Some have called them oil fields, others goldmines, but regardless of the name, one thing is clear — organizations across multiple industries are sitting on extremely valuable data. The biggest hurdle that these companies face is monetization. Our team at DACONOMY believes that there are two key forms of monetization, the first is through data operationalization and the second is through data sales.

Selling Data

The beauty of most data is that it’s a byproduct of daily operations. Ordinary transactions, customer databases, and routine accounting can all serve as new revenue streams for a company. This data is valuable because it has the potential to provide unique insights that under normal circumstances, would go unseen by other organizations. For all companies, the key to selling data is identifying complementary organizations who have the ability and desire to make the data being sold actionable.

As noted by Accenture, there are five data monetization frameworks. The least valuable is selling raw data, raw data refers to data that has been unprocessed and unanalyzed. Next is selling processed data, this is data that has been pulled from multiple sources, managed and analyzed for consumption. The third is selling data that has been processed using data science, dating mining, and predictive modeling. The fourth includes data presentation, using insights and models to show how the data will help the company. Finally, there are companies which provide end-to-end data solutions, providing high-value data at scale.

Operationalizing Data

Data can also be operationalized; this is the process of taking data and using it to improve the internal operations and external strategy of the company. Operationalizing data comes in many forms, and it can be applied to all aspects of a company. A great example is pricing; companies are using analytics to optimize pricing strategies. A study conducted by McKinsey found that 75% of a typical company’s revenue comes from its standard products and that 30% of the thousands of pricing decisions companies make every year fail to deliver the best price. With a 1% price increase translating into an 8.7% increase in operating profits — assuming there is no loss of volume. Analytics-driven pricing strategies are helping organizations pinpoint growth opportunities.

Another great example can be seen in marketing campaigns. Companies across multiple industries are deploying data-driven marketing campaigns. By collecting data including customer demographics, buying preference, and much more, companies can develop propensity scores for potential customers and focus their marketing efforts accordingly.

Marketplace for Transaction

The value proposition behind data is clear, furthermore; most companies have the technical capacity to leverage their data. But the missing puzzle piece is still the marketplace for transactions. Currently, data monetization is mainly reserved for data brokers, large companies, and “big tech players” who dominate the market. These big players prevent competition with a restrictive approach to data monetization tools, making it impossible for other large companies, SMEs, and Micro industries alike to participate and monetize directly.

As a result, most companies who own data are not monetizing, selling, or exchanging data. To increase participation in the data economy, there needs to be a standard easy-to-use platform that enables anyone to sell their data easily; this is the essence behind our vision at DACONOMY — a universal decentralized ecosystem.

Large data volumes, low storage cost, and access to cutting-edge technology have made data monetization more feasible than ever before. Although data has become easier to collect and analyze, data transaction is still a developing field. It’s up to companies like ours to push the field forward, enabling more companies and individuals to participate in the growing data economy in the future.