AI Trending Topics

Context & Problem

Before this feature, renters had to scroll through dozens or even hundreds of reviews to spot recurring issues or themes. This made it slow and difficult to get a clear sense of sentiment, often burying important insights in long review lists.

Solution (V1)

I designed a new feature powered by AI to make reviews easier to digest:

• AI analyzes review text to identify the most frequently mentioned topics.
• Users can click a topic to instantly filter reviews related to it.
• Keyword search allows refinement within a selected topic.
• A "Reset" option quickly returns to the full review list.

Mobile Version

Desktop Version

Iteration (V2 – In Progress)

• Training the AI to improve topic accuracy.
• Adding sentiment analysis to show whether trending topics are mostly positive or negative.
• Exploring ways to make insights more actionable with visual indicators.

My Role

Sole UX designer for the feature.

• Partnered with product manager to define goals and requirements.
• Collaborated with engineering to refine feasibility and interactions.
• Designed wireframes and prototypes, iterating based on stakeholder and user feedback.

Impact

• Transformed lengthy review lists into an at-a-glance, topic-driven experience.
• Faster decision-making: relevant reviews surface in seconds.
• Improved discoverability: hidden feedback now surfaces quickly.
• User control: blended AI suggestions with manual search for precision.

How We'll Measure Success

• Increased click-through rates (CTR) on trending topics.
• Reduction in average time to find relevant reviews.
• Higher engagement rate within the reviews section (more reviews read per session).
• Positive feedback in user surveys on ease of finding relevant information.