AI Story Time
A language learning app that helps young learners build language skills through animated stories and an AI reading tutor powered by speech recognition.
My Role
Design Owner
Team
1 x Visual Designer
2 x Software Engineers
Year & Scope
2009 - 2010
0→1 platform
My Contribution
Product Strategy
User Research
Product Design
Project Management
IMPACT
Designed a gamification system that turned passive story-watching into active practice, converting thousands of new subscribers.
PROBLEM
Users tried it, then left
When the product launched in late 2018, we piloted it with three school districts across 15 schools and 652 target users. The pilot did not meet expectations: after the free trial ended, only 6.9% of users converted to paid subscriptions, despite receiving a significant discount.
Similarly, the product struggled in the consumer market:
4.7% conversion
Among users who viewed the App Store listing
16% cancellations
Among users who subscribed to the app
17% deletion
Among users who installed the app
BEHAVIORAL ANALYSIS
Users dropped off across the core experience
To understand why users weren’t converting or staying, I first analyzed user behavior and found that only 10% of users remained active each month. To better interpret their behavior, I compared actual behavior against the intended user journey:
Login frequency
42%
(1.27 of 3 times)
Stories watched
24%
(1.2 of 5 stories)
Time spent
11%
(3.38 of 30 min)
Quiz
10%
(0.3 of 3 quizzes)
Points collected
9%
(240 of 2800 points)
Read aloud
5%
(0.14 of 3 read alouds)
*Metrics represent average weekly behavior per active user.
The comparison surfaced three clear gaps:
Low Engagement
Users returned infrequently and spent significantly less time in the product than expected.
Low Story Consumption
Users completed far fewer stories than our experience was designed to support.
Low Feature Adoption
Read Aloud was consistently the least-used of the product's three core learning activities.
USER RESEARCH
Three root causes behind the product's struggles
To understand the reasons behind the gaps, I conducted eight in-depth interviews with four teachers, two parents, and two students. I also reviewed App Store feedback and support tickets to broaden the sample.
Across research sources, three root causes emerged:
Weak Motivation
Young learners rarely practiced without external motivation. Existing gamification wasn't enough to sustain engagement.
Poor Discoverability
Students struggled to find age-appropriate stories, while teachers couldn't easily locate curriculum-aligned content.
High Cognitive Load
Read Aloud sessions felt demanding, while autoplayed English translations annoyed readers who didn’t need them.
COMPETITIVE ANALYSIS
Competitive gaps shaped the strategy
To ground the product strategy, I audited 6 representative products across 7 dimensions (target user, content type, instructional units, leveling, incentives, key features, subscription). Three competitive gaps shaped our direction:
83% assessed a learner's background during onboarding — age, grade, interests, sometimes a placement quiz — to match them to the right content from day one. We did almost none of this.
83%
Age
Gender
Grade level
Interests
Quiz
67% went beyond points with richer incentive systems—avatars, room decoration, rewards, and certificates. A leaderboard alone wasn't enough.
67%
Tickets and rewards
Avatar
Room decoration
Badges
Certificates
Read Aloud was our strongest differentiator. While competitors focused on voice recording, our speech-recognition tutor provided instant feedback. I made it the core of our strategy.
Speech recognition
VS
Voice recording
STRATEGY
Turning insights into design bets
Drawing on all the research findings above, I developed six design bets to address the key user pain points and market gaps:
Coin-and-shop economy
Reward learning with a coin economy, letting kids earn and spend coins to customize their avatars instead of relying only on leaderboards.
Friend invitation
Strengthen social motivation by letting children learn alongside friends they know instead of competing with strangers.
Personalized discovery
Recommend relevant stories based on students' grade level and interests captured during onboarding.
Search improvement
Improve content discovery with theme browsing and voice search for both students and teachers.
Sentence-level rewards
Break reading into achievable milestones by rewarding progress sentence by sentence instead of story by story.
Translation on/off
Give learners control over English translations with an explicit on/off toggle during practice.
DESIGN
Discovery that fits, motivation that sticks
With the strategy defined, I translated the six design bets into a cohesive product experience:
Game system
A coin-and-shop economy alongside points and the leaderboard: kids earn coins through stories, quizzes, and Read Aloud, then spend them to dress up and upgrade an avatar — creating a personal, visible goal beyond leaderboard ranking.
Friend invitation
An invitation flow that rewards both sides with coins, points, and subscription time. It gives children a familiar social circle to learn with, while helping the product reach new users through referrals.
Personalized discovery
Onboarding captures grade level and interests to power personalized recommendations. Search also supports voice input, “My Interests,” and “All Interests” browsing, so both young learners and teachers can find the right story faster.
Redesigned Read aloud
Learners can choose whether to keep English translation on during practice, and rewards now happen sentence by sentence so progress feels continuous — protecting the product’s key differentiator.
GO-TO-MARKET
Taking it to market: the Read-O-Rama contest
To relaunch AI Story Time and attract new subscribers, I designed Read-O-Rama — a reading contest where learners earned points through activities and the top 133 won prizes. I also created the promotional video end to end, from script and voice-over to editing.
Showcasing AI Story Time and the Read-O-Rama campaign at the ACTFL Annual Convention.
AI Story Time launch video, created by me end to end—from script and voice-over to editing.
IMPACT
A redesign that drove new subscriptions
As the sole product designer, researcher, and project manager, I shipped AI Story Time end to end: 1,000 animated stories across 15 levels, each paired with a quiz and AI-powered Read Aloud. I also launched Read-O-Rama to acquire new learners, converting thousands of new subscribers.
Thousands
new subscribers converted
1,000 stories at 15 levels
content shipped at launch
WHAT'S NEXT
From new subscribers to lasting engagement
AI Story Time taught me that engagement systems are never “done” — they need to be measured, tested, and tuned. If I continued the work, I’d use retention and behavior data to understand what drove return visits, then adjust content and incentives around those behaviors.