Product Designer | Jul 2024 – Oct 2024
AI Tutor
Job-specific English Learning Product
Role
Product Designer
Timeline
Jul 2024 – Oct 2024
Team
Design, ML Engineering, PM, Content
Skills
Overview
How might we create a standalone AI learning product for job-specific English?
Building on the success of AI Discussion, we set out to create a comprehensive AI-powered English learning product focused on job-specific communication scenarios, targeting B2B customers and cost-sensitive users.
Problem
Users needed structured, job-relevant English learning
While AI Discussion was popular, users wanted more structured learning paths relevant to their professional contexts. Additionally, Ringle needed to expand its addressable market to include B2B customers and price-sensitive segments.
Solution
Curriculum-based learning with AI role-playing
I designed AI Tutor with a structured learning journey: Expression Learning → AI Role-playing → Discussion Practice. The product features job-specific courses covering scenarios from business presentations to coffee chat conversations.
Outcome
Strong launch metrics and user engagement
AI Tutor exceeded launch expectations, acquiring over 21,600 new users and generating 108,300+ learning sessions. The average user learns 2.7 times per week, showing strong engagement with the structured format.
21,600+
New users acquired
108,300+
Learning sessions
2.7x/week
Average learning frequency
+48.7%
Monthly new paying user growth
Reflection
What I learned
Structure enhances AI learning experiences
While free-form AI conversations are useful, structured curricula help users make consistent progress and feel a sense of achievement.
Job relevance drives engagement
Content that directly applies to users' work contexts significantly increases motivation and retention.