In our digitalized world, data is the new gold. It is a potential source of knowledge, efficiency optimization and new revenue. Companies that learn to monetize their data effectively can gain a decisive competitive advantage.

There are two types of data monetization. Direct data monetization involves the sale of data assets directly to third parties or customers for financial gain. Indirect data monetization, on the other hand, involves using the data internally to optimize operations, improve products or services and enrich the customer experience.

In 2023, the bitkom association published the study “Data economy – where does the German economy stand“. The conclusion: almost half of companies expect data-driven business models to make a significant contribution to their business success in two years’ time.

Survey on the importance of data-driven business models in Germany in 2023

Source: bitkom, May 15, 2023, atares representation

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What strategies exist for successful data monetization?

1. Development of data-driven products and services: Companies can develop new products or services based on their data.
2. Implementation of data partnerships and collaborations: Companies can enter into partnerships with other companies to share and monetize their data.
3. Monetization of data through targeted advertising: Companies can use their data to place targeted advertising and thus generate additional revenue.
4. Exploring subscription-based data models: Companies can offer subscription models for their data to generate regular revenue.
5. Creating data marketplaces for additional revenue: Companies can sell their data on data marketplaces to generate additional revenue.
6. Direct monetization: A simple example of direct data monetization is contact lists of potential business customers that influence buyers’ business or commerce.

We see the following examples in the various sectors:

• FinTech: Companies use transaction data to develop personalized financial products and improve risk management models.
• HealthTech: In healthcare technology, data is used to improve treatment methods and personalize medicine. The analysis of patient data enables more precise diagnoses and the individualization of treatment plans.
• Supply chain tech: data integration in the supply chain enables more efficient logistics and warehousing. Sensor data helps to monitor product statuses and optimize delivery routes.
• HR tech: In HR, data analysis is revolutionizing recruiting and employee management. Algorithms can, for example, use applicant data to predict the accuracy of fit for a position.
• Industrial Tech: In industry, the analysis of operating data makes it possible to predict maintenance requirements and production costs, increase the efficiency of production lines and calculate the carbon footprint of new products.
• PropTech: Real estate companies use market and usage data to make investment decisions and optimize building operations.
• Mobility: Mobility data helps to analyze traffic flows and develop efficient, sustainable transport solutions.

The future of the data economy promises an even closer integration of AI technologies that enable automated and intelligent decision-making processes in real time. Advancing digitalization and the growth of the IoT are increasing the flood of data and thus the range of possibilities for data analysis. However, it will be crucial to develop regulations and standards that not only maximize economic benefits, but also protect the privacy and security of individuals.

We are on the threshold of a new era of the digital economy, in which data is the key to sustainable growth and innovation. From investing in innovative start-ups and cooperating with them to setting up our own “Data Gold Units”: let’s seize these opportunities together and tackle the challenge with courage!

Further reading:
Research areas of data economics – Wirtschaftsdienst
Federal Network Agency – Data economy

Franziska Wolfgram
f.wolfgram@atares.team
+4989 – 38888-124