Luigi.

As one of the largest online fashion eshops in Greece, Luigi had crossed the threshold where small efficiency gains translate into meaningful revenue. At that scale the biggest challenge is maximizing the effectiveness of ad spend — and the biggest component of that challenge is the Google Ads account, which runs the majority of performance spend for the brand.

Above a certain account size, waste becomes invisible. A single underperforming keyword in a mid-tier ad group might burn a few euros a day — not enough to trigger a manual review, but across hundreds of campaigns and thousands of queries, the cumulative drain becomes significant. The human account manager sees aggregate campaign performance, not the atomic waste pattern; by the time it surfaces in a weekly report, it has already been funding a leak for days.

The brief was simple to state and hard to execute: maintain perfect optimization hygiene at scale, without asking the account manager to manually comb through terabytes of query and performance data. The answer had to be a system that sees what a human eye cannot see fast enough — and translates that signal into a short, prioritized action list the manager can act on in minutes.

We moved years of hard-won Google Ads expertise into an automated analysis and alerting system capable of processing several terabytes of data daily without error. The system ingests Google Ads performance data at the keyword × query × hour × device granularity, joins it with GA4 revenue data and Merchant Center catalog state, and runs a library of analysis rules against the combined dataset.

The rules encode the kind of pattern-matching a senior account manager does intuitively — spot a search term that is burning budget with zero conversions, flag a query whose CPC has drifted outside its expected band, detect a product category whose ROAS has dropped below threshold for three consecutive days. What used to take a full day of analyst time to find is now flagged automatically the moment the pattern emerges.

Output lands as a daily briefing for the account manager: a ranked list of the highest-impact actions, with the supporting data already joined and visualized. No dashboard-hopping, no exports, no pivot tables. The manager reviews the list, approves or adjusts, and the actions are pushed back into the account — with logs of what changed, why, and what the expected impact is. Interaction time per account dropped from hours to minutes per day.