The specialist AEO and GEO agency, with our own AI search monitoring platform.
Focus vertical — Automotive.
We track how ChatGPT, Claude, Gemini and other LLMs describe your cars, dealership or platform, diagnose what is holding you back, then execute the answer engine optimisation work end to end. Built on AI monitoring tool we developed in-house and configure around your brand, model line-up, competitors and buyer segments.
Car buyers now build their shortlists inside ChatGPT and Claude before they ever visit a dealership or open a marketplace.
Answer engine optimization and generative engine optimisation are the layer where those consideration sets get formed, and it is the layer where most automotive brands, dealers and used car platforms have no presence, no data and no plan in place.
You rank on Google but you do not exist in AI search.
Search rankings and AI visibility run on entirely different signals, and ranking well on Google gives you almost no head start in AI search. Language models do not read search results pages. They draw on their training data, on third-party citations and on how clearly your models, services and inventory are described across the web, which means you can hold page one on Google and still be completely absent from ChatGPT, Claude and Gemini responses.
AI compares you to the wrong competitors.
You do appear in answers, just grouped with cars or platforms you would never describe as competitors. The class and segment signals you give off across your site and external sources are weak or contradictory, so language models default to placing you in the wrong comparison set. That happens at the exact moment a buyer is deciding which models to evaluate, test-drive or shortlist, which is arguably more damaging than not appearing at all.
Your vehicles get described inaccurately.
AI models describe your specs, trims and features based on what they have learned, and what they have learned may be outdated, incomplete or wrong. Fuel economy gets misquoted or battery range gets confused between trims. All of this is shaping how buyers perceive your cars before they have walked into a showroom.
Your visibility swings between queries.
You show up in some AI responses and are not present in others, even for near-identical prompts. Your brand signal is too inconsistent for AI systems to include you with confidence, so two buyers who phrase the same question slightly differently end up with two completely different shortlists, and yours often only makes one of them.
The signals that decide whether AI recommends you.
Automotive has a particular set of signals that drive visibility in AI search and the accuracy of how AI describes you. These are the six we track, diagnose and improve through our monitoring platform.
01
Competitive set accuracy.
Which cars or platforms is AI grouping you with, and are they the competitors that actually matter in your class? When the grouping is wrong, you are being evaluated against the wrong rivals and very likely losing to alternatives a buyer would never have considered if they had asked the right question.
02
Class / segment positioning.
Does AI understand which class your models belong to? Automotive segments overlap constantly: crossover vs SUV, compact vs subcompact, premium vs mainstream. When AI cannot confidently place you, they tend to leave you out. A clear, consistent segment signal is the foundation.
03
Technical spec accuracy.
Are your engines, fuel economy, battery range and equipment described correctly across AI responses, or is something getting lost in translation? Inaccurate specs create friction during consideration and erode trust before a buyer ever requests a test drive or quote.
04
Use case and scenario fit.
Do AI responses connect your cars to the use cases that actually convert? Presence in "best car for X" answers, where X matches family use, commuting, off-road or city driving, is the point at which AI search starts feeding showroom traffic rather than vanity impressions.
05
Price and trim attribution.
Are you being recommended with the right price band, trim level and market? Buyers ask AI very different questions depending on budget, region and currency, so when AI puts you in the wrong bracket, your AI presence ends up attracting leads your sales team cannot close.
06
SoV versus key rivals.
How often do you appear against the three to five competitors who matter most in your class? Share of Voice in AI search is the most direct read on how likely you are to be recommended, and it tends to be a leading indicator of showroom and platform traffic a quarter or two ahead of the funnel.
A monitoring platform that is built around your automotive category. We do not offer just a generic template.
We built our own AEO monitoring platform in-house, and we configure it around your brand, model line-up, competitive set, positioning and the queries your buyers actually run. The competitors we track are the ones you actually compete with, and the metrics we surface map to how AI search visibility translates into showroom traffic and platform leads in your specific segment.
We are a full-cycle agency, which means we do not hand over a dashboard and walk away. We analyse, we diagnose, we build the roadmap and we execute, either alongside your team or as a fully outsourced function.
Custom prompt library.
Tell us the models, segments or locations you want to monitor, generate prompts automatically and pick the ones that fit, or upload your own. You get a fully configured AEO monitoring dashboard built around the segments that matter to your business, not a default one.
Configurable Niche metrics.
Mention Rate, Share of Voice, Average Rank, Competitive Set Accuracy, GEO Score and several others, all weighted and reported against the goals you actually care about. The dashboard is customisable from the ground up, so the view your team logs into reflects how your business measures success.
Adjustable competitor lists.
Nobody knows your real competitor set better than you do, and AI knows even less than that. You can adjust the brands, models or platforms you want to monitor and benchmark against at any time, on your terms and at the cadence that suits your sales cycle.
Full setup support by our team.
As a full-cycle AEO and GEO agency, we are involved from step zero. We set the tool up, tailor it to your category and buyer segments, and guide you through prioritising the GEO initiatives that will move the needle first. Execution can run with you, with us or with a blend of both, depending on your setup.
