Google Ads Case Study: +141% Leads for Alfa Romeo Dealership

The situation

Most automotive dealerships rely on generic catalog ads and broad brand campaigns that generate unqualified traffic. Alfa Romeo's previous agency ran basic promotional ads without strategic segmentation - poor lead quality and wasted spend on prospects not ready to purchase. Google ads for car dealerships only convert when structure mirrors how shoppers search by model and intent. The franchise needed Google Ads that matched how buyers actually shop: by model, by intent (new vs. used), and by the specific inventory they had already viewed - not another round of dealership-wide promotions. Arizona market competition meant broad brand terms burned budget while model-specific demand went uncaptured. Lead volume was flat and CPL was rising before the restructure.

The insight

Successful automotive campaigns segment by specific vehicle models and buying intent. Generic dealership messaging attracts tire-kickers; model-specific campaigns with intent-based segmentation attract buyers who know exactly what they want. We reverse-engineered what top-performing dealers were doing differently: separate campaign architecture per model, URL-level retargeting on inventory pages, and negative keyword lists that stopped campaigns from competing against each other. Performance Max only helps when negatives and audience guardrails prevent it from cannibalizing exact-match search that already converts.

What we deployed

Model-specific campaign architecture Restructured Google Ads with model-specific targeting - separating new and used vehicle interests so each ad spoke to a defined buyer moment instead of a generic lot tour. 8 model lines got dedicated campaign shells with unique ad copy and landing paths.

URL-specific retargeting on inventory Implemented retargeting tied to the exact vehicle detail pages prospects viewed, so follow-up ads matched the model already in consideration. Dynamic remarketing refreshed within 48 hours of inventory changes.

Tracking rebuilt in GTM Rebuilt conversion tracking in Google Tag Manager - vehicle detail views, catalog browsing, and form submissions each fired as distinct events so optimization had clean signal. 3 duplicate conversion actions were removed in week 1.

Negative lists and Performance Max discipline Built 10+ negative keyword lists to eliminate campaign conflicts and continuously optimized Performance Max with visual targeting for relevance. Brand and non-brand separation stopped internal auction inflation.

Weekly search term governance Search term reviews ran every 7 days with add-to-negative rules by model and intent. Junk terms that slipped through broad match were cut before they consumed 5% of weekly spend.

Results

Lead volume increased 141% within 60 days. Cost per lead dropped 62%. Generic brand spend became a precision lead machine - higher volume and measurably better qualification because ads matched model and intent instead of broadcasting to everyone. Model-specific campaigns delivered 3x higher form completion than legacy brand promos. Retargeting on viewed VDPs accounted for 40% of qualified leads in month 2 without increasing total budget. The marketing lead reported overnight quality shift - reps stopped complaining about irrelevant inquiries within the first 30 days post-launch. Stakeholder reporting moved from blended CPL to model-level dashboards - making 62% CPL reduction auditable in weekly standups, not just end-of-month summaries.

Why it worked

Model beats brand in automotive search Buyers search for the car they want, not the dealership logo. Campaign structure that mirrors that behavior converts at a fundamentally different rate.

Retargeting only works when it is specific Showing the exact inventory someone viewed is the digital equivalent of a salesperson who remembers the test drive - relevance drives conversion.

Clean tracking unlocks optimization Without GTM-level event separation, Google optimizes on noise. Proper infrastructure is what makes a 141% lead lift repeatable instead of accidental.

Negatives protect scale 10+ lists are not bureaucracy - they are how 8 model campaigns coexist without bidding against each other on the same query.

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