Assistant Professor of Mechanical Engineering, Stanford University
Easier programming and data synchronization
Create more publications in shorter time
Implement advanced study design
Increased student engagement and class participation
Increased validity and reliability of study data
Dr. MacDonald’s research investigates what consumers want out of products, which features and aspects are relevant in decision-making processes, and how product choice is driven by individual preferences. While traditional consumer behavior is often accomplished using self-reports and questionnaires, Dr. MacDonald desired to enrich verbal reports with more quantitative measures of consumer behavior. Due to its non-intrusiveness and predictive power for attention processing, eye tracking was determined as the most suitable methodology.
However, the lab lacked the technical expertise required to set up and calibrate the eye tracking device. To fully test consumer choices on the features of a set of products, a complex study design was needed, including multiple conditions and randomization to counteract sequential effects. In addition, all types of measurement required manual synchronization to ensure participants were properly matched with their corresponding observations. This process was very demanding and resource-intensive, given the sheer amount of data points generated by the experiment.
Dr. MacDonald and her team have recently published seven cutting-edge studies powered by iMotions. “If I compare to other software that we have been using before, then we always designed a study that would fit to the software. Now we just design our study and we know that iMotions can handle it. I can do things so much faster with iMotions and they even understand the budget of an assistant professor,” says Dr. Erin MacDonald, Assistant Professor of Mechanical Engineering at Stanford University.
In the near future, Dr. MacDonald plans to conduct even more sophisticated and groundbreaking research that will push the boundaries of what has been possible thus far in engineering. Additionally, she plans to increase student engagement and offer research courses with iMotions as the core tool.
With iMotions, all of the aforementioned issues could be solved, allowing Dr. MacDonald and team to collect fully synchronized data using eye tracking and survey-based self-reports within a single software platform. In addition to the initial static images, iMotions allowed the research team to collect data on consumers’ behavior such as click-through rates while browsing shopping websites, which provided additional insights into product choice and preferences. The presentation of products was completely randomized, which increased the rigor of the experimental design, as well as data quality. Using iMotions technology, everything could be linked, enabling Dr. MacDonald and her team to conduct their research more efficiently and to publish results faster.
“If I compare to other software that we have been using before, then we always designed a study that would fit to the software. Now we just design our study and we know that iMotions can handle it. I can do things so much faster with iMotions and they even understand the budget of an assistant professor.”