Fogg Behavior Model and Reducing Perceived Effort
Learn how the Fogg Behavior Model from Stanford University can help design digital health applications that foster lasting positive behavior change by optimizing motivation, ability, and triggers.
The Fogg Behavior Model developed out of Stanford University’s Behavior Design Lab (BDL) by Dr. BJ Fogg (who is also the BDL founder)
- The Behavior Model website covers the Fogg Behavior Model in a very interactive sense.
According to Fogg, behaviour change occurs when all three components, Motivation (M), Ability (A), and Triggers (T) converge simultaneously. The absence of any of these components inhibits behaviour change. The model is instrumental in identifying barriers to desired behaviours.
The Three Core Components
Motivation
Motivation underlies the drive to change behaviour. It can be high or low, and its intensity influences the difficulty of tasks individuals are willing to undertake.
Ability
Ability, within this model, pertains to the ease of performing a task. Increased ease or simplicity can enhance an individual’s perceived ability.
Triggers
Triggers or prompts initiate action. They are vital in the presence of motivation and ability but insufficient in their absence. The model recognises three major types of triggers: Spark, Facilitator, and Signal.
Application in UX Design
By applying these concepts in UX design, behaviour change is achievable. With motivation, ability, and triggers or prompts occurring at the same moment, digital health apps can cultivate daily habits that foster lasting positive behaviour change.
Fogg’s model also discusses the idea of reducing perceived effort to increase retention. A simple method to apply this theory is by informing the user about the time they need to spend daily or weekly to achieve their goals. This clear communication can prevent users from overestimating the effort required and improve engagement.
Reducing Perceived Effort
- To put it bluntly, apps that ask you to do too much work in order to receive any value, will struggle to retain users. Reducing perceived effort should be considered for all aspects of an applications lifecycle while in use, or not.
- We have previously covered a simplified version of this model in the “User-work to perceived value ratio” article found here.
A core pillar of Sahha was built on foundations of this model, we believe passive health data is a way to unlock not only better health outcomes but can also significantly reduce barriers to entry for users of health and wellbeing application by reducing the burden of data entry.
Additional Resources
- Divya Ray (senior design at IBM) also brilliantly covers the model in a format for the more technical. In her article she shows our Fogg’s model for behaviour change is less complex than many assume; and how the model can be systematically approached.
Conclusion
The Fogg Behavior Model provides a comprehensive framework for understanding and facilitating behavior change. By strategically leveraging motivation, ability, and triggers, UX designers can create digital health apps that foster lasting positive change.
Furthermore, the model emphasizes the importance of reducing perceived effort to enhance user retention. By implementing these principles, we can build health and wellbeing applications that are not only impactful but also user-friendly and engaging.
The potential for the application of this model extends far beyond its current uses. As innovation in the space evolves, the Fogg Behavior Model will undoubtedly continue to shape approaches to behavior change and UX design for digital health apps.