Enterprise Ad Campaign Automation

A Python application built on the Google Ads API to automate a process that, at Quandoo, originally consisted of fifty manual steps run by hand every week: pulling current performance, editing bids, cleaning up label hygiene, and reshuffling budget across campaigns. Turning that into a script eliminated the risk of human error in the handoffs between steps and reclaimed approximately 30 hours every week that had been going into list-pulling and spreadsheet edits instead of strategy.

Replacing a 50-step manual PPC workflow

The workflow it replaced was the kind that accretes over years: a checklist somebody wrote down once, followed literally by every analyst since, regardless of whether every line still earned its place. Bid edits, budget pacing checks, label hygiene, campaign-level QA: fifty discrete steps, each one small enough to seem not worth automating on its own, but adding up to a manual ritual that ran every single week without fail.

How the Google Ads API automation runs

The script runs the team’s full weekly workflow in one command: pulling current performance data through the Google Ads API, applying the rule set the team had previously been running by hand, and writing the changes back through the same API. Configuration lives in human-readable YAML rather than buried in code, specifically so a non-technical marketer can open it, see what a rule does, and adjust a threshold without needing an engineer in the loop.

Auditing the process, not just automating it

The audit that came with building it mattered more than the automation itself. The same fifty steps had been running since long before I joined, and turning each one into code meant asking, one at a time, whether it still needed to exist. Roughly a third of them disappeared in the first month. They had quietly stopped being load-bearing, but nobody had noticed, because nobody wanted to be the one to break a working manual process to test that theory. Automation forced the question that a checklist never would have.

Results: reclaimed hours, lower CPA, better budget efficiency

• 30+ hours a week reclaimed across the user-acquisition team, redirected from list-pulling into actual strategy work.
• 65% reduction in CPA on the campaigns the automation touched.
• 4× improvement in paid-budget efficiency, measured across Paid Search, Social, and Display on UA spend approaching €1M a year.

The system didn’t stay a one-off script. It became the substrate the in-house attribution framework was built on top of afterward, since it was already the thing pulling and reconciling campaign-level performance data on a schedule.