In-the-moment Customer Sentiment and Satisfaction
Amazon Alexa
User Experience Design Internship
Overview
Created a long-term vision for collecting in-the-moment customer sentiment and satisfaction
My Role
UX Designer Intern
Timeline
May - August 2023
Team
Alexa Proactive Experiences (APEX): design manager, designer, researcher, product manager
Skills / Tools
Figma, Principle, Product Thinking, Multimodal Design, Voice Interaction Design, Conversation Design, Visual Design
⟡ Overview
I was a UX Design intern on the Alexa Proactive Experiences (APEX) team. As a horizontal team, APEX integrates content from domain partners (i.e. News, Music, Recipes, etc.) to create personalized moments of engagement via notifications, suggestions, content optimization, and feedback across voice and graphical user interfaces.
Over the span of 12 weeks, I created a multimodal CX framework for collecting in-the-moment customer sentiment and satisfaction and presented my proposal to a cross-functional group of stakeholders, and achieved alignment.
Prototype of card CX pattern with time of day question on Echo Show device
⟡ Problem
Beyond 'Alexa shut up'
Currently, all reportable customer sentiment only captures negative sentiment. Positive sentiment is extracted from implicit signals like engagement.
In 2022, the APEX team conducted experiments collecting explicit customer feedback for select ambient home content and device notifications. The introduction of the touch-only Like and Dislike signals via thumbs up and thumbs down actions resulted in a significant increase in engagement → this suggests that customers are willing to provide explicit feedback.
How can we expand the methods and formats APEX uses to gather a wider variety of in-the-moment customer sentiment and satisfaction? How can we improve personalization, relevance, and timeliness for customers at the time a customer interacts with Alexa?
⟡ Solution
Under the mentorship of the APEX team, I delivered a comprehensive Sentiment framework that:
- increased opportunities to solicit customer engagement
- produced scalable, quantitative metrics related to customer satisfaction
- provided actionable insights to improve personalization, relevance, and timeliness
All of which can be shared and referenced by domain partners to optimize content delivery and improve customer satisfaction.
The Sentiment framework establishes a collection of scalable design patterns and questions that encourage active engagement, supports both voice and touch interaction, and expands upon existing Alexa design capabilities.
Conversation design
Sentiment dashboard
