There is no denying that data has now become a valuable asset for companies all over the world.
Compared to even a few years ago, data collection has become significantly easier, with so many tools and technologies helping in this front. Many companies are flooded with data and since the pandemic, it appears this mountain of data will only grow higher as more businesses undergo digital transformation.
The real challenge, however, is not simply identifying all of this data. In fact, as more companies realize the opportunities that data can bring in improving their business, it’s becoming more clear that finding ways to make use of the data at hand is just as important. Additionally, with several services helping companies organize and learn from the data they have, the market of selling data has grown explosively in the last few years. Data monetization is now trending like never before.
In fact, in a recent study published by Allied Market Research the global data monetization market is to reach USD$370,969 million by 2023.
Companies and executives now fully understand the importance and value of data. The reason data monetization is crucial and becoming bigger than ever before is that data helps to increase profitability via value. With the right data sets, you can learn to understand your customer better and gain deeper insight into the market.
The coronavirus has shown investors and businesses alike that the market is volatile. It can be unpredictable. This is why gaining an edge with data can help to obtain a small hint of predictability and stability into the decisions made.
According to a study by MIT, only 1 in 12 companies are monetizing data to its fullest extent out of a sample from 400 companies in 34 countries. This validates the importance of data monetization strategy and its implementation.
Checking Data Quality
Before you go about deciding to monetize your data, it’s important to first see whether the data you have is ready to be monetized. Unquestionably, the quality of the data matters. The data is only valuable when it is accurate and the sources are reliable. Some key qualities to examine are:
- Relevancy — Only relevant data can potentially benefit the buyer. Make sure to organize your data in such a manner that it should be relevant for a certain company or industry.
- Segmentation — Raw data should be segmented according to the specific purpose of its use. Targeted data holds real-life value, thus segmentation allows for better and more result-oriented potential.
- Data Security — According to Gartner “Information security spending is expected to grow 2.4% to reach $123.8 billion in 2020.” Just as much as data grows, so will the need for secure data. Data breaches or their misuse can result in headaches and bigger legal issues for companies. Hence security is vital to ensure the safe monetization of your data. Authorization, anonymity, and encryption are the keys areas to focus on when securing your data.
What to consider when monetizing your data
Realize the value of your data
It is very important to realize the worth of data for your company first. Your data can be monetized in two ways; externally and internally. Before externally selling the data you have to value the data as an asset, which means there should be good management of the data to maximize profitability.
Simply put, metadata is the underlying data describing the data. This refers to the information about your data — its quality, where it is stored, and how it is sorted. This will give you a fair idea about what amount and type of data can actually be monetized both for external and internal operations. This also lets you understand your data offerings. There are different types of data such as marketing data, operational data, behavioral data. With each different type, there is a slew of information relevant to that, so make sure to try and understand the metadata behind your data.
Price your data appropriately
Raw data usually comes in abundance. This is usually called primary data, while ready to consume is another form. The price of both types of data offerings may differ. Companies are now using AI and machine learning to analyze big data more quickly and efficiently than ever before. AI provides result-driven insights through processing the raw data. You can also trade and exchange your data with other companies, which is mutually beneficial for both. There are two types of pricing that you can use to assess the value of your data. Cost pricing is determined by evaluating the cost of collecting, storing, and transforming the data. Value pricing, on the other hand, is determined by charging the value of your data based on its market value and demand.
Automation and scalability
Data requires analysis and data-analysis requires man-hours. It is important to build an analytical system that is focused more on automation. Missing or redundant data can actually do harm instead of any good. If you can, invest in building a one-time strong analytical system that not only increases the quality and quantity of your data but also ensures its integrity. This will also help you towards scalability to maximize your profits in the long run.
Whether you plan on monetizing your data now or later, it’s always good to start managing your data properly from the very beginning. Data helps in reducing risk, identifying vulnerabilities, and providing more efficient workflow management for your company. It is important to treat data as an asset, with the potential to be sold later down the road.
With so much data out there, it can be difficult tricky to filter through the noise. Making the right decision as an investor or business is difficult. Chain of Demand’s Predictive Insights helps to take the load off by making data easier. Gain access to millions of data points to improve the reliability of your decisions and start exploring our data today.alt databig data