The Business Challenge
The business situation the organisation faced before the project began.
As the agency grew, client reporting across multiple accounts was manual and daily. It ate hours and capped how many clients each handler could manage, so capacity, not demand, became the bottleneck to growth.
How the Solution Was Delivered
Discovery, design, development, testing and rollout — the journey, not the tooling.
- 1Audited the manual reporting workflow and found the daily data pulls were the bottleneck
- 2Built Python ETL to pull Meta and Google Ads data daily across all accounts
- 3Automated report generation through the Claude API
- 4Wired n8n workflows to schedule and deliver reports without manual steps
- 5Rolled out across the team and tuned for reliability
Business Outcomes & Impact
The measurable outcomes recorded on this AI Case Study — with the story behind them.
Cut report turnaround by 50 to 70 percent and lifted account-handler capacity from 3 to 4 clients to 6 to 8, removing capacity as the bottleneck to growth.
Business Outcome Categories
The story behind the numbers
Report turnaround dropped 50 to 70 percent, and each account handler went from covering 3 to 4 clients to 6 to 8. That added capacity supported the agency through a year of 40 percent revenue growth.
Lessons Learned
What surprised the team, what worked well, and what would be done differently.
- The constraint was the manual process, not the tooling. Fixing the workflow unlocked capacity faster than hiring would have.
- Consistency mattered as much as speed. Automated reports were uniform across every account, not just faster.
- Investing in automation slowed the team short term but paid back quickly in leverage.