11th Dec 2018
How might we...
...layer information visually, clearly and concisely?
- English
- Deutsch
Building powerful narratives around value exchange
The way apps engage with people about data use can be quite cold and formal. What if it was more natural, more familiar, more relevant and human?
Product Context
Fanfare is a fictional music app that connects people to the best live concerts and music based on their location and taste. Location data is used to initially find concerts nearby and then make ongoing suggestions. Third party data is used to tailor suggestions to people's tastes. The more Fanfare knows, the better the recommendations.
In order to provide the service, Fanfare is powered by some of the following data:
- Location data, which connects people to relevant content
- Facebook profile, for account verification purposes, and so the person's friends list can be used to recommend music events that their friends like
- 3rd party music streaming services (e.g. iTunes and Spotify), whose data is used to tailor suggestions to the person's tastes
- An API is made available to 3rd parties so they can offer discount services based on music tastes and consumption. This API requires people to give explicit permission to 3rd parties
Problem & Opportunity
People are being asked to provide a tremendous amount of data during sign up before they have an overall sense of the trustworthiness and usefulness of the service. This is especially challenging when services ask for multiple data sources, including 3rd party data, at the outset.
The cross-functional Design Jam team challenged themselves to consider how Fanfare could make asking for location information, and connecting to 3rd party data sources, feel necessary in order to provide exceptional value, and therefore make people feel that the data exchange was worthwhile.
Fanfare team working on their challenge statement
Design Features
Visualising value exchange
Through an enjoyable, step-by-step on-boarding process, Fanfare shows people how their personal data can help the app provide better recommendations. The conversational search string, alongside the clear visual cues of ever-decreasing dots on a map, helps people see the value exchange of their data, and more personalised results.
- Location data narrows down the search to your geographical location
- Connecting to a 3rd party music service personalises the search by music taste
- Connecting through Facebook identity helps to connect friends with similar tastes and locations
- A personalised set of suggestions are displayed as a result of the exchange of data
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 like most. It's a powerful way to cultivate and foster trust.
Design Features
Giving people choice over sharing location
'Granular control' was a recurring theme amongst several Design Jam teams. Similarly to Oink, Fanfare came up with a solution allowing people greater control over their data, while clearly conveying the value exchange for doing so.
At its highest level, Fanfare could be used without sharing location, even though the service is challenging to provide without it. It's clear to see how adding location would greatly enhance the personalisation of the service but Fanfare gives a choice:
- 'Yes, all the time,'
- 'Yes, only when I'm in the app,' or
- 'No, continue without.'
These choices give people granular control and do not presume consent to gather location to be continuous. If the person is happy with the service over time, they may just select 'Yes, all the time,' in the future once trust is established.
Next steps
How might we build on Fanfare's ideas to...
- Make data exchange feel more conversational and human?
- Make the connection to 3rd party data sources feel great for people?
- Give people more granular control over the personal data they consent to sharing?
