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.
Student Experience Research and Pain Point Mapping
Brainly — Product Manager
As Brainly matured, it needed a deeper understanding of its student users’ emotional journey — beyond surface-level metrics — to inform more engaging, trust-building, and learning-focused product strategies.
Product teams lacked a clear map of how students experienced the platform emotionally and cognitively.
This created misalignment between feature delivery and actual user needs — especially in moments of frustration, uncertainty, or disengagement.
The opportunity was to synthesize a comprehensive student experience map to guide strategic priorities and product narratives.
- Designed and executed a mixed-method research initiative combining in-depth interviews, guided user testing, behavioral surveys, Hotjar recordings, and session replays.
- Analyzed user behavior across different journey stages — first contact, repeated use, disengagement, frustration, churn — to identify key inflection points.
- Led synthesis workshops with Product, Design, and Growth teams to align findings to platform decisions.
- Produced a visualized journey map connecting emotional states, behavioral patterns, and product interactions.
- Framed opportunity areas for feature ideation, UX adjustments, and AI augmentation grounded in real user struggles.
- Delivered actionable research assets used in multiple product and marketing team roadmaps.
- Revealed blind spots in product assumptions, shifting roadmap priorities toward learning support and frustration mitigation.
- Informed the development of multiple new features aimed at increasing trust, reducing confusion, and reinforcing engagement.
- Reframed internal product language around student motivation, cognitive load, and emotional states.
- Became the foundation for broader initiatives exploring learning sessions, motivational design, and AI-based support.
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.