Renault
Consolidation of multiple formats and channels into a single campaign driven by Google's machine learning (bidding, creative mix, channels) on a conversion objective
Renault (Turkey) cut its cost per conversion by 86% by consolidating its lead-generation campaigns into a single Google Performance Max campaign driven by machine learning; the UK entity replicated it with a CPA 67% below its target.
Key points
- Lead-generation campaigns consolidated into a single Google Performance Max campaign.
- Driven by Google's machine learning (bidding, creative mix, channels), lead quality imported from the CRM.
- Cost per conversion -86% in Turkey, +1,261 leads at CPA -67% in the United Kingdom.
- Evidence B, status mixed signals.
Objective
Lower the cost per qualified lead and stop managing one campaign per format and per channel: a single campaign, driven by Google's AI.
The deployment
In Turkey, the Renault Mais team managed its lead-generation campaigns (test drives, dealer contacts) separately by format and by platform, with the agency OMD. It consolidated everything into a single Performance Max campaign. The principle: you upload the assets - videos, images, texts - and Google's algorithm continuously decides which creative to show, on which channel among Search, YouTube, Display, Discover, Maps, and Gmail, and at what bid. Creatives that do not convert are dropped automatically. Renault Mais reports a cost per conversion divided by almost seven, or -86%. The same pattern runs elsewhere in the group: in the United Kingdom, Renault Retail Group generated 1,261 more leads at a cost 67% below its target. Since then, Performance Max has become Google's default format for this kind of acquisition.
Results Proof B
Think with Google case study quantified with a named quote from a Renault Mais executive (platform bias), corroborated by an independent agency case study on another Renault entity (UK) - no confirmation in financial results.
How it works
Documented architectureThe stack in detail
- plateforme Google Ads Performance Max Single multi-channel campaign (Search, YouTube, Display, Discover, Maps, Gmail) driven by Google's ML: bidding, creative mix, allocation.
- outil Smart Bidding (Google) Automatic machine-learning bidding on a conversion objective.
- outil Google Analytics (GA4) + import de conversions offline Reporting of qualified leads from dealers into Google Ads, so the algorithm learns on real conversion.
- outil Salesforce CRM used by Renault Group to requalify leads and feed their quality back into Google.
- integrateur OMD Renault Mais (Turkey) media agency on the Performance Max consolidation.
How it runs, concretely
For ops teams-
1Define the real conversion Marketing team + dealer network
A lead is not a completed form: it is a contact the dealer judges actionable. It is this definition that you give Google, not the click.
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2Feed quality back from the CRM Data / CRM team
Leads that lead to a test drive or a quote are fed back into Google Ads (offline import). The algorithm then learns to seek the right profiles, not the curious.
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3Supply assets in volume Creative agency
Videos, images, and hooks in quantity, to give material to test. Too few assets and the algorithm keeps cycling the same combinations.
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4Frame EU compliance Data / legal team
In Europe, Consent Mode v2 is mandatory and the campaign remains a black box on placement detail. To be framed on the governance side before scaling.
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5Let it converge before judging Google AI
During learning, the CPA is unstable. Cutting or reworking at this stage means sabotaging the campaign.
The imported conversion. If you optimize on gross lead volume rather than leads actually qualified by dealers, the algorithm produces worthless contacts.
How your customers perceive this type of use
Sourced studiesLe pricing algorithmique est le terrain le plus inflammable : 68% des consommateurs disent se sentir leses quand les marques utilisent le pricing dynamique et 80% jugent plus dignes de confiance les marques aux prix constants (Gartner, 2024). L'equite percue varie selon le secteur : le pricing dynamique n'est juge juste que par 33% a 40% des repondants selon qu'il s'agit de concerts ou de cinemas (YouGov, 17 marches). Le prix personnalise par les donnees individuelles est le plus rejete : 47% des Americains s'y opposent fermement (Consumer Reports, 2024).
Acceptance conditions
- La constance des prix comme signal de confiance : 80% jugent plus fiables les marques aux prix stables (Gartner 2024)
- Le secteur conditionne l'equite percue : le pricing dynamique est mieux tolere pour les cinemas (40% le jugent juste) que pour les concerts (33%) (YouGov 2024)
Red lines
- Le pricing dynamique percu comme abus : 68% se sentent leses (Gartner 2024)
- Le prix individualise a partir des donnees personnelles : 47% d'opposition ferme (Consumer Reports 2024)
- Les frais caches et hausses imprevues, vecus par 79% des consommateurs sur un an et associes a la perte de confiance (Gartner 2024)
Sources: Gartner 2024 · YouGov 2024 · Consumer Reports 2024
How to replicate
Inference, not sourcedData prerequisites
- Reliable conversion tracking (qualified leads, not gross)
- Consent Mode v2 in the EU
- Differentiated conversion values (lead scoring)
Org prerequisites
- Video/image/text creative assets in volume
- Import of lead quality from the CRM
Possible stack
- Google Ads Performance Max + GA4 + offline conversion import (CRM / Salesforce)
The plan, step by step
- Step 1Define the real conversion (a lead judged actionable by the dealer, not the form) and connect GA4 + offline conversion import from the CRM.Deliverable: Reliable imported conversion in Google Ads.
- Step 2Produce the assets in volume (videos, images, hooks) and build the asset groups.Deliverable: Complete asset groups ready to deliver.
- Step 3Launch Performance Max as an official experiment against the existing campaigns, on a single conversion objective. In the EU, verify Consent Mode v2 before launch.Deliverable: Structured test in delivery.
- Step 4Let the learning phase pass (4 to 6 weeks) without cutting or reworking.Deliverable: Converged campaign with a stabilized CPA.
- Step 5Read cost per conversion and volume vs historical campaigns, arbitrate the consolidation, and set the governance (placement transparency).Deliverable: Documented consolidation decision and management rules.
First step: Official Google Ads experiment 'PMax vs existing campaigns' on a single conversion objective, with import of lead quality from the CRM before any scaling.
The same pattern, proven in other industries
adidas
AI-driven audience prospecting and bidding (ARO) across the full funnel
Allwyn
AI-driven omnichannel programmatic buying with retail data activation
Nivea
genAI testing and optimization of creative elements + automated localization at scale
Sources
- S1 Performance Max is the future of marketing - cas Renault Turquie (Renault Mais) Interested party archive pending
- S2 ClickThrough reduce Renault Retail Group's CPA by 67% with Performance Max Interested party archive pending
- S3 Groupe Renault boosts sales and reduces cost per lead with Google and Salesforce Interested party archive pending
An error, newer info, a source?
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