— Camylla is a Product Manager, Builder, and Problem-Solver based in Madrid 🇪🇸
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Brainly’s localization process was inefficient and error-prone, relying on outdated tooling (OneSky), manual developer requests, and inconsistent translation quality across platforms and markets.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.
Braze Integration and Cross-Platform Engagement Strategy
Brainly — Product Owner
Brainly needed a robust engagement automation platform to support scalable user communication across push notifications, in-app messaging, and email — all localized and behavior-triggered across platforms.
The engagement stack was outdated, non-personalized, and inefficient to scale across Brainly’s 350M+ user base.
The opportunity was to integrate Braze and establish a modern, fully owned user engagement pipeline — covering push notifications, in-app messaging, and lifecycle automation with high segmentation precision.
- Led vendor research, evaluation, and contract negotiation, aligning stakeholders across Product, Marketing, and Legal.
- PMed the full integration across Android, iOS, and Web, managing cross-functional dependencies (backend, localization, frontend, analytics).
- Designed scalable user journeys for push and in-app, mapped to behavioral triggers across the user lifecycle (onboarding, activation, re-engagement, upsell).
- Post-integration, assumed full ownership of the Braze channel: campaign strategy, message design, testing, and performance optimization.
- Implemented A/B and multivariate testing for timing, messaging tone, and feature prompts.
- Trained internal teams on Braze usage, permissions, segmentation logic, and lifecycle program structure.
- Completed Braze integration across all platforms under time and scope constraints.
- Decreased campaign creation time by over 80%, from multi-week engineering cycles to self-service execution.
- Boosted push and in-app engagement metrics through highly targeted journeys tied to user behavior.
- Enabled market- and language-specific personalization at scale.
- Maintained full product-side ownership of the channel post-launch, aligning messaging strategy with product and monetization goals.
SEO & AI Initiative
Brainly — Product Manager
Faced with Google’s SGE update threatening organic traffic, Brainly needed a scalable strategy to defend SEO rankings and maintain traffic acquisition.
Brainly’s organic search traffic was at serious risk due to Google’s new AI search features surfacing direct answers instead of traditional search listings.
The goal was to generate SEO-optimized topical content at scale to defend and grow Brainly’s visibility while minimizing development and operational costs.
- Led the exploration of scalable SEO content generation strategies using AI and scraping tools.
- Designed a Python-based system to orchestrate topical content creation across up to 1 million subjects.
- Built AI prompting frameworks for content generation aligned with educational standards and SEO best practices.
- Negotiated and aligned cross-functional teams (AI, Content, Product, Engineering) around a lean MVP plan, cutting proposed costs drastically.
- Supervised the web scraping and QA process to ensure topical accuracy and coverage.
- Reduced projected project costs from $300K to $15K by designing in-house MVP approach.
- Achieved 93% topical coverage and 70% QA accuracy across generated content.
- Delivered full MVP framework and initial data generation plan ahead of stakeholder deadlines.
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.