A customer in your market just asked ChatGPT:

'Who is the best John Deere dealer near me?' Did your dealership get recommended?

 

Most dealers don't know the answer to that question. And that's exactly the problem.

AI isn't just a search tool anymore. Tools like ChatGPT, Perplexity, and Google AI Overviews are increasingly making direct dealer recommendations — and the dealers that often appear aren't always the ones with the best websites or the biggest ad budgets. They tend to be the ones with the strongest, most consistent customer experience signals online.

The good news: you can see where you stand right now. These five prompts take less than 20 minutes and will show you what AI appears to be saying about your dealership, how you compare to competitors, and where the gaps are.

 

SATISFYD BENCHMARK

Across SATISFYD benchmark data, the average equipment dealer generates just 2 reviews per month per location. At that pace, AI has relatively little public evidence to draw from — and limited signals often lead to less specific recommendations.

 

Before You Start — A Few Important Notes

AI platforms like ChatGPT, Perplexity, and Google AI Overviews often return different answers to the same query. That's expected — they pull from different sources and update at different frequencies. Don't look for one correct answer. Look for patterns across platforms. Where you consistently appear, or consistently don't appear, is where the signal is.

  • Run each prompt in at least two platforms: ChatGPT, Perplexity, and Google AI Overviews give different answers — that's the point.
  • Use incognito mode so your search history doesn't skew the results.
  • Screenshot every output and save it with today's date. This is your baseline.
  • Run the same prompts again in 60–90 days to track how your visibility is changing.

Prompt 1 — Your Baseline: What Is AI Saying About You Right Now?

Run this one first. Before you look at competitors or dig into specifics, you need to know what AI appears to be saying about your dealership — in plain language, with sources cited.

 

THE PROMPT

I'm researching [Dealership Name], a [John Deere / Cat / Case / etc.] equipment dealer in [city/region]. In 200 words or less, tell me: what are customers saying this dealership is known for, how does it compare to its top competitors, and would you recommend it for [parts / service / equipment purchase]? Cite your sources.

 

WHAT TO LOOK FOR:

Is the description specific or generic? If AI describes you as 'a reputable dealer with good service,' that may indicate the customer experience signals AI can find aren't specific enough for it to say anything meaningful about you.

Compare how AI describes your competitors. If they get more specific language — 'praised for same-day service on compact utility tractors' versus 'generally well-regarded' — that tells you exactly what kind of customer feedback you need more of.

Look at the sources AI cites. If it's pulling from third-party review sites but not your own website, your first-party review content may not be reaching where AI looks.

WHAT IT MEANS FOR DEALERS:

The specificity of what AI says about you tends to reflect the specificity of your reviews and customer feedback. 'Great service' gives AI relatively little to work with. 'Fixed our Cat 320 hydraulics in 48 hours' provides the kind of digital reputation signal that AI can cite when recommending you.

Prompt 2 — Category Visibility: Do You Show Up When Customers Don't Know Your Name?

Most customers searching AI aren't typing your dealership's name. They're describing what they need. This prompt shows you whether you appear at the moment of highest intent — before a prospect has a preference.

 

THE PROMPT

I need [John Deere tractor service / excavator repair / compact utility tractor] in [city]. Recommend the top 3 dealers. For each one, tell me what customers say about them and what they're specifically known for. Does [Dealership Name] appear in your top 3? If not, what would need to be true about their review presence to be included?

 

WHAT TO LOOK FOR:

Pay close attention to the last part of this prompt. The question about what would need to be true about your review presence is among the most actionable things you can ask AI directly — it's essentially asking the model to tell you what's missing.

"What would need to be true about their review presence to be included?" — This is the most valuable question in the article. Highlight the answer and act on it.

 

Note the exact phrases AI uses for dealers that do appear. Those phrases tend to come from review text and customer feedback. If competitors are described as 'recommended by contractors for Cat service' and you're not, that's a specific gap to address.

WHY THIS MATTERS:

Only 1.2% of business locations appear to get recommended by ChatGPT, compared to 35.9% that appear in Google's local 3-pack. Category-based visibility is where many dealers are currently invisible.

(SOCi 2026 Local Visibility Index, 350,000+ locations)

 

Prompt 3 — Competitive Comparison: How Do You Stack Up?

This prompt puts you alongside your top competitors and shows you how AI appears to be differentiating between you — and why.

 

THE PROMPT

Compare [Dealership Name] to [Competitor 1] and [Competitor 2] in [region] based on customer reviews and online reputation signals. What does each dealership appear to be known for? Which would you recommend for [service department / parts availability / equipment purchase] and why? Cite your sources.

