INTRO
Before this class I had a very limited understanding of behavior design. I was always curious which features of applications I use are intentionally designed to subconsciously capture my attention, and why it worked so well. Getting into the content proved a very rewarding experience. In order to understand the design features themselves, you have to start at the root of behavior – human psychology.
LECTURES
Some of my favorite moments of this class were the lectures exploring these behaviors. I felt the most enriching content came from the Behavioral Psychology Intensive lectures. In these classes we learned about BJ Fogg’s work on changing habits, his B=MAT model, and Switch by Chip and Dan Heath who conceptualized the elephant riding metaphor. Exploring examples of these models in the real world, as well as discussing them in the form of discussion posts, reinforced these concepts.
PROBLEM
My group applied these concepts in our final app implementation, which focused on how to motivate novice workouters to improve frequency. This problem was ripe with behavioral complexities and, for Stanford students, filled with shallow excuses that so often plague us from actually making things happen (e.g. time, coursload, etc).
PROJECT
Using BJ Foggs model, we had to increase motivation, offer easy workouts, and trigger users to keep going. We first leveraged social belonging behavior by teaming up users. We then increased users’ ability to do workouts by offering simple and easy workout options in an explore feature. We made this feature engaging by architecting a card swiping mechanism like tinder. Lastly, we did not focus on any specific nudge or trigger, but implemented a team leaderboard to encourage users to compete within their team. This leaderboard, granted that teammates are contributing to challenges, creates a perceived norm that other teamates/users workout more often. As from class, when a perceived norm is greater than actuality, the bahvior will increase. Thus, the leaderboard should increase the likelihood a user will workout more frequently.
Applying this to the elephant rider metaphor, we increase clarity for the rider (rational self) by making actionable goals/challenges to strive towards. We supported the elephant (emotional self) via the team leaderbaord, providing motivation when users might be struggling. Lastly, we changed the path (environment) by making all challenges team based – helping everyone achieve their goals by doing it together.
DOWNSIDES
There were some notable downsides explored through our design fiction. Our fear was that novice users would take competitions too far. If compared to other users with more ability, a user could end up feeling worse about themselves and giving up. On the flip side, a user might end up going beyond their ability to keep up, putting themselves at risk for injury. Both scenarios are very tangible outcomes. If we had more time, I would prioritize mitigating these outcomes by designing safety thresholds into the app. I envision employing user feedback during onboarding and post workout logging to nudge users going too fast too quickly. Additionally, there is work to be done in matching users to teams of similar ability levels.
CONCLUSION
Overall, this course has opened my eyes to effective behavior design techniques. Going forward I will approach problems in this domain with similar diary study frameworks and ethical considerations prior to the design/implementation phase. I feel confident approaching these problems with an understanding of human behavior principles!
