With technology and business lines developing rapidly every second, modern enterprises have all generated terabytes of data. However, very few have realized the true value of the gold mine they possess. The predominant reason behind companies undervaluing their data-mines is the newness of the technology. Not long ago, companies realized they could extract in such massive quantities the fine-grained information about costs, profits, operations, supplier practices, organizational insights and even customer behavior. Although the opportunity has just kicked in recently, it has to be seized as soon as possible. With the increasing commoditization of data, data monetization can provide any enterprise a competitive advantage in the digital economy.
What is Data Monetization?
Data monetization is defined as the process of turning corporate data into currency. The monetary value assigned to data to identify its financial significance to an organization, will now expand the relevance of the information to beyond a particular organization into the line of business. The currency can not only be quantized as actual dollars but also in the form data used as a bartering device or a product or service enhancement. Most companies monetize their data in the following ways:
1.) incorporating measurable business process and operational improvements
2.) bartering information from other players in the business line
3.) “informationalizing” products by wrapping information around their core product and service offerings
4.) productizing information and using it to offer information offerings to new and existing markets
5.) selling data outright via a broker or some agent
Although these approaches differ have different capabilities and commitments requirement, each one of them represents an important opportunity for an enterprise to distinguish itself in the industry.
Why should you monetize your data?
The current conditions in the world of data sciences are suitable for monetizing the same: huge amount of structured and unstructured data; low data storage costs; data-driven marketing strategies that create relevant customer experiences; and improving business intelligence and data-based processes that utilize data analytics. Besides defining the financial significance of information to business processes, data monetization has several auxiliary benefits:
1.) Calculating the cost of replacing or recreating data in the event of its loss.
2.) Identifying the quantifiable significance of data in an organization’s revenue.
3.) Identifying the monetary value of data if sold.
In addition to that, data monetization can help an organization in planning their data-management framework and related processes like business continuance and disaster recovery planning. Moreover, enterprises can also benefit from an increasing brand reputation in the market, higher competitiveness and differentiation in the partner ecosystem, justified investments in Data and Analytics programs and corresponding funds that come their way, due to monetizing the data.
Some ways to monetize your data
A lot of companies across all industries have started to maximize their economic benefit by monetizing their data. While the competition is high and inevitable, it is never too late to start assessing your information assets financially.
The first step to do so, would be stop revenue leaks in the form of services offered by your organization. Using intelligent data analytics, these organizations can identify patterns associated with the services using unique identifiers assigned to each procedure. This can in turn be used to flag cases for potential errors or missing charges or improve the ROI of these services. Another way to monetize your data is by recording and analyzing customer satisfaction levels in a comprehensive form. Organizations offering products and consumer services, like airlines and retail stores use surveys and social media sentiment analysis to better understand customer satisfaction levels.
A lot of evident drift can now be seen in organizational and operational processes across all industries. Conventional goods manufacturers are supplementing their tangible products with flexible software options and services to create new channels for a fresh revenue influx. This not only offers the customers with more choices but also creates a better experience for the customers with higher levels of personalization. Creating a new revenue model and strengthening it with fraud identification and prevention strategies put in place, can help you put a quantifiable value to your data.
The business world is tending towards Data Monetization
Additionally, data-intensive business models like e-commerce and banking sectors use data to measure customer lifetime value and gain insights on customer churn. Traditionally, a narrow set of data points to determine how best to serve customers next time. However, organizations have now started using richer combinations of data and more intelligent tools to assess when customers will likely churn and the why behind it. Moreover, it also highlights what the company should do to preempt it.
Modern data analytics facilitate enterprises to design campaigns competitive enough to ace the industry. Improving ROI on marketing strategies using targeted campaigns will not only minimize your churn but also enable you to assign a financial benefit to your data.
While the industry shifts to newer business values and estimates benefits using new quantifiable definitions, it would be only a necessity to jump into the bandwagon for surviving the transformation. However, an organization needs to innovate and utilize the data-intensive processes to maximize the profits and grow exponentially in the age of data-renaissance.