Comparing Top Traffic Prompts vs Queries Across Different Page Types - Key Differences & Implications

Now that we have more tools providing access to prompts information like Similarweb or Profound from the major AI search platforms, and in particular, with Similarweb showcasing the top prompts bringing traffic per page we have the ability to compare them with the existing, most popular queries that bring most of the organic search traffic to the same pages from Google's traditional search results, and see the major differences and shift in behavior.

Going through a few scenarios of top (AI) prompts vs (traditional search) queries, as well as the pages receiving their traffic, we can clearly see the impact in:

• Giving visibility and traffic to whole pages in traditional vs chunks/passages within pages in AI search: In traditional search we target a whole page to rank for its relevant group of queries (variations of each other), with a specific and similar intent between them. In AI search, this changes completely, with LLMs using content chunks/passages within pages for their answers, many times citing/linking to pages that don't directly target what we would have considered to be the prompt's main term or topic.
• Ranking for a specific group of short, consistent, and similar queries with aligned intent per page in traditional search vs getting visibility from a wide variety of very long tail, conversational prompts across many intents and even languages per page with AI search. Some of these are also likely the outcome of what Google calls the query fan-out technique, which is the process of breaking down the initial query into subtopics and issuing a multitude of queries simultaneously when searching, enabling the AI search system to dive deeper for more comprehensive answers.
• The low level of personalization in traditional search results (making them easily replicable) vs the high personalization level in AI search answers (making them much harder to replicate and validate). Here's also important to note how the current level of AI search personalization, powered by user opt-In memory, explicit instructions and session context is only going to expand even more in the future, with additional integrations (and further personalization) already announced by Google at their I/O event.

Let's go through a few examples across different scenarios that show the above more clearly:

1. My personal site (aleydasolis.com) home page

Let's see the difference in traditional search top terms vs AI search prompts attracting traffic to my personal site home page in Spanish: https://www.aleydasolis.com/ (note how the English home page is located instead at: https://www.aleydasolis.com/en/, a different page).

The top terms attracting clicks from Google, as you can imagine, are queries variations related to my own name "Aleyda Solis", as well as "consultora SEO" (SEO consultant in Spanish, which is natural given this page is in Spanish).

Nonetheless, my Spanish home page top prompts are completely different, not only because they're very long tail, informational questions, but also their topics and even language:

• "What are the best practices for international SEO"
• "How can I optimize my e-commerce website for better search engine rankings"
• "Cuáles son las claves esenciales del SEO" (In Spanish: "what are the essential keys of SEO")
• "Can you recommend a comprehensive SEO learning roadmap"
• "What are the latest trends and tips in SEO"

Note how none of the prompts above are looking for my name or SEO consulting, which are the usual terms providing traffic to this page, but:

• Look for best practices in international or ecommerce SEO, services that I provide, and they cite me accordingly.
• Ask about the "essential keys in SEO" and they cite me since I have a book in Spanish about that topic.
• Ask about a comprehensive SEO learning roadmap, and they cite me because I've created learningseo.io, which is exactly that.
• Look for the latest trends and tips in SEO, for which they refer to me again as I cover them through my SEO news newsletter SEOFOMO, the SEOFOMO News aggregator hub, and via my social shares over here.

So all in all, these are very relevant prompts to refer me, although I wouldn't have chosen the page in Spanish, but English for those prompts in this language, and would have better linked the pages of the resources they refer me for in particular, rather than my home page, but is my Spanish home page where they have gotten that information from and/or also see as more relevant to refer as is the "home" of my entity, most of the links referring to my name are pointing to it, the structured data in it, etc.

It's also important to note, how if you search on Google traditional search for the prompts for which my site is referred AI search results, you won't see it ranking in top positions or ... at all. It's mostly guides, in some of them referring to my resources, or in some scenarios, my resources (SEOFOMO, LearningSEO.io) ranking directly.

2. An informational blog post

We can see something similar in the differences between the top prompts and queries referring traffic to my 5 AI Insights from Google Search Central Live in Madrid on April 9, 2025 post.

The top terms referring organic search traffic from Google are related to the event's name "search central live madrid" and variations of it.

However, the top prompts referring traffic are mostly broader, not even asking about the Google event in Madrid, but about the topics I covered from what Google shared in the event in Madrid, using the post as a reference (and endorsing it from the answers):

• "How does Google handle AI generated content in search rankings?"
• "¿Cómo funcionan las búsquedas con IA y las vistas generales de IA en Google?"
• "What strategies can be used to monitor and track AI Overviews and Gemini searches?"
• "¿Cuál es el futuro del SEO con la integración de modelos de lenguaje de gran tamaño (LLMs)?"

Did I write this blog post thinking I would ever get any traffic from people looking for the topics above? No, at least not as a primary target:

• I thought it would be mostly visited by those looking for the AI insights shared in the Google Search Central Live event, since this was the broader topic the page targeted.
• There were many other pages focused on targeting those other AI Google queries above as their main topic, rather than mine.

