Carlita L'Abbé - 40028020
David Semujanga - 40032841
Dang Lam Ha Lara Tran - 40058907
Personal data is constantly generated. From mouse clicks to heart rate, our lives alongside technology is extensively documented. This kind of information can be a valuable tool for development and many companies are willing to pay big money for it. The issue right now is that the companies gathering your data, such as Facebook and Google, are selling your data to third parties without your knowledge or consent. Unbelievable, I know.
This is quite concerning as our data can majorly influence companies in their decision making, from targeted advertisement to political campaigns.
The data industry is not ALL bad. In fact, your online data can help academic researchers learn more about humanity or help cities build more efficient public transit. Considering the data market is expected to reach $118 billion this year we think it is only reasonable for individuals like you and me to be able to make some profit off the data we are so generously generating.
The idea of a data marketplace is not new. There are currently a few applications and services that allow users to sell their data but there are flaws to them. Many don’t give users full transparency on how their data is being used once sold. The services that do give users access as to how their data is being used offer little to no compensation in exchange for the data.
The research allowed us to gain a deeper understanding of the problem. With this information, we were able to come up with questions and create a survey on Google Forms to get the population's views and opinions on how their data should be handled online.
The results of the survey were then put into charts for better visualization of the data gathered.
This last chart is the most telling of them all. Many people are unwilling to sell on a data marketplace. How do we design a personal data marketplace if most people are unwilling to sell their data?
Armed with the information provided by the research phase, we were then able to move on to the analysis phase of this design process. This phase will help us understand why the users would need to use a personal data marketplace.
Since we included a demographics section in our survey, we were able to make user personas of potential users of our app based on the survey responses. Each persona has background information, their motivations and goals in terms of using a personal data marketplace and their pain points in regards to the current situation of how their data is being used/sold.
Creating a user journey exploring the mindset of Jeffery getting acquainted with the concept of user data gives us the opportunity to understand the concerns and roadblocks of our potential users.
Storyboards are an effective way of communicating how users could interact with the app. This storyboard has Jeffery as the main character.
Doing a user flowchart allowed us to visualize how the user would be navigating through the application.
To start the core design of the app, we did sketches as it is a cheap and effective way to communicate to each other how we wanted the app to look like in terms of layout.
Using the sketches done earlier, we were then able to make wireframes so that we could have a digital representation of the application's main layout and functionality. As wireframes are relatively simple in terms of aesthetics, this could be done quickly while still providing a good foundation for the mockups.
We brainstormed different color palettes. We wanted to go with a mainly green theme as it is a color that inspires money and trustworthiness. We also wanted white as the base background color as it gives a minimal and clean look to the application.
Final Color Palette
We used the Metropolis font by Chris Simpson. It is a minimalistic font that we thought would suit our user interface well.
When signing up, as part of the onboarding process, users can choose which accounts they want to link to the app. These accounts will be the main source of data and can be configured later on if the user wants to restrict the sale of certain types of data associated with a particular account. Then, the user can choose which categories of buyers they want to sell their data to. These two steps allow the user to fully control how their data is being used.
This page gives the user a quick overview of their history with weekly statistics. In the section “See your impact”, the user gets the opportunity to see how their data participated in a bigger project like the development of a new app feature or in the findings of a scientific article.
In the initial conceptualization of the offers page/functionality, we had envisioned quick actions for the user to be able to accept or decline an offer directly from the dashboard without having to open a separate panel. However, this encourages the user to potentially consent to an offer while having read minimal information about what they are giving up. This goes against our business’ core objectives of offering complete transparency to the users.
Reviewing this, we changed the user interaction design for this component to automatically open a pop-up window with clearly stated details about the offer. From this pop-up, users can then choose to accept or decline the offer.
We have applied this to both the quick access /recent offers in the dashboards as well as the offers page.
Here, users link their various sources of data to their account and control what type of data they are willing to sell. A user may have varying levels of comfort selling different types of data that could be bundled together. For example a mobile phone has various information stored in them such as, a contact list, GPS data, app usage, etc.This page gives users more precise control over what data they agree to sell.
When buyers publish their offers on our website, their offers must be categorized in specific fields. Our users get to filter through these offers to only sell to fields of their interests.
Here, users can see their history of accepted offers.
This page allows the user to edit basic account information such as username, name, email and password. In addition, the user can put their credit information so that the money from the sale could be sent directly to them.
The hardest part of designing this application was probably understanding the problem itself. Understanding the underlying pain points behind the frustrations of users towards the data industry and effectively addressing these in our design required a lot of communication with our user base. Analysing our research, we were able to narrow down what was keeping the users skeptical about selling their data. Keeping in mind all we had learnt along the way, we designed a web application that is engaging, inspires trust and remains transparent with information.
