Skills Applied
User Interviewing, Affinity Mapping, Wireframing, User Testing, Journey Mapping, Prototyping (Lofi-to-Hifi)
Timeline
6 weeks (Feb 2024 - Mar 2024)
Team
Gerard Samson, Smridhi Gupta, Jiten Thakkar
In a collaboration hosted by Amazon Music, our team designed a new AI-powered explore page for podcast lovers to find their next obsession. Our team reimagines Amazon Alexa into generative AI assistant that powers the new bite-sized recommendation explore and recommendation feature. Our aim is to push the needle forward for the Amazon Music app.
The Design Brief: Given the current state of Amazon Music, how might AI enhance a customer’s experience with music and/or podcasts?
Research Findings
Through interviewing avid podcast listeners we found that 50% of users:
experienced trouble with tailored recommendations
preferred short-term content
rely a lot on others for their next podcast
“I'm always taking recommendations, but I always like vetting, especially for something that I wanna invest in time and effort and energy into listening”
— User Feedback
Issue 1
Users experienced trouble with tailored recommendations
Recommendation 1
A Gen-AI powered Alexa pulls data from wish lists, shopping habits, and read books to better inform your explore page algorithm.
Issue 2
Users prefer short-form and easily accessible content
Recommendation 2
Display bite-sized recommendations of video clips, quotes, posters, and merchandise using tiles
Users tend to rely on their social network for their next podcast
AI uses Natural Language Processing to recommend the best pieces to users' friends
Initial user testing shows promises
Initial user testing found small prototype errors and desire for more onboarding for the AI process. Overall, they were pleased with idea of short-form recommendations for their next podcast. More user testings need to be conducted, however, to further validate initial results and gain new findings.