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Visualising the value exchange between aggregated and personal data sets

Giving people ways to monitor their health in relation to the local environment while contextualising it in comparison with useful information about other places.
Product Context

Ayr is a health and environment app made for the active citizen. It provides people with local weather, air and smog information. Ayr connects to people's wearable tech to adapt its recommendations based on their health.

In order to provide the service, Ayr is powered by some of the following data:

  • Location data is used to provide people with local, relevant smog information. Ayr can be connected to people's home Internet of Things and health devices such as smartwatches, allowing the app to provide specific, detailed information about environmental quality.
  • In order to get custom data from Ayr, people can enter specific information regarding their health. Ayr's medical record is encrypted for people's security. Biometrics can be stored and used to encrypt data.
  • Third party data exchanges unlocks additional features like custom recommendations based on health data gathered by devices.
  • Aggregated data is shared with third parties to serve ads from relevant health businesses nearby, providing revenue to the company.
  • Ayr shares aggregated weather information to national weather services to help improve predictive weather datasets.

Problem & Opportunity

While health-related data is highly sensitive, people are usually asked to provide a tremendous amount of it when signing up, before they gain an overall sense of the trustworthiness and usefulness of the service. Such apps rely on aggregated datasets combined with personal data to offer valuable support to users. This is especially challenging when apps ask for multiple data sources, including third party data, at the outset in order to provide a meaningful, helpful service.

How might we...

...Demonstrate how aggregated datasets can benefit people on an individual level

Ayr team working on their final share-back presentation

Design Features
Step-by-step value exchange

Through a fact-based, step-by-step onboarding process, Ayr shows people how their personal data can help the app give better recommendations to keep them healthy. Ayr provides 'bite-sized' and meaningful data to give context:

  • Location data narrows down geographical location to provide accurate smog information
  • Connecting your wearable tech allows you to build up your health profile and provide daily advice
  • Providing information regarding your health allows for Ayr to personalise the user experience according to their objectives

The contextual nature of this consent flow makes sharing data feel natural, as people can see how what they give will help them get what they need most. It's a powerful way to cultivate and foster trust, all within a few minutes.

flow ayr sing
Design Features
Zooming in from global to individual perspectives

Ayr also demonstrates the value of aggregated datasets by walking people through general facts about the area to later end up on a personalised set of health suggestions, which are displayed as a result of the data exchange. The common, anonymised datasets serving people on an individual level is demonstrated in an intuitive way by narrowing down and cycling between global facts and what they mean to specific users.

zoomin ayr sing
Next steps

Environment and health-based services are very dependent on statistics and global numbers to provide meaningful and secure recommendations to people. For such services, it is key to strike a balance between reliable general guidance and personalised support. Additionally, people rarely have granular control over how their data can be used to carry out meaningful actions.

How might we build on Ayr ideas to...

  • Show people how the data they've shared has helped others