Consolidating Cross-Channel Ad Metrics Into a Unified Real-Time Marketing Dashboard
"By consolidating fragmented Meta and Google Ads schemas into a type-safe data lake, we eliminated daily manual reporting entirely, empowering decision-makers with instant, normalized cross-channel insight."
- Monorepo system architecture powered by Turborepo and Bun
- Normalized multi-currency spend tracking (USD / INR) with an instant client-side switcher
- Redis & BullMQ background sync pipeline running at 10-minute intervals with exponential backoffs
- Unified database schema supporting granular daily ad and campaign level performance metrics
- AI-driven daily anomaly detection alerting on spend spikes above 150% of the 7-day baseline
- Dual client/server-side jsPDF reporting engines integrated with containerized n8n webhooks
The Challenge: Fragmented Metrics
Modern digital marketing teams run spend across Google and Meta, but each platform serves campaign stats under distinct API parameters, schemas, and terminology. Standardizing conversions, clicks, and impressions into a single, cohesive view usually requires hours of error-prone manual spreadsheets.
Additionally, billing across multiple regional currencies (e.g. USD vs INR) makes global spend totals difficult to track dynamically, causing budgeting anomalies to slide past unnoticed until invoices arrive.
API Schema Fragmentation
Google and Meta Ads use completely distinct terminology (e.g., Campaign vs Ad Set) and data formats.
Currency Discrepancies
Inability to view consolidated spending metrics when different campaigns use different billing currencies (USD vs INR).
API Rate Limiting
Accessing live APIs during high-traffic visual dashboard loads leads to performance degradation and rate limits.
Manual Report Dispatch
Marketing managers spend hours manual compiling metrics and generating PDF reports to send to clients via email or Slack.
Spend Anomalies
Lack of real-time spend spike and CPC anomaly detection, causing budgets to drain before intervention can occur.
Real-Time Synchronization & Normalization
We decoupled the visual reporting layer from the API sync process. An asynchronous worker pipeline built with **Bun** and **BullMQ** runs background syncs every 10 minutes. A central currency-exchange utility hooks into daily rates to normalize all metrics in PostgreSQL, offering toggles to view calculations in USD or INR instantly.
Turborepo Decoupling
Separated high-traffic Next.js visual dashboards from network-intensive background sync workers, keeping client UI smooth.
Multi-Currency Normalization
Automatically normalizes all campaign spend metrics to USD in PostgreSQL, with an instant live USD/INR switcher in the dashboard UI.
Asynchronous Queueing
Built a BullMQ & Redis worker service under Bun runtime that syncs ad accounts every 10 minutes with exponential backoff retries.
Dual-Engine PDF Compilation
Engineered jsPDF pipelines for instant client-side downloads and server-side Base64 reports for automated delivery.
Automated Webhook Dispatch
Integrated containerized n8n servers to schedule, fetch, and broadcast daily PDF attachments to Slack and WhatsApp.
AI Anomaly Detection
Developed mathematical baselines comparing yesterday's spends to 7-day rolling averages, highlighting spikes of over 150%.
Automated Daily Reporting Pipelines
To remove manual report compilation entirely, we built a dual-engine reporting pipeline. Inside the browser, users can trigger client-side **jsPDF** renders for instant exports.
On the server, an API endpoint compiles campaign rollups into base64 PDFs daily. A containerized **n8n** webhook engine triggers every morning, fetches the PDF briefings, runs spend anomaly checks against 7-day rolling budgets, and automatically broadcasts formatted reports directly to team Slack channels, WhatsApp, and stakeholders.
Operational Impact & Comparison
Decoupled Monorepo Design
The system uses a Turborepo monorepo framework where a Next.js frontend (utilizing React 19) is completely separated from the background sync service running on Bun. PostgreSQL acts as the single source of truth, accessed through type-safe Prisma ORM clients. Background jobs are scheduled and executed via BullMQ and Redis queues to insulate the system from external API rate-limiting issues. The reporting layer features a dual-mode jsPDF setup: client-side for instant download and server-side API endpoints for automated, Base64-encoded PDF generation. These endpoints integrate seamlessly with n8n workflow webhooks to orchestrate automatic daily dispatches to Slack, WhatsApp, or email.
Deployed Stack
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About Arcnetic
Arcnetic is an elite digital engineering studio specializing in high-performance web development, custom dashboards, distributed background queues, and complex integrations. We don't just write code — we build corporate-grade digital ecosystems.
© 2026 Arcnetic. All rights reserved. Case study published with client consent.
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