Turning Data into Valuable Data Products
In June, WIRED published an infographic that showed the top feeder schools for big technology companies. It used information available on LinkedIn to see where recruits to companies like Apple and Twitter went to college. It meant that the merits and benefits of a college (and presumably all colleges) could be measured.
While the results were interesting, the part that intrigued me was this novel use of existing “data products” to answer interesting new questions. LinkedIn is essentially free to most individual users, but the data generated through the normal use of the network is an incredibly rich source of insight – so rich that it generated nearly $450 million in revenue in 2013. Advertisers, search firms, and premium users are pleased to pay for LinkedIn’s valuable data products.
For example, if I choose to get a premium account, I can find out exactly who has seen my profile. If I’m a professional headhunter, I can pay to get even more specific information, such as all the robotics engineers who graduated from Northwestern University in 2004. And if I’m an editor at WIRED or a university administrator, I can look for connections between specific schools or degrees and actual careers, to the point of calculating the potential ROI for any given degree.
The evolution from data to data product is important for any company that wants to create more value from its information assets. Of course, there are a number of factors to consider: Who owns the data? What about privacy? How can – or should – I use the data? In part these questions are open for society to answers.
How we make decisions, as individuals and firms is changing. Novel data products are becoming more accessible in guiding out decisions from where to eat (Yelp) to where to stay (Tripadvisor) and even where to go to college (LinkedIn). I do think it’s interesting to look at how today’s big data technology is enabling the creation and monetization of new data products. The value of these data products is also becoming more recognizable. Just as Angie’s List charges, we can expect users to pay up for valuable data products. Companies are finding ways to get people to pay who wouldn’t normally be expected to pay, or to form new markets that wouldn’t be expected to form. It’s changing how business is conducted and who we do business with, and I find that immensely thought provoking.