On Bubbles and the Value of Data

In a recent article at Newsweek, Daniel Lyons claims that:

“Data, by itself, is worthless. Facebook is betting it can create software algorithms to extract value from that data—essentially to perform a kind of techno-alchemy and turn zillions of meaningless bits into billions of dollars. Nobody knows if the company can really pull this off…”

I couldn’t disagree more. Today, creating software algorithms to extract value from data is a science, applied by all big companies on the Web.

For instance, the research field of Data Mining focuses on discovering hidden patterns in large data sets. When these patterns are found, what was previously raw data becomes very useful information and knowledge. One example would be an E-commerce company that sells a large diversity of items on the Web. Data mining tools can be used to predict future buying trends and forecast supply demands.

Another important research field is Recommender Systems, whose goal is to recommend items of interest to users based on preferences they have expressed, either explicitly or implicitly. Recommender systems increase both the user satisfaction and the revenue of the companies using it, because the user is exposed to the items that interest him most and thus has a higher probability of acquiring them. The best-known example is Amazon, which is very successful in recommending books to their customers based on their previous purchases.

In the case of Facebook, at this moment they have almost 700 million users, and continue to grow fast in new markets. For each one of these users they have very valuable data, including detailed user profiles and their connections. These data can be easily used to select precisely targeted advertisements, what as a consequence increases the price they can ask for each such advertisement.

We just recently saw the IPO of LinkedIn, and it is now valued at more than U$10bn. This value is not derived from paying users, because most services are free. The real value of LinkedIn comes from more than 100 million very detailed professional profiles, including precious personal information that no other company has. Again, this allows them to display advertisements that have a high probability of being clicked, and thus a high probability of generating revenue.

Facebook and LinkedIn are not bubbles. I and my friends at Yahoo! Labs are working hard devising new ways to extract value from data. We know how valuable data can be. None should underestimate it.

About Hayim Makabee

Veteran software developer, enthusiastic programmer, author of a book on Object-Oriented Programming, co-founder and CEO at KashKlik, an innovative Influencer Marketing platform.
This entry was posted in Data Mining, Recommender Systems and tagged , . Bookmark the permalink.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s