Cashing in on the New Currency- 5 Ways to Monetize Data

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February 24, 2016 by Updated April 29th, 2024

monetize data

“Show me the money.” That’s not just a line made famous in a Tom Cruise movie. It’s what the CEOs and CFOs of organizations that have bought into Big Data initiatives are now demanding of their IT departments—“Show us how you are deriving monetary value from our data.”

It’s a valid request. After all, today’s CIOs are telling business leaders that their company’s data is its most valuable asset—and that analytics can uncover actionable insights within that data that can boost the bottom line. While this claim is not wrong, the fact remains that many organizations are failing to fully leverage their data for economic benefit. And as data becomes more and more the new currency, only those organizations that are adept at transforming data into dollars will be able to compete.

If your organization is looking to derive more bottom-line benefits from a big data initiative, here are 5 ways to monetize data.

  1. Have a clear Big Data strategy: Your organization may have vast stores of data, but you’ll get no value from that data if you don’t know what to do with it. In order to effectively transform data into dollars, it’s imperative to understand what you want to achieve before any data analysis begins, as doing analysis for analysis’s sake will get you nowhere. Once you have identified your analytics end game you can implement specific strategies to achieve the desired results, always making sure that IT goals stay properly aligned with corporate priorities and business objectives.
  2. Don’t underestimate data relevance: Today’s data is streaming in from multiple sources at massive volumes, velocities, and varieties. And today’s big data analytics platforms can handle it all, from neat and structured data to raw and chaotic, and everything else in between. As a result, the challenge for organizations lies in determining which data sets are relevant and which ones are not. Having a big data strategy in place can help to better make that determination. But the danger of underestimating the relevance of a particular data set to business needs and objectives is still very real and can prove very costly.
    Asking the right questions going into the analytics process can help organizations to identify valuable data sets that would otherwise remain worthless. For example, questions regarding how to improve the user experience of a product or service would help organizations recognize the value of analyzing social media sentiment data to gain a better understanding of customer satisfaction levels.
  1. Get proactive with customer retention: Thanks to the Internet, and the proliferation of mobile devices, today’s customers are informed and empowered like never before. They are also more prone to jump ship when a business fails to meet its high expectations—making customer retention more important than ever. According to Bain and Co., a 5 percent increase in customer retention can increase a company’s profitability by 75 percent. And Gartner Group statistics show that 80 percent of a company’s future revenue will come from just 20 percent of its existing customers.
    In the past organizations took a reactive approach to customer churn, relying on a narrow set of data points to determine how to better serve customers the next time around. But this approach did little to curb customer attrition. In today’s era of big data, organizations can take a proactive approach to reduce churn. Armed with more intelligent tools and data science, organizations can leverage deep and rich combinations of data to gain real-time insights on when and why customers are likely to churn and what steps they can take to prevent it before it happens.
  1. Increase marketing ROI: Big Data has ushered in the era of data-driven marketing. Today’s marketers have access to massive volumes of data, streaming in from a variety of channels. Much of this data is rich with raw customer information brimming with valuable insights marketers can act upon to create more personalized, relevant, and effective campaigns. And while many of these insights are hidden deep within the data, marketers now have the big data analytics tools they need to bring them to light.
    According to McKinsey studies, companies that factor data insights heavily into marketing and sales decisions can boost their marketing ROI by 15 to 20 percent.
  1. Act on Insights: While data may be considered the new currency, the real value lies in the insights brought to light by big data analytics. Along with informing new and better products and services—which for any company is a major advantage—insights can also give rise to new business and revenue models that could literally transform a company. That being said, the value that insights hold will never be fully realized unless those insights are acted on to produce the kinds of changes that can boost profitability and create a competitive advantage. For this to happen, CIOs proposing big data initiatives must get buy-in from business leaders to trust the data and be willing to move out of their comfort zones and make changes according to what new insights dictate.

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