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Data Trust: Unlock the Power of Reliable Information for Business Success

A data trust can protect consumer data and ensure it’s used in a responsible manner. Explore the benefits and outlook here.

All businesses rely on data to sell products and services. Using customer data comes with many complications, like privacy concerns and regulations for how that data is used.

Businesses that utilize customer data can create more personalized and effective marketing campaigns. For instance, you may leverage psychographic data to send targeted emails. Unfortunately, consumers may hesitate to share their information with you due to misuse and other issues. A data trust might be an effective solution for helping businesses access customer data and give consumers peace of mind.

Data trusts are similar to other types of trusts, like a living trust, ensuring the data is accurate and used responsibly. According to HBR, data trusts will become increasingly important as AI popularity grows.

How do data trusts work?

Data trusts work similarly to other types of trusts in which a third party maintains and manages consumer data. With a data trust, an independent organization governs the proper use of data. Therefore, these third-party entities handle consumer data instead of platforms like Facebook or business websites.

A data trust protects customer data and makes it easier for companies to share information.

AI writing tools like ChatGPT collect data, which helps artificial intelligence technology learn and understand the world more. Without data, these systems would have nothing to learn from and wouldn't exist. AI requires large sets of information, which can be challenging to obtain.

Businesses also rely on data. For instance, they use AI predictions for forecasting based on previous sales information, website data to learn about their marketing campaigns, and personal customer data to send email campaigns.

Data trusts would enable businesses to obtain more data at consumers' discretion. With a data trust, consumers sign contracts, giving third parties access to their information, which can be used for anything as long as it's agreed to. Therefore, this data can be used to improve AI in marketing or help AI systems on various tasks with fewer compliance issues and risks.

Simply put, the benefits of data trusts allow companies to share data more easily. Unfortunately, sharing company data, specifically customer data, has strict regulatory oversight. You can't share customer data with other companies without their consent, so it's challenging for businesses to transmit data that can improve overall operations.

A data trust aims to combat these issues by having a third-party oversee and manage the information collected, determining whether a consumer's data can be used for a particular purpose.

When consumers enter a data trust agreement, they determine how their data can be used. This is the opposite of how things work now. For instance, when you use social media, platforms inform you of how your data is used, requiring your consent. With a data trust, consumers decide how their information is used.

It's important to note that data trust benefits go beyond marketing and training AI language models. In fact, it can play a significant role in research and development. For example, doctors can use patient data from a data trust to support their research.

Does a data trust really protect privacy?

The benefits of data trust solutions aren't just for businesses; they can further protect consumer privacy by allowing a third party to make important decisions about how your data is used on your behalf. For instance, you can agree on the specific ways your data can or can't be used.

Data trusts set standards for data protection, forcing businesses to use data appropriately and securely. Since they address topics like which data is shared, how it's shared, and who has access to it, consumer privacy is more protected under a data trust model. As trustees, consumers can decide who can use their information, making it potentially more effective than current government regulations.

Advantages and limitations of data trusts

Data trusts can be effective for training AI models and sharing data across businesses and industries. However, this relatively new concept is currently just a theory. Like any other method of protecting consumer privacy, the data trust model has benefits and drawbacks.

Advantages of using a data trust

Data trusts make information more accessible, improving data collaboration that can drive innovation. Consider how AI has drastically changed the business landscape. Businesses use AI daily to guide their decision-making and improve internal and external processes. Meanwhile, we wouldn't have AI without data because machine learning and artificial intelligence require massive amounts of information to learn.

Limitations of using a data trust

While data trusts aim to make data more accessible while enhancing privacy protections for consumers, it's not an entirely realistic model. According to the MIT Technology Review, companies may be reluctant to establish data trusts, and government intervention in the form of laws leaves data in someone else's hands rather than unbiased third parties.

Consumers are at the mercy of private companies and platforms that collect their data. As things stand today, when you sign up for a social media platform, you agree to let them collect various data about you. If you don't agree, you often can't use the platform.

To form a data trust, you must be willing to make sacrifices. If a company joins a data trust and agrees to its terms, then fails to comply, it will no longer have access to your information. This means you may be forced off the platform.

Data trust alternatives

While data trusts may not be totally realistic because it'll be challenging to get companies to agree to them, there are several alternatives that may be more feasible for consumers.

Data cooperatives and unions allow individuals to choose what data is made available and to which companies. For instance, you can share your data with governments, medical researchers, and so forth. Those organizations would then use a trust to protect consumer data. According to MIT Technology Review, data trusts, unions, and cooperatives all tackle the same issue differently.

A data union is an organization in which individuals get rewards for participating in data sharing. Users join a union, consenting to let organizations use their data for various purposes. Under this model, people are incentivized to share their data, allowing them to earn money in exchange for their consent.

On the other hand, a data cooperative allows individuals to pool their data voluntarily. Cooperatives are owned and operated by members, giving them full control over important decisions, such as how data is used.

The future of data trusts

Data trusts are a thought-provoking theory. Unfortunately, business leaders may be less willing to use them since they already use their own technology solutions to collect customer and user data.

On the other hand, data trusts can improve data quality by providing AI technologies with better data resources through efficient collaboration.

Since data is so important to businesses, you shouldn't be surprised to see data trusts and other sharing models in the future. Consumers are becoming increasingly aware of how their data is used and want to protect their privacy. Yet, they also know the importance of data for providing them with the best content.

For instance, when you watch Netflix or another streaming platform, it collects data about your preferences, providing you with tailored recommendations. While consumers want to guard their data, they know sharing it can provide them with better opportunities, but it's up to companies to encourage consumers to share that information. Therefore, one of the most likely scenarios is that data sharing will become monetized, rewarding consumers for sharing data and giving companies consent to use it in various ways.

Governments, private companies, and consumers may become more interested in data trusts as protection and privacy issues continue to loom.

Using data trusts for data governance

From AI content moderation to marketing, healthcare, and city data, consumers, companies, and governments must determine the best way to share data. Data trusts can boost data governance efforts, improving consumer trust in data sharing. Third-party intermediaries can increase data sharing while instilling confidence in consumers.

Unfortunately, trust law varies by country, with some not allowing general data trusts. Again, this concept is relatively new, so we'll have to wait to see it in practice before determining its efficacy.

Until then, protect your customer's data with Mailchimp. Using our suite of marketing tools, you can comply with data protection laws by getting consent to send customers marketing communications and creating a privacy policy to describe how your business collects and uses personal data.

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