Development of a SaaS B2B Marketing Web Platform

This SaaS B2B Marketing Web Platform is designed to give growth and marketing teams a single source of truth for their performance data. The application connects to multiple data sources - Google Analytics, Google Ads, Meta Ads, and social platforms and consolidates them into a real-time dashboard that surfaces traffic, ROI, conversions, CPA, CTR, and lead quality in a clean, card-based interface. Users can monitor trends over time, drill into individual leads, and review social performance widgets that show followers, engagement, and top posts. The platform features a responsive, desktop-first interface, a scalable back-end analytics layer, and scheduled data syncs from third-party APIs. As a Full Stack Engineer on this project, I was responsible for architecting, building, and deploying both the front-end dashboard and the back-end data services.

Front-End Development: Implemented the main analytics dashboard using React and Next.js with TypeScript, focusing on a clean, “glassmorphism” visual style and smooth interactions. Built reusable components for KPI cards, time-series charts, filter bars, lead tables, and social performance widgets, ensuring consistent behavior across the Realtime Overview, SEO, Paid Ads, and Social Media sections. Integrated charting libraries to render interactive traffic, ROI, and conversion trends with hover states, tooltips, and date-range controls.

Back-End Development: Developed a scalable REST/GraphQL API using Node.js and Express, responsible for ingesting, normalizing, and serving campaign, lead, and engagement data. Implemented background jobs for scheduled data pulls, data transformation pipelines, and summary metric calculation so the UI can fetch pre-aggregated metrics with low latency. Exposed endpoints for KPI summaries, time-series data, lead lists, and social statistics, with query parameters for date ranges, channels, and segments.

API Integrations: Integrated external APIs from Google Analytics, Google Ads, Meta, and social networks to automatically pull performance metrics, follower counts, and engagement stats. Implemented OAuth-based authentication for connecting customer accounts securely, and built a mapping layer to unify metrics from different providers into a common schema usable by the dashboard.

Database Management: Designed and optimized a PostgreSQL schema tailored for analytics workloads, separating raw event tables from aggregated reporting tables. Added indexes and partitioning strategies to support fast querying across large time windows, and implemented data retention policies to keep storage usage predictable while preserving historical trends.

Testing and Deployment: Wrote unit and integration tests using Jest and supertest to validate core API endpoints, data transformations, and permission rules. Deployed the application using a CI/CD pipeline, with the front-end hosted on Vercel and the back-end and database running on AWS (ECS/RDS), including environment-based configuration and automatic migrations.

Collaboration: Worked closely with marketing stakeholders and designers to refine the dashboard layout, prioritize key KPIs, and ensure the interface matched real analyst workflows. Translated business requirements, such as "identify high-potential leads quickly" and "compare performance across channels at a glance" into technical features like AI-assisted lead scoring, sortable lead tables, and channel-specific widgets, delivering a platform that is both powerful for data-driven teams and approachable for non-technical users.