Execute with your team or with our support, depending on your internal capabilities.
We adapt monitoring and AEO implementation to your category, internal metrics, and workflows.
We adapt monitoring and implementation to your category, your internal metrics and the workflows your team already uses. Strategy, execution and our in-house monitoring platform run as one engagement, so the work shows up in AI search visibility you can actually measure.
4 STEPS
AEO monitoring,
Monitor AEO – if & how you appear in AI search:
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mention rate,
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share of voice,
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brand attribute signals,
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topic coverage matrix,
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brand & source co-occurrence,
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your brand GEO score & dynamics,
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& any other tailored criteria.
Learn how AI systems describe:
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your models & pricing perception,
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reliability and ownership cost,
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safety and technology,
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comfort & driving experience,
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buyer fit,
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& not limited to.
1
GEO readiness,
Analyse your GEO readiness:
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own resources programming layer,
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own resources content layer,
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third party presence,
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citations.
Check competitor visibility:
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who gets recommended,
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in what contexts,
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with which attributes,
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how positioning changes over time.
Understand which sources influence AI outputs:
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review platforms,
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automotive media,
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spec databases,
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forums, Reddit, YouTube,
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owner communities, etc.
2
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quick-win identification,
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authority signal prioritization,
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content & documentation recommendations,
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external visibility opportunities,
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phased execution framework,
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our team support,
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dynamics tracking.
Get a 90-Day GEO Roadmap.
3
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website & semantic structure recommendations,
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model and inventory pages optimisation,
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spec sheets & owner manual optimisation,
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AI-oriented content strategy,
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content creation & placement automation,
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review platform visibility increase,
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external mentions & authority building,
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Reddit, YouTube & community presence,
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competitive positioning optimisation.
Enjoy Generative Engine Optimisation Support
4
What GEO fixes look like in practice.
These are the patterns that come up repeatedly across automotive engagements. The specifics shift from brand to brand, dealer to platform, but the mechanics behind the fix stay consistent.
"We appear in AI answers but we are grouped with cars we don't actually compete with."
Correcting the competitive set.
GEO Fix:
When class and segment signals are inconsistent across the brand website, external profiles and third-party automotive media, AI models draw from contradictory inputs and fall back on generic groupings. The fix involves aligning segment language across owned and external surfaces, building comparison pages targeting the right rival queries and updating automotive databases, review sites and Wikipedia entries to reinforce the correct positioning.
What to expect: competitive set accuracy improves as consistent segment signals replace the contradictory ones. With aligned language across owned and external sources, the shift typically becomes measurable within six to ten weeks.
"ChatGPT is describing our specs incorrectly and it's costing us in consideration."
Fixing technical and feature signals.
GEO Fix:
Thin, inconsistently structured spec pages rarely get cited by external sources, so AI models fill the gaps with outdated information inferred from older model years and review sites. The fix involves rebuilding spec documentation as citable, structured content blocks with FAQ schema, publishing trim comparison content and distributing the corrected information through trusted automotive media channels.
What to expect: spec descriptions in AI responses improve as the structured content gets indexed and picked up externally. Four to eight weeks is a typical window before the change becomes visible in monitored responses.
"We never appear when someone asks AI for a recommendation in our class."
Building class presence from 0.
GEO Fix:
Strong SEO performance does not automatically translate to AI presence. When brand signals are too thin or too scattered, language models cannot include a model in class-level shortlists with any confidence. The fix involves building class landing pages around consistent terminology, creating comparison and "best car for" content targeting high-intent prompts and expanding external authority through automotive publications, expert reviewers and owner platform updates.
What to expect: class-level presence builds incrementally as signals accumulate. Brands starting from near-zero visibility typically see measurable improvement in AI-generated shortlists within eight to twelve weeks of a coordinated push.
"Our visibility across ChatGPT and Claude swings wildly from one query to the next."
Stabilising multi-LLM visibility.
GEO Fix:
When different language models return different specs and different competitive sets for near-identical queries, the root cause is usually semantic inconsistency across the website, metadata and external mentions. The fix involves standardising terminology, improving internal linking between related models and trims and setting up continuous monitoring across ChatGPT, Claude and Gemini to track variations and respond to them as they emerge.
What to expect: stability improves as the underlying signals become more consistent across sources. Monitoring is essential here as without a baseline across multiple LLMs it is difficult to tell whether changes are having any effect.
Who we work with:
Our AEO and GEO work spans car manufacturers and global automotive brands, EV-native makers, premium and luxury marques, mainstream and budget brands, national and regional dealer groups, single-point dealerships, used car marketplaces and platforms, certified pre-owned programmes, auction platforms, car subscription and leasing services, fleet and B2B mobility providers, independent auto service chains, specialised repair workshops, tyre and parts retailers, automotive aftermarket brands and vertical marketplaces.
In marketing since 2009. In AI search since it became a category.
Our team has worked with international brands across SaaS, e-commerce, fintech and professional services for over fifteen years, originally as ContActive Tech Communications.
Today, that same senior team applies its strategic and technical expertise to answer engine optimisation, generative engine optimisation, and AI search visibility.