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.
Offline-First Django CRM Development
Freelancer — Systems Architect
The Service of Applied Psychology at UNED needed a CRM system to manage patient cases and session schedules while complying with strict university regulations: no internet connection, full local data control, and access restricted to authorized administrative personnel only.
Commercial CRM solutions could not meet the university’s data sovereignty and security requirements.
The opportunity was to design and deliver a fully offline, GDPR-compliant CRM system capable of managing patient data, therapist schedules, supervisions, and administrative reporting, all from a single secured local machine.
- Designed and built an offline-capable CRM platform using Django, deployed locally on a dedicated Windows machine.
- Developed models and workflows for patient management, case tracking, session scheduling, therapist coordination, payment recording, and supervision logs.
- Implemented user authentication, access controls, and local backup procedures to secure sensitive data without cloud reliance.
- Built the system modularly to allow administrative users to operate independently with minimal technical intervention.
- Conducted full training for the administrative team on platform operation, basic maintenance, and data protection best practices.
- Documented all system procedures and provided a localized offline user manual.
- Delivered a fully functional, offline-first CRM that met all UNED’s data protection, access control, and operational requirements.
- Enabled efficient patient intake, scheduling, and case management without external software dependencies.
- Reduced administrative overhead by centralizing previously fragmented workflows into one streamlined system.
- Achieved full GDPR compliance for patient data storage and management within a university context.
Appbot Platform Ownership and App Review Insights Team Management
Brainly — Product Owner
With millions of mobile users, Brainly’s app stores received constant user feedback through reviews — a high-volume, high-noise channel that had been underutilized for actionable insights.
User sentiment was fragmented across platforms and languages, with no structured process for extracting insights from reviews.
The opportunity was to operationalize app store feedback analysis using Appbot and a dedicated team to surface qualitative insights for product, UX, and support teams.
- Took full ownership of Appbot platform: user management, tag design, alerting logic, and feedback flow configuration.
- Recruited and managed a dedicated app review team responsible for tagging, triaging, and summarizing feedback across 7+ languages.
- Created standardized workflows for feedback escalation to Product, Design, Engineering, and Support teams.
- Implemented sentiment tracking dashboards segmented by platform, language, and feature.
- Coordinated with the localization and content teams to manage cultural and linguistic nuances in feedback interpretation.
- Established periodic insight reports and reactive feedback alerts tied to releases or spikes in negative reviews.
- Reduced latency between app feedback and issue detection, improving response time and customer trust.
- Improved signal-to-noise ratio in app reviews, surfacing 10x more actionable insights per cycle.
- Enabled structured tracking of feature-specific sentiment across time and geographies.
- Institutionalized a permanent feedback channel within the product development cycle.
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.
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.
Redesign of the User Ban Experience for Fairness and Trust
Brainly — Product Manager
Brainly’s automated moderation and ban systems were functionally effective but often perceived by users as opaque, arbitrary, or unfair — undermining platform trust and increasing support ticket volume.
Users who were banned (often for violating content or behavior policies) received minimal context or guidance, resulting in confusion, frustration, and unnecessary churn.
The opportunity was to redesign the entire ban experience — from messaging to appeals — to increase clarity, reduce repeat violations, and preserve user trust even during enforcement.
- Audited the existing ban triggers, messaging flow, and user-facing touchpoints across platforms.
- Proposed and implemented a tiered penalty system with escalating consequences tied to user behavior history.
- Designed new UX patterns including clear messaging on cause, ban duration, and user recourse options.
- Integrated the system with Zendesk to generate automatic tickets for review, reducing response latency and support overhead.
- Added educational content and community guideline links to all ban-related communications.
- Aligned enforcement flows with user sentiment data and legal/privacy guidelines.
- Reduced repeat ban rates through clearer warnings and educational interventions.
- Improved user perception of fairness in platform enforcement — confirmed via support feedback and user interviews.
- Lowered support team workload by automating ban-related ticketing and triage.
- Strengthened Brainly’s moderation framework without alienating borderline users.
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.
Django-Based Collaborative Dissertation Platform
Freelancer — Systems Architect
Traditional academic supervision tools (Word, email, PDFs) were unstructured, hard to track, and inefficient for managing feedback on a 300+ page dissertation under constant revision.
The goal was to build a purpose-built collaboration platform for real-time document review between PhD student and advisor.
Academic advisors needed a structured way to comment on specific sections, track changes over time, and reference data tables and figures — none of which was well-supported by traditional tools.
The opportunity was to build a lightweight but powerful Django-based app that enabled inline feedback, review tracking, and custom integration of code-generated content.
- Designed a custom collaboration platform tailored to the academic supervision workflow, enabling structured feedback and version control across long-form documents.
- Built a local-first system that prioritized data privacy, modularity, and full author control over content and revisions.
- Developed flexible editing and commenting capabilities to support granular, sentence-level review and iterative improvement.
- Implemented dynamic content handling to support integration of external elements such as data tables and figures generated in Python.
- Created administrative tools to manage documents, track feedback cycles, and support academic process transparency.
- Future-proofed the architecture to accommodate citation logic, content compilation, and extended use beyond a single dissertation.
- Eliminated friction in PhD feedback loops — supervisor could leave comments per sentence, reducing back-and-forth confusion.
- Enabled centralized review across dozens of chapters, interviews, figures, and datasets.
- Significantly reduced cognitive load for managing revision cycles and integrating comments.
- Demonstrated feasibility of a structured alternative to traditional word processors for academic research.
Coda-Based Accounting System with Multi-Table Sync and Automation
Centro de Psicología Sandra Ribeiro — Systems Architect
As the clinic scaled, financial tracking became fragmented across spreadsheets, invoices, and session logs.
There was an urgent need for a unified accounting system to track revenue and expenses across therapists, session types, and payment sources — while ensuring data integrity and auditability.
Existing tools couldn’t connect session records, payments, invoices, and supervision tracking into a coherent, flexible financial overview.
Manual entry created duplication risk, poor traceability, and no real-time visibility into financial health.
The opportunity was to design a live, low-maintenance, auditable accounting system built entirely in Coda.
- Designed the system architecture to consolidate financial data from multiple service lines and workflows into a single source of truth.
- Implemented automated logic to sync and categorize income and expenses based on operational activity.
- Built custom interfaces to allow the administrative team to manage finances with minimal manual input or duplication.
- Ensured traceability between financial records and their operational origin (sessions, supervisions, payroll, etc.).
- Structured the system to support accurate forecasting, tax preparation, and performance reporting.
- Replaced fragmented financial tracking with a unified, real-time accounting system.
- Reduced manual workload and error rates in financial reporting.
- Enabled strategic oversight of the clinic’s revenue streams, costs, and category-level performance.
- Created a scalable foundation for further automation (e.g., invoicing, digital signatures, external integrations).