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What is data trust?

Through years of dedicated work we’ve come to learn that data trust is the sum of data transparency, value delivery and consequence acceptance. A brand must therefore say exactly what it will do, do exactly what it said, and both accept and clearly communicate the positive and negative consequences of their actions.

…data trust is the sum of data transparency, value delivery and consequence acceptance

In simple terms Data Trust is the trust a person places in an organisation’s data practices. Data trust has been earned when people have a high propensity to willingly share their data. As we now know, this is not the case today.

 

What is Data Trust, by Design?

Data Trust by Design is the practice of designing transparent, positive-sum, value-generating experiences that give people the ability to make free and easy choices about how their data is and isn’t used.

 

DTbD Principles

Data trust design principles give organisations a foundation to design processes, workflows and experiences that are inherently trustworthy. These principles align to the stages of a person:organisation relationship. They have a beginning, a middle and an end. They provide a simple frame of reference for how to treat people and their data at each stage of the relationship.

There are 6 principles guiding this practice.

Principle 1

First contact: Define shared objectives

People and organisations have stuff to achieve — stuff they’re motivated by. For a person:organisation relationship to really work, objectives need to be clearly stated by both parties upfront. If common ground is reached, proceed. If common ground can’t be reached, maybe it’s not meant to be. In either case the upside is that you may have just won yourself a brand advocate. Remember, people value transparency.

In practical terms, this means truly practicing data minimisation. Simply communicate your objective whilst finding ways for your potential customer to do the same. At this point in time there is no need for identity or any unnecessary attributes to be exchanged. KISS and decide whether it’s worth proceeding with further data processing quickly.


Principle 2

Before every interaction: Make the purpose clear

To make use of people’s data to fulfil a value proposition, your purpose has to be explicit. It has to be understood. People need to be informed, and only once they’ve made a choice in your favour do you proceed.

In practical terms this means catering to the context. If the interaction is simple and transactional, give people the most important information first. But give them the ability to drill down deeper if they feel it’s necessary. If specific requirements have to be met, ensure these are communicated explicitly. People need to understand the context if they are to assess it.

If you can explain your purpose in a sentence, picture or simple interaction, do it. If it requires more granularity and support, you’ve got to be willing to go the extra mile. Remember, people need to be informed and empowered so they can make a choice.


Principle 3

Establish a baseline: You are equals

The most successful relationships are built on a foundation of mutual respect and trust. Mutual respect starts with attitude, behaviour follows.

In practical terms, clearly state the control and access rights the person you’re building a relationship with has and relate it to your data processing purpose. Just like you, people need ways to make use of their data, withdraw your right to use that data and take their data to other relationships.

If you can do it, so can they. In this new world, people and organisations exchange value as equals.


Principle 4

Take your time: Trust has to be earned

Trust compounds over time. It’s the sum of radical transparency, consistent value delivery and a willingness to accept consequence.

Data trust relies on a show, don’t tell model. Give people the opportunity to try before they buy. Give them simple, light touch ways to engage with your brand. Show them that you do what you say, and you’re willing to own the consequence of your actions.  

Design for the long game. Quarterly reporting isn’t the metric that matters. Sustained customer value creation is.


Principle 5

Mutual success: Share in the value you co-create

They call it value exchange for a reason. By focusing on the value you create, rather than the value you take, it’s very likely you’ll begin delivering superior outcomes to the people you serve. If you do this consistently people will trust you to deliver.

Practically this means evolving your design practice and business metrics. It means focusing on the value, meaning and engagement you create for the people you serve, not just the metrics of old like CAC to LTV ratio.

When utilising people’s data to create value for them, make sure they understand how their data is being used to create that value. Magic tricks are great but feeling like the magician is much more rewarding.


Principle 6

Say goodbye: Make endings matter

Even the best relationships must end. The trusting relationships you have with the people you serve are no exemption. When the time is right, regardless of who activates the ending, make it simple and easy for both parties to get out on the best of terms.

Practically this means giving people options. It means giving them ways to get all of their data, and helping them use that in whatever comes next for them. Think beyond people’s right to portability. Endings are contextual to each relationship. Some people might want assistance enforcing their right to be forgotten. If so, make this happen seamlessly. Give them visibility of tangible progress and show them clearly you’ve done exactly what they’ve asked you to do.

 

There's plenty more where this came from, so if you're interested in applying these principles and getting hands on with some new design patterns...

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