 

WHAT TO LOOK FOR:

If competitors get recommended over you for a specific use case, look closely at what AI says about them. The language it uses tends to come directly from their customer feedback and review content — that's your roadmap.

If you appear but with less specific language than a competitor, the gap may not be your rating — it may be the depth and specificity of your customer experience signals. A dealer with a 4.3 and 200 detailed reviews may surface more reliably than a dealer with a 4.8 and 40 generic ones.

Prompt 4 — Multi-Location Check: Are All Your Locations Showing Up?

Dealers with multiple locations often have uneven digital reputation coverage. One store tends to drive the brand's AI presence while others are nearly invisible. This prompt surfaces that gap quickly.

 

THE PROMPT

I'm looking at [Dealership Name] which has locations in [list cities]. For each location, how would you describe the reputation based on available customer reviews and digital signals? Are there significant differences between locations? Which location would you recommend for [specific use case] and why? Cite your sources.

 

WHAT TO LOOK FOR:

When AI gives a location-specific, detailed description, that location has built strong AI representation through consistent customer feedback. A brand-level description ('generally well-regarded in the region') often means that location doesn't have enough distinct review content to stand on its own.

If AI explicitly says it can't find enough information about a location, treat that as near-zero visibility for that store.

Prompt 5 — Monthly Monitor: Is What You're Doing Working?

Run this prompt every 30 days. Save the output each time. AI models don't update in real time — changes in your digital reputation signals take 60–90 days to show up in AI responses. This prompt gives you a consistent benchmark to measure that movement.

 

THE PROMPT

Today is [date]. How would you currently describe [Dealership Name]'s reputation based on available customer reviews and online signals? What are the three most prominent themes in customer feedback right now? On a scale of 1–10, how confident are you in your description — and what's limiting your confidence? Cite your sources.

 

WHAT TO LOOK FOR:

The confidence score is worth tracking month over month, but treat it as directional rather than scientific — different AI platforms evaluate confidence differently and the scores aren't standardized. What matters is the trend and what AI says is limiting its confidence.

A score below 7 often comes with an explanation: thin review coverage, outdated content, or customer feedback that isn't specific enough to cite. That explanation is your action item.

Watch for competitors appearing in the comparison who weren't there last month. A competitor increasing their customer experience signals faster than you will start edging into AI recommendations in your market.

What to Do With What You Find

Most dealers running these prompts for the first time will find one of three patterns. Here's how to read them and what to do next.

Pattern

What It Means

Next Step

Showing up — but described generically

Customer experience signals exist, but aren't specific enough for AI to form a detailed picture of what your dealership is known for.

One effective way to address this is coaching customers to mention specifics — the equipment type, department, what problem was solved, what made the experience stand out.

Some locations show up — others don't

Digital reputation coverage is uneven. One location drives AI presence while others have insufficient customer feedback signals to register.

One effective way to address this is building a systematic review ask strategy at the underperforming locations — post-service, post-purchase, post-repair.

Competitors show up — you don't

This is typically a combination of both patterns. AI has more customer experience signal to draw from for competitors than it does for you.

One effective way to address this is a consistent, long-term approach to collecting specific, recent customer feedback — the kind AI can actually read and cite.

 

AI isn't creating a new story about your dealership. It's interpreting the one that's already out there. The question is whether you're shaping it.

 

See Where Your Dealership Stands 

Not sure where to start? Run your free Reputation Scorecard. It takes a few minutes and gives you an instant baseline on your review volume, recency, ratings, and sentiment — the customer experience signals that appear to influence whether AI recommends you or a competitor.

Want to go deeper? We'll run the prompts together on your dealership, show you exactly what AI is saying about you right now, and identify where to focus first. Schedule a time here. 

Emilie Spalla
Post by Emilie Spalla
Aug 7, 2026, 3:54:39 PM
Emilie Spalla, Vice President at SATISFYD, has over 15 years of client relations experience in the manufacturing, agriculture, and construction industries. At SATISFYD, Emilie has created a customer-first environment, leading teams that deliver high-quality solutions that exceed customer expectations. She has worked closely with both enterprise and dealer groups and is passionate about helping them create customer experience excellence strategies and programs. Emilie is excited to help businesses provide the very best experience for their customers. Emilie holds a Business Management and Economics degree from Hope College. She is an avid mountain biker and resides in Traverse City, Michigan with her husband and two daughters.

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