Data monetization is the next big source of revenue

As organizations collect large amounts of data from various sources, there is growing recognition that these data assets can drive value beyond traditional uses via data monetization, writes Dr. Saad Alajlan, Practice Lead and Subject Matter Expert in Data Management & Governance at ELM.

Data monetization is a strategy to convert data into economic value, either directly through sales or indirectly through improved business processes and customer experiences. In other words, data monetization is a way to generate revenue from data.

Valued at $3.47 billion in 2024, the global data monetization market size is according to Fortune Business Insights predicted to reach $12.62 billion by 2032, exhibiting growth at a compound annual growth rate (CAGR) of 17.5% during the forecast period. This growth is due to an increase in the volume and variety of data generated from several sources, such as the web, social media, IoT devices, and e-commerce platforms.

Specifically in the Saudi Arabian market, demand for data monetization is growing significantly each year, driven by several factors. One of the most important of these are national data management office regulations (NDMO), which provide a comprehensive framework for data management. This framework encourages companies to realize the economic potential of their data assets by highlighting the significance of data monetization as a core pillar in the framework.

In addition, a major factor that has accelerated data monetization initiatives has been the maturation of data management practices in the government, semi- government, and private sectors. At the same time, significant investments are being made in data technologies, analytics, and artificial intelligence, all of which contribute to enabling data monetization.

Leveraging data for commercials

Organizations are increasingly recognizing the potential of data monetization to create a new stream of revenue and increase their operational efficiency.

To monetize data, an organization needs to sell data directly (direct monetization) or create data-driven products and services for which customers are willing to pay. Examples of direct monetization include offering paid access for consumer insights, industry reports, or predictive analytics tools.

Another method to monetize data is called indirect monetization, which is where organizations use data insights to drive efficiencies, reduce costs, or generate new revenue streams. For example, by analyzing customer data, a company may improve its product offerings, optimize marketing campaigns, or enhance customer experiences.

There are broadly speaking three data monetization approaches that organizations can utilize: improving, wrapping, and selling. In the improving data monetization approach, organizations generate revenue by leveraging data to optimize their operations and improve efficiency. In the wrapping approach, revenue is generated by leveraging data-driven features or experiences to enhance a product’s value proposition, allowing organizations to increase prices or product sales.

Lastly, in the selling approach, new revenue streams are created by commercializing data as an information-based solution.

Overcoming challenges

Many organizations face numerous challenges in monetizing data, such as data quality and monetization strategy. In data quality, effective monetization depends on high quality, and well-structured. Many organizations struggle with incomplete, or inconsistent datasets, making it difficult to extract meaningful insights and value.

In data monetization strategy, identifying the right monetization models requires clarity and alignment with business objectives. Additionally, demonstrating clear ROI and justifying investments in data infrastructure and analytics can be challenging.

Building capabilities

To effectively monetize data and overcome the challenges that organizations face, it is essential to establish several key capabilities. These capabilities include defining a well-structured strategy, ensuring data is accurate and reliable, having the right infrastructure in place, building a highly skilled data science team, understanding customers’ needs, and effectively leveraging organizational data.

Conclusion

Data monetization represents a huge opportunity for organizations to turn their data into a strategic asset, driving both operational efficiency and new revenue streams. Businesses may fully utilize their data assets by investing in appropriate capabilities, such as data governance, advanced analytics, customer insights, and well-structured data strategy.

Organizations that use innovative monetization methods will not only remain competitive but also distinguish themselves as leaders in the data-driven economy as data volume and importance continue to increase. Those that can use data responsibly, effectively, and sustainably will be the champions in the future.