable substance on the planet: Customer Data. The interesting thing is that these two mini-revolutions are taking place at the same time.
Professor Noah Smith (of the Noahpinion Blog) writes on Quartz.com that – finally – new economics is replacing the establishment. Smith gives great examples of applied economic theory – mostly in private enterprise – that has had resounding success in every case. For example, Google owes much, if not all, of its success with Adwords to its chief economist who developed and implemented Auction Theory to sort ad bids. In a discipline invented by philosophers (Adam Smith/ David Hume) – its a huge victory to claim that the collective body of economic knowledge actually has some practical use. Social analytics, data-driven marketing, and certain views of business intelligence are doing something similar for social media: they’re creating the theory behind all that practicality. Social media is not just practical, its purely practical (i.e. the purpose of using Facebook is to use Facebook). Corporate use of social media has seen some success, but often times CEO’s will face a moment where 75 million followers doesn’t mean much less than 150 million. Data – on the other hand – is the Social Media ROI Holy Grail. Consider the recent acquisition of GNIP by Twitter as one of many examples. The self-reported preferences, interests, hobbies, habits, and plans of one individual are infinitely more valuable than a single page like, follow, or circle. But – like applied economics – Social Data theory has only recently come of age. We’re only just starting to present the data in a way that businesses find immediately useful.
Mblast represents customer data as a profile. We view our customer profiles as the center of a true 360 degree view. All of the content a person creates is connected back to their Mblast profile: on Facebook they talk about X, on Twitter they talk about Y, when blogging they write about X and Y. Our profiles are windows into the history of an individual and a map for ‘where’ they’ll be in the future. We combine the social data with demographic, geographic, and sociographic data – to round out understanding of the individual – and leave room for the integration of custom enterprise data sets. We see ourselves as creators of theory: our product represents an opportunity to use social data in a variety of ways which we have discovered to be most effective at generating new sales. It is truly an exciting time to be working in Social Analytics. The same goes for Economics.
That the two disciplines would be undergoing such great change at exactly the same time is no accident. Professor Smith notes in his Quartz.com article that “the information age and [it’s] tidal wave of data,” are largely responsible for the shift from Theoretical to Applied Economics. The Information Age is the Social Age and the “information” being shared is “social data.” This is novel: data from social media, blogs, and articles is changing economics – for the better. If we think about it, economic theory is forming the basis for social data theory. On the surface, brands demand a return on their investment in social media and the market supplies ROI models until the brands are satisfied. On a deeper level, the demand is for an economic model (i.e. social media investment > monetary return). The real question is: where do we go from here?
The future is always uncertain – economists know this, social media strategists know this (although both may be willing to go to great lengths to qualify that uncertainty). We – at Mblast – can say with a high degree of confidence that the future will be in the hands of they who hold the data. We believe that the beneficial merging of social data and economic theory are a prime indicator of this phenomenon. Its almost as if the years of economic theory were spent preparing for social data – no hypothesis could be tested, no experiments could be designed, no peer reviewed articles could be published without data. Now, all of the sciency parts of economics are possible and the data they’re using is the only data economists were ever interested in – human interactivity habits (a.k.a. social data). If you consider many of the soft-sciences, you’ll find each discipline ripe with theory and light on application – like with economics there has been a deficit of data. But like economics, the data they pine for is social data. All we need to do is connect our API.