Same Search, Different Results? Why Google, ChatGPT, Claude, and Perplexity Deliver Different Answers

When it comes to news about search, let's get real: as a marketer, I've seen enough "search is changing" headlines to last a lifetime. (Yes, we're guilty too.)

That said… it's, well, true. More people are searching on AI platforms, and they're becoming more likely to trust the generated results AI shares. But most SEO conversations still focus on where people search or how they behave — not on how the answers actually change depending on the platform.

So, I ran a test.

I typed the same query into four different platforms: Google, ChatGPT, Perplexity, and Claude.

The results? Different platforms gave me completely different answers — even though I asked the exact same thing.

That's a huge shift from the "Google-only" era — one that makes a big difference for brands looking to understand how to show up consistently across various traditional and AI-driven search experiences.

Let's take a look at the search results, what makes them different, and how marketers can adapt.

(My blog post, my interests, okay?)

Let's go.

From Google, I got — you guessed it — a list of links and the "map pack" we all recognize.

Google suggested I click through to relevant sites like Reddit, Grubstreet, and The Infatuation. The Google Local 3-Packresults leaned on familiar SEO signals like proximity ("near me") and high star ratings (4+), driven by accurate NAP info and keywords like "best" in reviews.

Translation: This is the Google SEO we all know. Structured data + local relevance + authority still rules.

(If it matters to you, I can confirm that Martiny's is excellent.)

Louder for the people in the back: unlike Google, ChatGPT doesn't rank websites. ChatGPT skipped the links and served up a clean, conversational answer. No rankings, no crawling — just a direct recommendation, with some context and a mapped result.

As you can see, the introductory language is different… and so is the top result. (I do love Bemelmans, so good job to ChatGPT.)

Additionally, searchers are encouraged to ask follow up questions with "ask anything" — so they can go deeper on menu items, neighborhoods preferred, dress code policies, and much more.

That's the ChatGPT difference: It's not just about retrieving — it's about guiding the user experience.

Perplexity delivered another conversational, detailed, and interactive result — as you'd expect in AI-driven search. But the language was different, and so was the top result.

What stood out? Citations. Perplexity linked directly to sources like reviews and publisher content to back up its response — something other models didn't do as much.

"Diverse sources ensure comprehensive coverage,"Perplexity told us in a previous blog. The platform really leans into that here.

Balthazar is an absolute classic of the genre, I'll give Perplexity that.

And for our last experiment this round… it looks like we've proved our title thesis: same search, different results. Claude kept it classy. The response was conversational, confident, and surprisingly formal.

What stood out? Claude's tone feels a little more curated than the others — like a polished concierge recommendation instead of a search engine result. It didn't show citations like Perplexity or offer follow-up prompts like ChatGPT, but the language was clean, and the answer felt purposeful.

Claude also added subtle context about ambiance and reputation, mentioning the venue's vibe and customer experience. That signals it's likely pulling from a combination of reviews, structured data, and editorial content — not just business listings.

I have to admit that I've never been to The Bar Room at The Regency Hotel – this speaks to AI's potential for discovery, not just convenience. Looks like I have new weekend plans!

That's four platforms, four different top picks — and not a single duplicate across the board. Same search. Very different results. Now what?

If you're a marketer, the first step is to not panic.

Sure, you might be thinking: wait, so I can't get a brand to show up near the top of the list everywhere? The answers and suggestions are all different, even for the exact same query?

But remember: this isn't all that different from what we've always dealt with in traditional SEO.

Google has never given us their full algorithm, either. But marketers found success by building smart, consistent, structured strategies — and the same thing works today, just adapted for AI.

Here's what marketers can do to help put their brand's best foot forward — even if no two answers sound exactly the same.

The first step to AI search success is to make sure your data is correct and consistent — so it's easy for AI to find, trust, and re-interpret. A tool like a knowledge graph is the best way to keep all your brand information clean, accurate, and up-to-date.

With a knowledge graph, you have the power to update once, in a central location, and automatically sync updates across platforms. To put it simply, organizing your information in a knowledge graph helps you "speak AI's language."

First, keep the reading level to grade 10 or below where possible. Then, remember that AI prioritizes content that can be understood through natural language processing (NLP). Writing the way that people talk — and answering their natural, conversational questions — is important.

For example, instead of focusing ranking for broad keywords like "hotel with pool" or "kid-friendly," write FAQs and blog posts that answer customers' specific questions:

• "What are the best family-friendly hotels near Central Park?"

• "Where can I bring my partner (and my kids) for a long weekend in the Catskills this summer?"

• "Is there a hotel or inn near Hudson, NY that has a fun pool or waterpark?"

Reviews and FAQs aren't just helpful for customers — they're gold for AI-driven search.

Monitor what customers are asking (like, "do you have a happy hour martini deal," perhaps?) and update your FAQs to address those topics. This kind of enhanced content gives AI tools access to specific, real-world, context-rich information. In turn, artificial intelligence can understand and pull from that information when generating answers to questions and prompts.

Related to the above: remember that AI models learn from reputable third-party sources.

• Try to earn mentions and links from trusted publications, forums (like Reddit or Quora), and local directories

• Build brand authority through thought leadership content, expert Q&As, or original research

This might sound like a lot to process. But it's all achievable — and you're probably already doing some of it through traditional SEO best practices.

Curious how AI search really works? Learn how platforms like ChatGPT, Gemini, and Perplexity choose what to show.

As for me? I'm going to optimize a few blog posts and then head out for some fries. See you out there, marketers.