What Is Data Monetisation?
Most organisations gather large quantities of data on a daily basis, but they only utilise that data within their own internal reports. At the same time, companies competing against those organisations will utilise virtually the same dataset to create revenue-generating products and/or services through a method called data monetisation. To monetise data means to leverage existing datasets to extract value from it; and as such, the initial cost of acquiring the data is now generating income instead of just being an expense.
Why Data Is a Business Asset
Businesses need to regard information as working capital (as opposed to something that simply takes up space). For example: The transactional history of an enterprise, how users behave, telemetry received from their machines, and their customers’ character all possess true economic value in the marketplace. When they are cleaned up, organised, and packaged properly, these types of data could help to resolve issues encountered by other organisations. Therefore, businesses that create systems designed specifically to explore, convert, and present data will reap the rewards of having continued income streams versus only occasional viewpoints.
Hidden Revenue in Everyday Operations
Many businesses don’t realise they’re collecting valuable data even before they collect it. User clicks demonstrate the way users interact online; payment and refund data provide evidence of fraud and product problems early in the purchasing process; supply chain data reveal changes in the demand for products or markets; profiles of customers help illustrate why customers choose to buy; and, finally, device and sensor data provide evidence of how products are performing in the real world. As a result, this type of information can be costly for others to recreate; consequently, it is considered to be an asset.
Turning Raw Data Into Revenue
It doesn’t get very far with a good idea about making money off data and executing it properly. Companies need to determine what data is more valuable than the cost of storing it. Systems need to be created that allow for future growth and return reliable data-driven answers to assist in better decision-making. Raw data must be converted to readable answers so that users do not have difficulty in understanding them. The most effective data product integrates smoothly into the user’s workflow, and so the user will use the product reliably.
What Successful Data Monetisation Looks Like
Data monetisation can cut expense items, increase income items, and help with better decision-making when executed properly. Predictive analytics can help avoid equipment breakdowns. Retail analytics data helps to enhance both sales and inventory forecasting. Payment analytics data reduces fraud and chargebacks. The one common theme across these items is the focus on genuine problems that exist in business rather than on sexy types of technology.