Data Compensation User Research

UX RESEARCH - User Research - Team Project

The Goal

A client approached the University of Michigan School of Information with a project proposing to understand how individuals felt about being compensated for the data they produced for the company. In addition, the client was also interested in knowing specific features and content that consumers would need in order to feel comfortable using such a system or product. As a group of three UX researchers, our team set out to design and conduct a two part UX research study. The first stage of research was a survey that would give us a broad, quantitative understanding of individuals’ feelings about data compensation and ownership. The second stage was a card sorting activity, informed by our survey results, so we could narrow down how consumers felt about specific pieces of data and receive qualitative feedback with preliminary and follow up questions.

The Process

Secondary Research - Our primary research was preceded by a comprehensive overview of current practices in the data collection market, the influential laws and regulations, and a competitive analysis of the major players in the area of data ownership. This research was provided at the request of the client for their own insights. This groundwork also gave our team a solid understanding of the field and the information was used to guide the design of our survey.

Survey - The first phase of our primary research was to conduct and analyze a survey. The survey was administered with Qualtrics and was approximately 30 questions and taken by 108 participants. The primary focus of the survey was to understand peoples comfort levels and general perceptions of data collection, digital privacy, and data compensation. The survey also aimed to understand what individuals thought of as personal data. The data analysis of the survey was used both for our main findings included in our report to the client and to inform the questions and design of our card sorting activity.

Card Sorting - Our group had originally planned to design an interview with card sorting session that was informed by the results of our survey. Due to the Covid-19 crisis, we had to transition our research to fully remote, and as a result pivoted our second stage of research to an asynchronous, fixed card sorting activity to accommodate time and scheduling conflicts. The card sorting activity was completed by nine participants.

In two rounds of sorting, participants placed data examples from a defined list into the category high, medium, or low sensitivity. These examples were taken from answers that survey participants had identified as “personal information.” Each round was then followed by a set of short response questions to understand the participant’s reasoning for the hierarchy they created and their thoughts on the scenario the session asked them to think about. The follow up questions also delved into issues of how companies that collected user data could establish trust with users and what features from these companies would make them more comfortable to use their products.

The Result

Our team presented three main findings to the client via a written research report and recorded video presentation. These findings were: 1.) People are split on sharing data for compensation, yet everyone desires transparency and control over their data; 2.) The data people feel protective of is unaffected by the circumstances or methods that organizations use to access that information; 3.) Individuals have expectations for how their data is going to be used, but they do not know for sure who is using their data and why.

We also presented the clients with recommendations for features that would need to be included in a data compensation system. These included creating transparency for how data will be used and allowing for users to pick and choose exactly what data they share for compensation in return. We also suggested that content be educational and informational about data privacy and security in general, giving people a sense of control over their data beyond the clients family of products.