Nike Run
Club Chatbot
Role
UX Research
Conversation
Design
Tools
Miro
Figma
Botpress
Time
Apr-May 2024
(2 Months)
Clients
Class Project-
Tony Lee
Overview
Nike Run Club's fragmented experience causes users to leave the app. How might we keep runners engaged by integrating personalized, data-driven support within the app?
I designed a conversational AI chatbot, embedded directly in the app, that leverages users' data to deliver personalized, actionable insights. This solution enhances the user experience by keeping runners engaged, focused, and supported throughout their journey.
The journey map shows NRC excels during guided runs, offering valuable, real-time support. However, users feel abandoned post-run, lacking follow-up guidance or engagement. This insight highlighted key opportunities for the chatbot to provide ongoing support beyond each run.
Core User Needs
01.
Training plans and notifications should adjust to users’ progress, preferences, and external factors, keeping runners motivated and aligned with their goals.
02.
Runners seek clear, accessible performance data and motivational insights, enabling them to monitor their progress and improve consistently.
03.
Users want easy access to in-app guidance and advice, eliminating the need to rely on external resources for tailored running support.
Through A/B testing via a Google form, I gathered data on notification preferences. Results showed a strong preference for personalized notifications, with 85% of users favoring them. Additionally, users highlighted the importance of tailoring notifications to their running habits and personal data, driving more effective engagement.
Develop
I used BotPress to develop an initial prototype of the chatbot, aiming to integrate personalized, data-driven support within NRC. However, user feedback revealed that the chatbot's slow response times impacted engagement. To resolve this, I optimized the conversation flow, adding more knowledge bases and user intents. Additionally, I integrated ChatGPT and live Nike website data as fallback options, ensuring quicker and more accurate responses when pre-programmed answers were unavailable.
Final Prototype
Impact & Takeaways
“Excellent work! Great to see you applying strong conversational design principles to enhance the user experience.”- Tony Lee, Professor
“I wish the app had this feature I wouldn’t have had to rely on TikTok for training tips!”-Cayleigh Kissinger, User
This project provided a unique opportunity to refine my skills in designing a data-driven solution within an existing app, from initial research to prototype. Through testing, feedback, and iterative design, I learned how to better understand and address user pain points, especially how personalized notifications and real-time support can improve engagement. Using tools like BotPress and Figma, I developed a prototype that integrated seamlessly with the existing app, providing a more interactive and supportive experience for runners.
Looking back, I recognize the importance of balancing creativity with practicality. While the prototype showed strong potential, I realized the need for continuous performance improvements—like addressing the slow response times in the initial BotPress prototype. If I had more time, I would further refine the integration of real-time data to reduce any delays in delivering personalized content. Additionally, the A/B testing phase taught me the value of direct user input in shaping features. I would have incorporated more structured testing earlier in the process to catch any potential issues sooner. Ultimately, this project reinforced the value of adapting design based on user needs and feedback, while maintaining flexibility to iterate as new insights emerge.