A three-tiered way into the monetization of information that follows the frame of Aggregation, Analytics, and Actionable Predictions.
Just about every company is awash in data these days. From data about your customers and their buying habits to data about the market in general, you've got an immense quantity of information right at your fingertips. But the question then becomes: how do you monetize that data?
I wish to talk about a 3 tiered pyramidal approach to the monetization of data that will make it possible for you to consider where you are and what the next steps may be. We'll look at the credit industry which follows the framework of Aggregation, Analytics, and Actionable Predictions.
In the base level of the pyramid, that is the most readily available and least valuable approach to monetize info, is aggregation. What I mean with this is when you choose information from other sources, for example, your own company, and combine it all together to make an integrated picture. While some of the data sources independently may be interesting, it's if you combine them that they become valuable. By way of instance, consider your credit report. This is information that the credit agencies aggregate such as what credit cards that you have if you've got a mortgage and if you pay your bills in time. By pulling all this data together into a single account, the credit bureaus can sell that information to interested parties in certain volume for approximately $1 a piece. That is not a lot of money, however, they sell an awful lot of those.
The center degree of the information pyramid involves implementing analytics to your data, which means that you process the data in a way that creates insights and helps paint a much clearer image. A good example would be the production of FICO scores, that give lenders a very concise image of your credit rating--which can range from 200 to 800. By analyzing your entire credit history then assigning your credit value an rating, FICO becomes a far more valuable measure than only the raw or aggregated data involved. That's why FICO scores can cost around $5 each to purchase.
That then leads us to the top of the volcano--that is where you produce actionable predictions from your information. This could involve a procedure where you both aggregate and use analytics to a specific market which allows you to forecast the results of a position and do it. It's possible to use your data to provide advice and help make better decisions.
Think about the illustration of how you get offers for credit cards in the email where you are pre-approved for some dollar amount. That's not a random variable. What is happening behind the scenes there's that a firm conducted the data they had on you and marketed it to the credit card business, where they heard that, according to your background, there was a 99% chance you would be able to repay the credit limitation they were prepared to approve you. They could also have the ability to predict the odds that you will accept the offer. That is incredibly valuable advice to get a charge card company to have, something they'd be a payout of $25 to $50 for. Because they can do it on the predictive information - it's 25 to 50 times more precious than simple aggregated data!
The example we researched shows how you'll discover ways to take your raw data and find various ways to monetize it. The more you may use analytics and predictive evaluation, the more valuable your information becomes.
Ask yourself what sort of data you have in your company and how you might be able to turn it into a lucrative revenue stream using the design of Aggregation, Analytics, and Actionable Predictions.