❤️ Jesús picks: This project stands out as one of my favourites, driven by the unique off-site dynamics, ethnographic nature and the opportunity to collaborate with diverse teams and businesses. UX research was at the heart of every decision, shaping the path forward and making a lasting impact for ATB.

Background
During my tenure at ATB I have been leading the user research programs and up to 4 researchers for several vital projects part of ATB’s transformational journey and its commitment to serving Alberta’s rapidly growing tech ecosystem across new mediums.

ATB was the first bank in Canada to introduce Pepper to its customers. Pepper is a 4ft tall robot that speaks, moves and interacts with people. Pepper was designed to be a ‘companion’ robot, and is capable of interpreting a smile, a frown, or tone of voice. She also notices and responds to non-verbal cues, such as the angle of your head, for example.

Challenge
I conducted a research study to help answer questions the innovation team had about how a robot could be used at ATB Financial and learn how the customers react to robots associated with the brand in different locations for different personas. The robot was taken to several locations to run experiments and answer the following questions: 

How appealing is the robot to customers?
How does the robot impact consumer engagement and brand perception?
How do customers respond to the robot?
How do customers perceive and interact with Pepper?
How willing are users to trust a robot for banking advice?
When do users prefer to interact with a human instead of a robot?
What factors would discourage people from interacting with the robot?

Results and Outcomes

During this project, I led several phases of research into this emerging technology. We began by observing customers at ATB branches, assessing their interactions with default software and early customizations. Next, we studied the robot in various locations to evaluate brand perception and its role as an ATB representative at off-site locations.

Our findings revealed the types of interactions customers were willing to have with a robot, identified the most effective use cases for the brand, and pinpointed locations where this technology could address specific needs.

Balancing observational methods with traditional attitudinal research was essential in uncovering user needs that weren’t always directly articulated.