We took over the nationwide private-lease account of this Dutch automotive provider at the start of the COVID period. Cost-per-conversion sat around €115 and the conversion-volume line was nearly flat — a campaign bidding against weakly defined intent, with budget spread across auctions that did not convert. Twenty-four months later the account had landed at roughly €60 per lead — −48% versus the level we inherited — and conversion volume had climbed from around 120 leads per quarter to ~375. Same provider, same product, same monthly budget; what changed was what the campaign was bidding on.
What we did
Tightening ad relevance. Pulling budget out of the auctions that returned nothing.
The inherited account was structured by historical budget categories rather than by how private-lease decisions actually get researched. Searches from someone comparing monthly lease prices look nothing like those from someone choosing between a specific model and a competitor; they do not belong in the same ad group, and they were. We rebuilt the campaign and ad-group structure around lease-decision intent themes — model-specific demand, searches within monthly budget ranges, lease-versus-buy research — with ad copy and landing-page transition matched to each theme.
Ad relevance is what moves Quality Score, and Quality Score decides whether the bid you set even reaches the auction. A €0.85 bid at Quality Score 9 beats a €1.20 bid at Quality Score 5. Most of the CPL gain came out of this layer.
With the new intent structure in place, the budget reallocation was visible in the monthly auction-insight data. Broad-match catch-alls that had been swallowing budget without converting were gradually starved; the clusters where lease decisions actually landed were fed. Visible in the biggest-changes panel of the screenshot: one campaign cluster had €25,880 (−40.55%) pulled away, and the matching +€26,384 went to the cluster that actually converted. One pulled, one pushed — every shift accountable to the underlying conversion data.
Work then shifted to weekly maintenance: search-term cleanup, monthly auction-insight review, seasonal reweighting around the Dutch car-buying cycles. By the end of the engagement, cost-per-conversion had settled at around €60 — well under half the level we inherited — and conversion volume was running roughly three times the starting rate. The before-and-after is not the result of a single quarter; it is twenty-four months of compounding small honest decisions, the kind that require someone keeping the rhythm steady that long.
Read the chart left to right. The red conversion-volume line climbs from a nearly flat 2020 baseline; the yellow cost-per-conv falls from above €120 toward €60 in 2022. The biggest-changes panel shows one cluster where €25.9K (−40.55%) was pulled away and the matching +€26.4K that went to the cluster that actually converted — one of the clearest single-frame illustrations of ”same budget, different placement” in the portfolio.
Was able to work with Feisal for several years in the automotive industry. The goal of our cooperation was to generate as much revenue as possible with online activities for customers in this branch. Feisal has a good outlook and pragmatic approach.
By the numbers
24 months, 1,940 conversions, €115 to €60 cost-per-lead. The blended figures across the full engagement: 147K clicks, 1,940 conversions, €136K total spend, €70.03 average cost per conversion. The trajectory shows where the work was: a cost-per-conv that fell from around €115 at takeover to roughly €60 stabilized, while quarterly conversion volume tripled from about 120 to ~375.
Cost per conversion: from a flat structure with broad-match catch-alls (takeover, early 2020) to intent-mapped clusters with reallocated budget (stabilized, mid-2022).
Same provider, same monthly budget, three times the conversions. The change was not the budget — it was what the budget was bidding on.
Boring, predictable, attributable. That’s what good PPC looks like.
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