🚀 Multi-Client Marketing Analytics Infrastructure

End-to-End Dashboard Delivery for 50+ Clients

Led the design and delivery of a scalable analytics infrastructure for a marketing agency, building and maintaining over 150 production dashboards across 50 clients.

Stack: Airbyte · PostgreSQL · Metabase · SQL · Marketing APIs

📌 Project Overview

This project involved owning the complete analytics lifecycle for a performance marketing agency serving 50+ active clients.

On average, each client required 3 dashboards covering:

  • Campaign performance
  • Budget & cost tracking
  • Conversion & ROI analysis

The goal was to create a scalable, automated analytics system that could onboard new clients efficiently while maintaining data accuracy and reporting consistency.

🧩 Business Challenge

The agency faced several operational bottlenecks:

  • Manual data extraction from ad platforms
  • Time-consuming report preparation
  • Inconsistent KPI definitions across clients
  • Scaling difficulties as client count increased
  • Reporting delays impacting client communication

They needed a centralized, automated reporting system that could handle multi-client data workflows.

🏗 Solution Architecture

I designed and owned a scalable analytics framework consisting of:

1️⃣ Data Ingestion Layer (Airbyte)

  • Integrated multiple marketing data sources including Meta, Google Ads, and other ad platforms
  • Configured Airbyte connectors for automated data sync
  • Scheduled incremental data refreshes
  • Structured client-level data isolation

2️⃣ Database & Data Modeling (PostgreSQL)

  • Designed client-specific schemas
  • Built clean transformation layers using SQL
  • Standardized KPI calculations (CTR, CPC, ROAS, Conversion Rate)
  • Created reusable data models for rapid client onboarding

This ensured scalability and consistent metric definitions across clients.

3️⃣ Dashboard Layer (Metabase)

Delivered 150+ dashboards including:

  • Campaign performance dashboards
  • Spend and budget tracking dashboards
  • Conversion and ROI dashboards
  • Cross-channel performance reports
  • Executive summary views

Each dashboard included filtering by date, channel, campaign, and client-specific KPIs.

📊 Operational Scale

  • 50+ active marketing clients
  • ~3 dashboards per client
  • 150+ dashboards delivered
  • Automated daily data refreshes
  • Multi-source marketing data integration

🎯 Key Outcomes

✔ Eliminated manual reporting processes

✔ Reduced report preparation time significantly

✔ Enabled real-time client performance visibility

✔ Standardized KPI frameworks across accounts

✔ Built scalable onboarding workflow for new clients

✔ Improved agency-client reporting reliability

🧠 Technical Highlights

  • Multi-tenant data architecture design
  • Automated ETL pipelines using Airbyte
  • Advanced SQL transformation logic
  • KPI normalization across platforms
  • PostgreSQL performance optimization
  • Dashboard templating for scalability

💼 Business Impact

This system transformed the agency’s reporting capability from manual and fragmented to automated and scalable.

It enabled:

Higher operational efficiency across the analytics team

Faster client reporting cycles

Improved retention through transparent performance reporting

Efficient scaling without increasing reporting overhead