AI Search

AI Search is a feature for a traditional search, that enables users to find relevant courses and content by understanding their unique profile, goals and their objectives.

My Role

Product Designer

Tools

Figma, Miro, Lyssna, Looppanel

Scope and Approach

To better understand how users interact with the platform and identify opportunities for improvement, I conducted a multi-phase research process. The focus was on understanding how learners search for courses, clarify questions, seek assistance, and retrieve knowledge.

The project was structured into the following stages:

Recruitment

Recruited participants from our user base.

Research

Conducted 1:1 interviews, usability testing, and surveys to gather insights.

Analysis

Synthesized research findings to identify pain points and opportunities.

Design

Iterated on the existing design based on research insights.

Continuous Feedback

Regular syncs with teams to gather feedback and evolve.

Challenges

Accessibility

Designing an inclusive solution that catered to users with diverse needs, including those with disabilities.

Technical Constraints

Integrating AI capabilities within the existing platform infrastructure without disrupting the user experience.

Methodology

•
Surveys: Collect quantitative data to understand user preferences and behaviors.
•
1:1 Interviews: Gather qualitative insights into user motivations, challenges, and expectations.
•
Usability Testing: Evaluated prototypes to identify usability issues and validate design decisions.

UX Metrics

To measure the success of the solution, we established the following metrics:

90%

Usability

At least 90% of testers should complete usability testing sessions without major errors or issues.

90%

Satisfaction

At least 90% of testers should rate the solution as "Good" or "Very Good" in addressing their needs.

30%

Efficiency

Reduce the time taken to find relevant courses by 30% compared to the traditional search.

Results

•Delivered a functional MVP that met the established UX metrics.
•Users reported a 30% reduction in time spent searching for relevant courses.
•92% of testers rated the AI Search feature as "Good" or "Very Good" in addressing their needs.
•Early data showed a 15% increase in course enrollments after the feature was introduced.