For OEMs, EV brands, dealerships, and the aftermarket
Be the car AI recommends when buyers ask what to drive.
Buyers ask AI what's the best car for their need before they ever walk into a showroom. Your brand needs to be in that answer, by name, by model, by use case.
§01 Why AI search is reshaping automotive
The shopping conversation moved upstream of the dealership.
ChatGPT now serves more than 800 million weekly users, and a meaningful share of car-buying research starts inside answer engines before any dealer visit. The buyer asks for two or three models that fit a use case. Half the consideration set is decided in that conversation, often before the buyer ever types a brand name.
For automotive, the implication is sharp. Brand-direct marketing still matters for the buyer who has chosen a brand, but it does not reach the buyer who is still asking AI what to consider. The deciding source is the independent press, the owner-review aggregators, and the specialist publications by category. If your models are not inside that cited pool, the buyer never sees them.
The work is engineering the source pool AI reads, getting your specific models cited inside that pool with consistent positioning, and managing the surfaces (dealer entities, local listings, owner reviews) that feed down-funnel queries.
§02 What we do for automotive brands
Five lines of work, run weekly, owned by us.
We sit alongside your in-house marketing, brand, and dealer-network functions. Brand campaigns, model launches, and dealer enablement stay with you. The AI visibility layer is our remit, delivered on a fixed weekly cadence.
01
Model-comparison prompt work
Buyers ask AI to compare specific models head to head: a Model Y against a Mach-E, an Ioniq 5 against an EV6, a Civic against a Corolla. We engineer the comparison content, third-party validation, and review citations that decide which model wins in the answer pool.
02
Best car for use-case citation surfacing
Most consumer auto research starts with a job-to-be-done query: best car for a growing family, best EV for road trips, best truck for towing a boat. The answer pool for each use case has its own logic. We map the use-case prompts that matter for your nameplates and engineer presence in the answers.
03
EV-category positioning across answer engines
EV queries weigh differently than internal-combustion queries. Range, charging network access, software updates, and battery warranties carry more citation weight. For EV-focused brands, we run the source-pool work that gets specific models cited inside the EV answer pool, not the broader auto pool.
04
Dealer-locator and local AI integration
AI surfaces are increasingly answering local queries: dealer near me, certified pre-owned in this city, service centre with EV charging. We work the local entity surfaces (Google Business, dealer directories, regional review sites) that feed those answers so the dealer network gets surfaced when the buyer is ready to act.
05
Owner-review source pool work
Owner reviews on third-party sites carry disproportionate weight in AI car-recommendation answers. We monitor sentiment in the surfaces AI cites for your nameplates, surface the review themes being pulled into answers, and run the response work to keep the source pool honest.
§03 The outcomes we commit to
Named results, written into the engagement letter.
We deliver results, not dashboards. The pilot pricing is built around it. You pay €500 per month for tools and APIs plus your direct media spend. We carry the team. At the end of the 90-day pilot, if we hit the goal we agreed on day one, the engagement converts on a €6,000 success fee and a €2,500 per month retainer thereafter. If we miss, you walk. No further obligation.
Model recommendation rate on use-case prompts
The metric that drives top-of-funnel demand. We commit to a measurable lift in the rate at which AI names your specific models on the use-case prompts you choose to target.
Comparison-query citation share
For head-to-head queries between named models, the deliverable is documented citation share lift on the comparison prompts where your nameplates compete.
EV-category source pool position
For EV-focused brands, the deliverable is inclusion in the cited source pool that AI draws from on EV-specific queries: range, charging, software, total cost of ownership.
Dealer-network local entity health
For brands with dealer networks, the deliverable is consistent local entity surfaces feeding the dealer-locator queries AI now answers directly.
§04 Who this is for
Brand and digital leaders at OEMs, EV brands, dealer groups, and aftermarket businesses.
The typical engagement is a CMO, Head of Digital, or VP Brand at an OEM, a fast-growing EV brand, a multi-rooftop dealer group, or a category-defining aftermarket business. Traditional automotive marketing channels are still running. The new question is whether any of that activity is reaching the buyer who is now starting the journey in a chat surface.
You usually come to us because of one of three triggers. A model launch underperformed in the press review pool and the brand team can see it in AI answers. A competitor with worse traditional metrics keeps appearing in AI recommendation answers and the team cannot explain why. Or the brand is launching into a new geography or category and needs to be inside the AI answer pool from day one.
§05 How we work
One framework, applied weekly. The methodology is public.
The work runs on the CITE framework. We comprehend the prompt set, influence the source pool, track citation and recommendation movement on a weekly cadence, and evolve the program as platforms shift. The research underneath is published openly.
§06 FAQ
The questions automotive buyers ask before they engage.
How does AI decide which cars to recommend?
Does my OEM marketing flow into AI answers?
Why do AI answers favour certain brands?
Do owner reviews on third-party sites still matter?
How do I show up for new model launches?
Ready to become the answer AI gives?
Book a 30-minute discovery call. We'll show you what AI says about your brand today. No pitch. Just data.