In fact, if you check Google's traditional SERPs for those prompts above, you won't see my blog post ranking for them.

However, my post was definitely a relevant source of information for them, and definitely relevant to refer to since I covered the answers to these questions through the content.

3. A more commercially focused blog post

What happens for more commercially focused blog posts? Let's see with The 10 Best Running Shoes for Flat Feet guide from Runner's World.

Since I have no affiliation with the site, I've checked the top terms driving traffic from Google's organic search results from Ahrefs: "best running shoes for flat feet", "running shoes for flat feet" and other similar queries variations are among the top from all over the world, in English (since the guide is in this language) as we would expect from a "query to page matching" system.

In the case of the top prompts, although we can see a few similar long-tail, conversational versions of the top terms like: "what are the best running shoes for flat feet" or "I'm looking for running shoes that provide good arch support for flat feet. Any suggestions", we also have different ones, asking for sub-topics covered through the guide in English without mentioning "flat feet", as well as the same flat feet topic but in Spanish:

• "Can you recommend running shoes suitable for overpronation?"
• "Which running shoes are best for runners with low arches?"
• "Cuáles son las mejores zapatillas para correr para pies planos" (In Spanish: Which are the best sneakers to run with flat feet)

Despite the "longer, conversational" style in this case though, there's a higher overlap with Google's traditional search results, with the same article ranking in the top position for "Which running shoes are best for runners with low arches?" in Google.

4. A Product Page of a major retailer

And what happens with ecommerce product pages?

Usually PDPs will rank for the specific product name for which they're very specifically relevant, which happens in this case with the Amazon product page: Anker 555 USB-C Hub (8-in-1), with 100W Power Delivery, 4K 60Hz HDMI Port, 10Gbps USB C and 2 A Data Ports, Ethernet microSD SD Card Reader, for MacBook Pro More, as we can see in the Ahrefs screenshot, with the top queries being: "anker 555", "anker 555 usb-c hub" and related queries for the specific product names.

I found the top prompts for product pages to be particularly interesting, since unlike the top traditional queries, these are very long, descriptive prompts, asking about the characteristics of the product but none mentioning the product name, with prompts in different languages, as happens in this case with Spanish and French along with English ones:

• "What is a reliable USB-C hub with Ethernet and HDMI ports for my MacBook Pro?"
• "Can you recommend a USB-C hub that supports 100W Power Delivery and 4K HDMI output?"
• "I'm looking for a USB-C hub with multiple data ports and SD card readers for my laptop. Any suggestions?"
• "Cuál es un concentrador USB-C confiable con puertos Ethernet y HDMI para mi MacBook pro?" (In Spanish: "Which is a trusted USB-C concentrator with Ethernet and HDMI ports for my MacBook pro")
• "Pouvez-vous recommander un hub USB-C prenant en charge la livraison d'énergie de 100 W et la sortie HDMI 4K?" (In French: "Can you recommend a USB-C hub that supports 100W power delivery and 4K HDMI output?")

However, when searching for these non-branded, very long-tail prompts in English in Google traditional search, in most of the top results this or another similar Amazon PDP is ranking as well, along with guides and UGC.

5. A Category Page of a major retailer

Finally, let's see what happens with a category page of a major retailer, like the Men's Polo Shirts of American Eagle, which gets most of its organic search traffic from traditional search results from branded "american eagle polo" and "american eagle polo shirts" related queries, but also some non-branded ones like "collar polo shirt", or "men polo shirts". These are usually relatively short, descriptive, matching the overall offering of the page: polo shirts for men.

The top prompts in this case are again in a variety of languages (English, Spanish, Portuguese), longer tail and non-branded:

• "Where can I find stylish men's polo shirts?"
• "What are some comfortable polo shirts for men?"
• "¿Dónde puedo encontrar polos de hombre a la moda?" (In Spanish: "Where can I find stylish men's polo shirts?")
• "Quais sao algumas camisas polo confortaveis para homens" (In Portuguese: "What are some comfortable polo shirts for men?")
• "Where can I buy men's pique polo shirts?"

Although many category pages are ranked in Google for these long tail conversational prompts (along with some informational ones and PDPs via product carousels), the American Eagle one wasn't in the top one in this case.

Through these top prompts vs queries examples across different scenarios, we can see the changes between a few AI and traditional search areas, highlighting the shifts in:

• Optimization Target: Overall Pages content vs Content chunks / passages
• Retrieval style: Single-query match with pages vs Query fan-out and content synthesis
• Search behavior: Long-tail, conversational queries vs shorter keywords
• Personalization level: Basic vs deeper, multi-layered answer customization

Although there’s a high overlap in principles for optimizing for AI vs traditional search, there are certainly differences due to the shifts above.

How to move forward?

I’ve created an AI Search Content Optimization Checklist, going through the most important aspects to take into account to optimize your content for AI search answers -from chunk optimization, citation worthiness, topical breadth and depth, personalization, etc.-, along with their importance and how to take action.