Amazing discoveries start with an innovative mind willing to look at things differently. Take Columbus, they said he was crazy for sailing the ocean blue in search of the “new world”. Well here’s another outrageous idea for you! What if you could use your Big Data project as a way to make additional revenue? Here are some ideas so that you can begin to chart this unknown territory with your Big Data, and turn your discoveries into dollars.
3 ways to monetize your data
It is logical to use company data to save money and find cost savings internally. But what if you take another approach with that same data? Check this out-- U.S. News and World Report was able to make their own discovery. They created the criteria and collected the data on college rankings for decades. And each year universities fight for the top rankings in their region or for a particular education track. They produced these ranking reports geared toward the prospective student. One day they stepped back and took another look at the rich data they had collected over the years, realizing they had another (big) market for this information. If they could package and sell it in a new way, to the colleges and universities, they could provide valuable insight and create new revenue streams!
So here are some tips to help you think outside the box with your Big Data.
1. Make it unique
Think of ways that you can make the data unique to your audience and their needs. You have data that no one else has, and it can help users make better decisions. Think about who, outside your business, could benefit from this unique information, and how they can benefit. Then apply some additional strategies to really make your data a must have:
Mashup - combine your Big Data with a public data set
What would happen if you combined your data with a data set on data.gov or another public set? Perhaps you work in the public health sector as an executive of a health insurance company. You could overlay your Big Data with government census data to identify healthcare trends that a growing hospital needs to plan for. The hospitals could use your data product to set up their hospital for the future. Here’s a list of companies already using government data in creative ways.
Predictive Analytics - find the treasure in future trends
Can we apply an algorithm to our data to find some special meaning or make the data more helpful? Predikto is one company that has this down in the railroad industry. They have a great product to predict the breakdown of railroad track safety monitors. Their product analyzes a plethora of data from weather to train loads to provide maintenance crews critical yet simple health-check displays, so they can easily see when these monitors are likely to fail and preemptively send a crew out for repairs before any damage is done.
Composite Metrics - if you build it they will come
Sometimes a simple metric isn’t enough if it can’t fully describe a behavior or the performance of a system. That’s when you need to come up with a Franken-measure: a made-up metric that creates a comprehensive composite to capture complex concepts. Think Google’s PageRank or the NFL’s Passer Rating. PageRank combines multiple complex metrics on web traffic and trends in such a way that the end result is something we can understand and use.
2. Put your best efforts into the user experience.
By putting yourself in your user’s shoes, then you can design data products much more effectively. First, like we mentioned earlier, you need to really think about who your audience is and what your audience needs to get from the data. How does this impact the way you tell the story of the data, and how you design the product so that the users can see the value immediately?
More often than not, the heart of the designer’s message is lost among all the metrics and charts. In this flurry of enthusiasm to display tons of data, little attention is paid to the user and guiding them on how to consume the information.
Remember, your data consumers are not the experts in the data like you are. Your users probably have responsibilities other than analyzing data. Give them the high-level path to follow, and let those users who need more info have the option to drill down into the details. Think about the delivery of data much like the way you tell a story, provide a beginning (starting point), middle (critical details) and end (decision points).
3. Start small, design one product first that solves a real problem easily.
It’s better to prototype a data product that is ready to put in front of a user in six weeks instead of six months. This allows you to keep it simple and make adjustments quickly based on what’s working and what’s not. Think like Google. Put out a concept or idea as a beta, study the user responses and feedback and add more capabilities as you go. This kind of logic allows for a quick release, less investment in development of the product and the opportunity to grow with the consumer.
Now that you are ready to set sail and chart your own new data territory, here are more helpful leads to help you do more with your data products!
Join us in December for our webinar on Turning Data into Dollars.
Also check out DJ Patil’s (the U.S. Government’s Chief Data Scientist) free e-book, Data Jujitsu, the art of creating a data product.
Finally, take a look at our own, Zach Gemignani’s slideshare on turning data into dollars.
For a demo of our product, Juicebox, schedule an appointment.