Licensing Data for a Competitive Advantage

Data licensing can give entrepreneurs and executives a competitive edge by unlocking valuable insights and directly boosting revenue. 

Imagine a newly opened coat store.  

To decide how many S, M and L coats to stock, it licenses the sales or inventory data from a shirt store in its neighborhood. This buys the coat store a perfect understanding of the upper-body clothing sizes in its target market. The shirt store, on the other hand, just made additional revenue from their data without doing any extra work. 

In this article, I explore how data licensing can transform decision-making, enhance innovation, and increase revenue.

Beyond internal silos — The power of external data 

All businesses generate vast amounts of data internally — and smart businesses use every bit of it to drive their decision-making.

However, relying solely on internal data can create blind spots. You often need to add external data to provide a broader context, allowing organizations to see beyond their own silos. Unique data sources can also help in differentiating your business. By licensing data from reputable sources, companies gain access to market trends, consumer behavior, and industry benchmarks. 

As a business owner, consider data licensing as a pathway to valuable information, product enhancements, and competitive differentiation.

A good example of this is Walmart’s negotiation of a data partnership with the Chinese tech giant JD.com. Through this collaboration, Walmart gained access to JD’s extensive data on consumer behavior in China. This allowed them to make informed decisions about inventory management, pricing strategies, and targeted marketing. 

Data licensing let Walmart buy an understanding of the Chinese consumer goods market that its internal data would never have been able to substitute. 

Monetizing your data assets

Businesses often overlook the value of their data as an asset. 

Licensing data to other companies can create a new revenue stream. For example, hospitals can share anonymized data on medical outcomes with pharmaceutical companies for drug research. Ride-sharing platforms can license traffic data to urban planners for better city infrastructure. Airlines could license data on flight bookings to hotel chains.

While data licensing offers opportunities, ethical considerations are crucial. Companies must ensure data privacy, comply with regulations, and maintain transparency. 

Clear agreements and responsible data handling builds trust with partners and customers and must be a priority when licensing data.

Leveraging AI and machine learning

Uncovering unanticipated insights

Data licensing opens doors to unexpected discoveries. 

AI and machine learning algorithms excel at finding patterns and correlations that human analysts might overlook. For instance, a retail company analyzing foot traffic data might uncover a link between weather patterns and in-store sales. 

These unanticipated insights can inform strategic decisions and drive competitive advantage.

Automated analysis

AI and machine learning make data analysis faster and more accurate. 

Algorithms can process vast datasets, identify trends, and predict future outcomes. By licensing data and applying machine learning models, businesses can automate tasks such as customer segmentation, fraud detection, and demand forecasting.

Personalization at scale

Data licensing enables exceptionally personalized experiences for customers. 

Machine learning algorithms analyze individual preferences, purchase history, and online behavior. Armed with this information, companies can tailor marketing campaigns, product recommendations, and pricing strategies. Personalization drives customer loyalty and boosts revenue.

Common barriers to data licensing

Businesses encounter a number of challenges when licensing data. 

This friction leads to licensing deals that could unlock enormous amounts of value for both sides not seeing the light of day. The fact that most traditional businesses are not as accustomed to buying and selling data as goods or services also creates similar inertia retarding the development of efficient data markets.

Some of the most common impediments and objections to more widespread licensing of data between businesses are:

1. Complex negotiations: Licensing terms, pricing, and usage rights can be daunting.

2. Data quality: Accuracy and relevance are crucial for informed decisions.

3. Integration: Seamlessly integrating licensed data into existing systems.

4. Cost: Licensing fees may seem prohibitive.

5. Complexity: Legal intricacies can be intimidating.

6. Risk: Fear of data misuse or breaches.

Conclusion: A step-by-step approach to data licensing

To counter the objections discussed above, an organized step-by-step approach to data licensing should be considered:

1. Needs assessment: Identify data gaps and strategic goals.

2. Vendor evaluation: Choose reliable data providers.

3. Negotiation: Collaborate on terms, pricing, and exclusivity.

4. Integration: Seamlessly integrate licensed data.

5. Monitoring and optimization: Continuously assess data quality.

For a more detailed understanding of how to implement this step-by-step approach, see the Data Licensing Cheat Sheet where I discuss this in greater detail.

Also see Key Terms of a Data License Agreement for help in understanding and negotiating data license agreements.