— Camylla is a Product Manager, Builder, and Problem-Solver based in Madrid 🇪🇸
Personalized Year-End Learning Summaries for Engagement and Retention
Brainly — Product Owner
To boost engagement and reinforce Brainly’s value as a learning companion, the team developed a year-end feature that celebrated user progress and encouraged reflection and return use.
Many users viewed Brainly as a transactional tool, unaware of their cumulative learning activity.
This created an opportunity to showcase individual progress through a personalized, data-driven experience — increasing platform affinity and reactivating lapsed users.
- Designed the end-to-end experience: tracked user learning behavior, surfaced key milestones, and delivered visually engaging summaries.
- Aligned product, design, data, and engineering teams to implement logic, backend aggregation, and frontend display across Web, Android, and iOS.
- Defined event mapping and data translation from raw user activity into meaningful, emotionally resonant metrics.
- Integrated lifecycle messaging through Braze to trigger delivery via push and in-app messages.
- Managed localization and delivery timing to ensure maximum visibility during strategic year-end engagement periods.
- Launched personalized learning summaries across platforms on time for the end-of-year cycle.
- Increased engagement metrics, including session duration and reactivation among dormant users.
- Strengthened user perception of Brainly as a long-term learning tool, not just a homework utility.
- Created a reusable framework for future lifecycle campaigns and user milestone messaging.
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.
Crowdin Integration and Localization Pipeline Ownership
Brainly — Product Owner
Brainly’s localization process was inefficient and error-prone, relying on outdated tooling (OneSky), manual developer requests, and inconsistent translation quality across platforms and markets.
With a global user base and content-driven platform, localization bottlenecks were delaying releases and creating UX inconsistencies.
The opportunity was to fully modernize the localization pipeline by selecting a better tool, automating developer workflows, and building a scalable internal localization operation.
- Researched and compared localization platforms; selected Crowdin based on automation potential, scalability, and platform compatibility.
- Led vendor negotiation, internal approval, and integration project across Android, iOS, and Web platforms.
- Owned post-integration management of the localization channel and acted as the single point of contact across development, product, and content teams.
- Selected, hired, and managed the internal localization team (translators, reviewers, language leads).
- Built automated workflows for developers to push and pull localization updates directly through Crowdin pipelines, removing manual steps.
- Designed process governance: versioning, priority setting, fallback handling, and communication protocols.
- Trained internal teams (engineering, content, product) on Crowdin workflows and access management.
- Replaced OneSky with Crowdin, enabling real-time, version-controlled localization across all platforms.
- Reduced localization turnaround time by eliminating manual developer steps and content handoffs.
- Improved translation consistency and quality across languages and product experiences.
- Established a repeatable, scalable localization framework adaptable to new products and markets.
- Increased engineering satisfaction by eliminating friction in the translation flow.
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.