How a Marketing Agency Automated Client Reporting

The Challenge

A 35-person marketing agency was spending 15+ hours every week manually pulling data from Google Ads, Meta, HubSpot, and Google Analytics to build client reports. The process was error-prone, inconsistent, and took senior strategists away from actual strategy work.

Their reporting stack looked like this:

• Google Ads data exported to spreadsheets
• Meta Ads Manager screenshots pasted into slides
• HubSpot CRM data manually cross-referenced
• Google Analytics pulled into separate dashboards
• Everything assembled in Google Slides, client by client

What We Built

We engineered an automated reporting pipeline that pulls data from all four platforms, normalizes it, and generates branded client reports automatically every Monday morning.

The technical stack:

• Custom API integration layer connecting all ad platforms
• PostgreSQL data warehouse for historical trend analysis
• Automated data normalization and QA checks
• Templated report generation with client branding
• Automated email delivery with PDF attachments

The Architecture

The system runs on a scheduled pipeline:

1. Data Collection (Sunday night): Automated jobs pull the previous week's data from each platform API
2. Normalization: Raw data is cleaned, deduplicated, and mapped to a unified schema
3. Analysis: Automated calculations for WoW trends, pacing vs. goals, and anomaly detection
4. Report Generation: Branded PDF reports generated per client using their specific KPIs
5. Delivery: Reports emailed to clients and account managers Monday at 7 AM

Results

The impact was immediate and measurable:

• 15 hours/week saved on manual reporting
• Zero errors in the first 3 months (vs. ~2 corrections per week previously)
• Faster insights: Reports delivered Monday morning instead of Wednesday afternoon
• Scalability: Adding a new client takes 15 minutes of setup instead of adding another hour to the weekly reporting cycle

Key Takeaway

Reporting automation isn't just about saving time. It's about making your data infrastructure reliable enough that your team can trust it and act on it. When strategists aren't spending half their week in spreadsheets, they can focus on the work that actually grows client accounts.