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AI SEO or GEO building ideas

Great thread, I'm playing catchup here. Gregg's buzzword takedown should be printed on a plaque and hung in every vendor office (my company included).

The ground floor comments are spot on. We're in here debating AI-ready VDPs and RAG pipelines while most dealers can't tell you if their NAP is consistent across 50 directories. The majority of the time I talk to dealers about SEO their GBP is not optimized, just claimed and abandoned like a New Year's gym membership. Local citations a mess. Core Web Vitals failing. Canonicals broken. Most aren't ready for "Make us show up in LLMs" and most don't want to stretch before a workout.

Once the basics are actually handled, content is where leverage lives. We use Hrizn with our clients. Best content OS in the space and I'm not being polite or pitchy. Their Dealer DNA components are the real deal. They're not generating another soulless Silverado blog post that reads like it was written by a chatbot with a thesaurus. They're building content tied to YOUR store, YOUR market, YOUR identity. With the March spam update live, every dealer running copy-paste content across 12 rooftops has gotta be rethinkin' their content strategy.

Where I'd really push this thread selfishly... the biggest problem in automotive isn't content or infrastructure. It's that every dealership's context lives in the GM's gut and gets distributed via vibes and monthly vendor phone calls (if they make them). 25+ SaaS platforms all operating in silos. Website vendor gets one story. Ad agency gets another. BDC is out there freelancing. We've been running on gut-distributed context for 30 years and calling it a digital strategy.

What could soon replace gut is a context or intelligence syndication layer. Capture what makes the dealership unique, update in real time, and push it everywhere. The dealers who win next won't be the ones with the most tools. They'll be the ones whose intelligence is actually organized and accessible instead of trapped in one person's head or gut. There are tons of providers building this layer into THEIR applications. To me, that's the same walled garden problem we've struggled with in this industry for the last 25 years. Every vendor wants to be the brain. Nobody wants to be the nervous system. Content, Ads, comms could all be leverage and operate harmoniously.

What's missing is a single context engine that syndicates intelligence out to every provider AND pulls the invisible stuff back in. Training data. Cross-platform comms. API usage and cost. Inventory. The operational signal that's actually driving output and nobody's monitoring because it's buried across 30 logins nobody opens. Who knows. This is moving so fast it's tough to keep up.
 
One thing I've done to adapt to 2026 SEO and LLMs is to consider each page (other than the SRP) as a Landing Page. Google's AI overview, in particular, right now just wants answers and so traffic may not necessarily come through the front door like it has in the past.

Knowing that we need to move away from basic 'templated' secondary pages that only focus on that content. Instead I'm including inventory on the "We Buy Cars" page because I don't know how they got there but maybe they haven't see the dealer's inventory yet. I see too many dealership pages where the finance page is just the dang credit app and NO TRUST factors shown. Or About Us is a boring generic paragraph with fill in the blanks for that one dealership. That's not good enough (never has been really)

This goes for VDPs as well. Someone mentions all car sites have the same exact data on them, that's true. So we are including additonal sections like "Why Buy From Us" content, the google map pack and dealership info, even Customer Testimonials, etc. A car buyer has more ways than ever to see your cars without visiting your website... so when they finally do land there the content on the page should sell them on the WHY US instead of assuming there is already trust there.

Lastly, building out more filtered inventory pages like "[body style] for sale in [city]" with relevant, relatable, local content and some FAQs instead of just a filtered list of vehicles. LLMs need REASONS to choose you...

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@Alex Snyder appreciate that.

Here's the plain-language version for any dealer reading this thread: The core problem: Your DMS has all the data. Your website has all the inventory. But when a shopper asks ChatGPT or Perplexity "find me a family SUV under $35k near me," most dealers simply don't appear — not because the inventory isn't there, but because the pipeline between the data and the AI is broken.

Three reasons that pipeline breaks:

Infrastructure — most dealer sites are too slow, too JavaScript-heavy, or actively blocking the new generation of AI crawlers. The AI never even sees the inventory.

Comprehension — even when the AI does crawl the page, it reads like a spec sheet built for a 2015 Google bot. The AI can't extract a confident answer from it, so it doesn't recommend it.

Trust — AI models cross-reference everything. A dealer with inconsistent information across their website, Google profile, and review sites gets filtered out before a recommendation fires.

What we've been mapping in this thread is essentially a three-layer spec for what an AI-ready dealership looks like in 2026 — and a controlled test to prove which layers actually move the needle.

The dealers who get this right in the next 12 months will have a significant first-mover advantage. The ones waiting for their website provider to solve it for them will be waiting a long time.
 

1. Machine Trust = Agree

  • Fast site
  • Clean HTML (no JS walls)
  • Proper schema
  • Real availability
Your correct: if that fails, nothing else matters!



2. Comprehension = Agree

  • Natural language
  • Real answers to real questions
  • Clear pricing
This is the most underrated layer in the industry right now.



3. Recommendation Confidence = Agree

  • Reviews
  • pricing clarity
  • next steps
However I would add AI doesn't just evaluate a single page on its own, it would look at consistency across pages, site-wide signals, entity-level trust, and even “Does the dealer look reliable across the web?”!

So those things would also need to be created for the test site.



I agree ...



Sadly you are correct and it is the most important part, it affects lawsuits, fines, conversions, rankings, and everything thing you do on your site. Since this is the most important part we will build it to meet and exceed all current specs, this way it doesn't affect any test.



Should we test to see if it affects:
  • discovery
  • ranking
  • selection across sources
Your addition to layer 3 is the right call and honestly it's the piece most people miss entirely.

A single VDP doesn't exist in isolation to an AI model. It's evaluating entity-level signals — does this dealer appear consistently across Google Business Profile, third-party review sites, social, and the open web? Do the NAP details match? Is the pricing consistent across surfaces? A perfect VDP on a dealer with weak entity signals still loses to a mediocre VDP on a dealer with strong off-page trust.

So the test site would need to be built with full entity coherence from day one — not just the page, but the entire web presence behind it.

On your three test dimensions — yes to all three, but I'd sequence them:

Discovery first. Does the unit even appear in an AI response at all? This is a binary pass/fail on layer 1 and entity trust. If you can't clear this bar, the other two don't matter.

Selection second. When the dealer does appear, does the AI recommend that specific unit or just the dealer generally? This is where layer 2 — the comprehension layer — does its work.

Ranking third. Across multiple sources surfacing the same inventory type, where does this dealer land? This is the hardest to isolate cleanly because it's influenced by everything simultaneously.

Running them in sequence also gives us a clean diagnostic — if a dealer fails at discovery, we know exactly which layer broke down and why.