Audio Transcript Analysis
Audio Transcript Analysis
An AI-powered tool that converts customer calls into chat-like transcripts, analyzes sentiment, summarizes conversations, and suggests relevant products—helping teams quickly turn voice data into clear, actionable insights.
ROLE
Product Designer
PROBLEM
Support and sales teams struggled to extract meaningful insights from long call recordings, making it time-consuming to understand customer needs, sentiment, and next actions.
SOLUTIONS
I designed an intuitive AI-driven experience that transforms call recordings into structured transcripts with sentiment insights, summaries, and product recommendations—enabling faster decisions and more personalized customer interactions.
GOALS AND CHALLENGES
Goals
Design an experience that transforms voice recordings into interactive chat transcripts.
Integrate AI-based sentiment analysis for emotional and tone detection.
Enable automatic product suggestions based on customer intent.
Provide quick summaries for faster ticket resolutions.
Challenges
Visualizing audio-to-text transformation in a simple, readable format.
Designing a conversation-first layout that feels natural and contextual.
Ensuring AI-generated summaries remain accurate and concise.
Maintaining clarity while showing multiple data layers (sentiment, chat, summary).
PROCESS
RESULTS
40% increase in active weekly users within 3 months
Reduction in average task time by 35% for key workflows
Consistent 4.7/5 user satisfaction score in post-launch feedback
Internal teams reported fewer support requests and improved onboarding for new hires
ROLE
Product Designer
PROBLEM
Support and sales teams struggled to extract meaningful insights from long call recordings, making it time-consuming to understand customer needs, sentiment, and next actions.
SOLUTIONS
I designed an intuitive AI-driven experience that transforms call recordings into structured transcripts with sentiment insights, summaries, and product recommendations—enabling faster decisions and more personalized customer interactions.
GOALS AND CHALLENGES
Goals
Design an experience that transforms voice recordings into interactive chat transcripts.
Integrate AI-based sentiment analysis for emotional and tone detection.
Enable automatic product suggestions based on customer intent.
Provide quick summaries for faster ticket resolutions.
Challenges
Visualizing audio-to-text transformation in a simple, readable format.
Designing a conversation-first layout that feels natural and contextual.
Ensuring AI-generated summaries remain accurate and concise.
Maintaining clarity while showing multiple data layers (sentiment, chat, summary).
PROCESS
RESULTS
40% increase in active weekly users within 3 months
Reduction in average task time by 35% for key workflows
Consistent 4.7/5 user satisfaction score in post-launch feedback
Internal teams reported fewer support requests and improved onboarding for new hires
