Back to School Monetization A/B Testing
Brainly — Product Manager
Back to School season is Brainly’s peak revenue window in the US, critical for annual subscription targets and user growth milestones.
User acquisition during Back to School surges dramatically, but converting free users to subscribers was historically inconsistent.
There was an urgent opportunity to optimize packaging, pricing, and promotion strategies to maximize conversion rates and reduce churn during this short, high-impact season.
- Designed and executed A/B tests on subscription pricing tiers, feature packaging, and promotional messaging tailored for the US student and parent demographic.
- Coordinated cross-platform rollout across Android, iOS, and Desktop, aligning marketing, engineering, and analytics teams.
- Leveraged behavioral segmentation to personalize onboarding offers and pricing experiments based on acquisition channels.
- Conducted rapid-cycle testing and iterative hypothesis refinement based on real-time Amplitude data analysis.
- Synthesized results into strategic recommendations for permanent pricing model adjustments.
- Achieved a significant uplift in subscription conversion rates during Back to School window.
- Reduced onboarding drop-off by optimizing offer timing and channel targeting.
- Improved LTV of new users acquired during the Back to School campaign versus previous years.
Gamification System Redesign for User Engagement
Brainly — Product Manager
Brainly’s original gamification system heavily rewarded only answering questions, encouraging quantity over learning depth and discouraging broader platform engagement.
The platform’s legacy gamification incentivized high-volume answerers but failed to reward genuine learning behaviors like asking questions, sustained studying, or topic mastery.
The opportunity was to fundamentally reframe gamification to support deeper user engagement, sustained retention, and meaningful learning progress, aligned with Brainly’s evolving educational mission.
- Audited the existing gamification system and identified key behavioral gaps undermining platform engagement and learning depth.
- Developed a strategic roadmap shifting focus from simple activity counting to learning journey reinforcement (personalized paths, progress streaks, topic-specific achievements).
- Proposed feature designs including dynamic daily engagement streaks, subject-based statistics, and adaptive rewards based on learning consistency, not volume alone.
- Worked with UX/UI teams to integrate motivational triggers and behavioral nudges into the core platform experience.
- Aligned stakeholders from product, education, and executive teams around the new vision for gamification evolution.
- Approved strategic shift of Brainly’s gamification system toward learning-oriented user rewards.
- Integrated new behavioral principles into future feature planning, refocusing product growth around active learners rather than passive traffic.
- Set the foundation for sustainable engagement strategies beyond transactional usage.
Strategic Vision for a Personalized, AI-Driven Learning Experience
Brainly — Marketing Strategist
Brainly needed to evolve from a high-traffic homework Q&A platform into a more engaging, indispensable learning companion.
This self-initiated vision work aimed to define what that transformation could look like through a structured, personalized, and AI-augmented study experience.
Despite its scale, Brainly’s user experience was transactional — users came for one-off answers rather than long-term study support.
The opportunity was to design a product direction that shifted from isolated queries to structured, session-based learning journeys, aligning with user behavior, retention, and educational value.
- Conducted research to map user pain points and emotional friction in the current experience.
- Analyzed competitor platforms and user motivations to uncover opportunities for differentiation.
- Designed a modular product framework centered on guided “study sessions” combining AI-generated support, user goals, and progress tracking.
- Proposed features such as dynamic content personalization, dual-model answer comparison, citation generation, paraphrasing tools, and learning analytics dashboards.
- Integrated AI into user workflows not as a gimmick, but as a tool for confidence-building, clarity, and reduced cognitive load.
- Created a phased rollout roadmap, including MVP scoping, adoption strategies, and UX principles for long-term engagement.
- Delivered a complete strategic blueprint for platform evolution, presented to internal stakeholders.
- Elevated internal discussion around long-term product direction, AI integration, and session-based learning value.
- Positioned the platform to explore deeper engagement models beyond reactive Q&A loops.
Exploration of a Dynamic Metering System for Monetization Optimization
Brainly — Product Manager
As Brainly looked to evolve its freemium model, static access limits (e.g., fixed paywalls after X answers) created blunt user experiences and left revenue on the table.
There was a need to explore more nuanced, behavior-based metering to balance engagement and monetization.
The existing access model treated all users the same, regardless of behavior or intent — either offering too much for free or pushing away high-value users too early.
The opportunity was to design a dynamic metering system that adjusted content access thresholds based on user behavior, predicted conversion potential, and platform value delivery — increasing monetization without harming engagement.
- Conducted exploratory research on metering strategies used by subscription-based content platforms (media, edtech, productivity).
- Designed a scoring algorithm using behavioral inputs (session depth, feature usage, engagement history) to dynamically assign access thresholds.
- Proposed content gating flows (e.g., adwall, soft paywall, reward-unlock gates) tailored to user clusters.
- Used principal component analysis (PCA) and engagement signals to simulate user segmentation for prototype testing.
- Outlined experimental design for phased A/B testing, including fallback conditions and sensitivity analysis for impact on churn, engagement, and LTV.
- Delivered a full spec doc including architecture, scoring logic, threshold calibration strategy, and success metrics.
- Provided a technically and behaviorally grounded framework for adaptive monetization experimentation.
- Shifted internal thinking away from fixed thresholds toward intent-driven gating models.
- Enabled future pilots of metering strategies aligned with personalization and AI scoring tools.
- Positioned Brainly to scale monetization intelligently without compromising trust or learning outcomes.