Alexa in-the-moment customer sentiment design mockup

In-the-moment Customer Sentiment

Amazon Alexa

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.

APEX integrates content from domain partners to create personalized moments of engagement across multiple channels in Alexa. Proactive experiences can occur for devices with a screen (headed devices, i.e. Echo Show) as well as voice-only devices (headless devices, i.e. Echo Dot).

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'

Amazon context

Design Challenge

How might we create a scalable, multimodal feedback system to capture explicit customer sentiment?

⟡ Solution

I designed a sentiment framework with 2 in-the-moment feedback patterns, VUI design, a metric-driven question bank, and an internal sentiment dashboard, scaling actionable feedback collection across all Alexa experiences.

Toast CX framework Toast CX framework Card CX framework

Conversation Design

Conversation design example

Sentiment Dashboard

Sentiment dashboard

⟡ Designing for Scale

Alexa aims to be voice-forward, yet multimodal. As my first experience designing for non-mobile experiences, I learned a lot from my team in order to create a scalable and captivating multimodal design vision.

To center and ground my internship, I created 3 tenets to guide my decision-making process:

1.
Be fast and concise

Prioritize experiences that minimize the time to submit feedback. Avoid double-barreled, multi-select answers, and wordy copy. Interactions should be single-tap and answer options should be easy to understand, visible, and equally accessible.

2.
Be engaging

Customers are engaged with response experiences for a limited amount of time. UI displayed should be captivating and entice the customer to interact.

3.
Customers should feel heard

Customers are directly providing input to Alexa, which creates a sense of control. To maintain customer trust, information collected should be actionable and feed into efforts to improve personalization, relevance, and timeliness.

⟡ Actionable Insights

Before creating the design patterns, I first worked with the APEX researcher to establish the main customer sentiment themes identified from past user research.

Customer sentiment themes: relevance, personalization, and timeliness

I decided to use CSAT, as it was the most relevant industry-standard sentiment/satisfaction metric for this project, and descriptive statistics for questions that mapped to themes of relevance, personalization, and timeliness.

7 measurements were defined for this proposal

After defining the measurements, a question bank with about 10 questions per theme was created. Each question was associated with an actionable measurement.

The question bank mapped each question with its relevant opportunity to solicit customer sentiment, the measurable outcome, and appropriate CX pattern

⟡ Future Opportunities

Scaling Across Domain Partners

To expand this framework across APEX domain partners (News, Music, Recipes, etc.), implementation complexity varies by question type.

  • Easier to implement: Standardized formats like rating scales, time-of-day questions, and CSAT scores require minimal customization.
  • Requires partnership: Domain-specific multiple choice and either/or questions need collaboration with domain teams, Research, and VUI designers to ensure questions are unbiased and optimized for voice.

AI-powered Enhancements

Large language models could enable:

  • Dynamic question generation tailored to each interaction
  • Natural language feedback from customers
  • Automated voice analysis for faster insights
  • Real-time learning to prevent hallucinations and improve personalization

⟡ Results

Positive feedback from stakeholders
Additional stakeholder feedback

⟡ Reflection

What I Learned

  • Designing multimodal experiences — I had only designed for mobile and web prior to this internship, and learned how to design new voice UI and GUI interactions for a voice-first technology.
  • Advocating for myself — I learned how to take initiative in meeting new people, being transparent on the scope of my project, and asking for specific feedback on my work. I also learned how to balance design needs with business needs, customer insights, and technical considerations.
  • Stay committed, not attached — Having a flexible mindset and iterating on feedback were essential to my growth over the summer.
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