“How can I see the search volume for ChatGPT queries?”
“How can I view the queries people are using on ChatGPT?”
At OtterlyAI, we’ve welcomed over 3,000 marketing professionals and SEO experts to our platform, and this is one of the most common questions we hear. Marketing teams are eager to evaluate how relevant certain search queries are on ChatGPT to determine how much priority they should give to optimizing for them.
This article aims to address all these questions.
There’s some good news – but also a few challenges.
Let’s begin with the basics.
Search Volume in SEO
For a long time, we as marketers have relied on search volume as a critical metric in our work. This data, which comes directly from Google, is a cornerstone of SEO tools like Semrush and others. It helps us assess the significance of specific search queries and determine how much attention they deserve.
When prioritizing keywords, we typically consider a combination of the following factors:
- Volume: How frequently is this query searched on Google?
- Competition: How challenging is it to rank for this query on Google?
- Topic-Audience-Product Fit: How well does this query align with what we offer to our target audience?
- Funnel Stage / Search Intent: Does this query target users at the top of the funnel or closer to the bottom?
If you’re an SEO professional or marketer, chances are good that you rely on tools like Google’s Keyword Planner, Semrush, Ahrefs, or similar platforms to incorporate search volume into your strategy.
Before diving into the topic of search volume in AI-powered search, I’d like to take a moment to discuss some of the inherent limitations of search volume as a metric.
What’s wrong about Search Volume: Some Limitations
Search Volume, while useful, has some significant limitations that should be considered when assessing its value for Google/Organic strategies. Below are a couple of key points to keep in mind:
(1) 15% of Daily Google Searches are brand new!
A notable 15% of all search queries on Google every day have never been searched before. This highlights the incredible variety and uniqueness of user behavior when it comes to online searches. (source)
Why does this matter?
Although the 15% figure was shared by Google back in 2017, it’s unlikely to have decreased—if anything, it has probably increased. With the rise of tools like ChatGPT and advancements in AI-driven search, user behavior is shifting to become more conversational, long-tail, and question-focused. These evolving trends suggest that the percentage of brand-new, never-before-seen searches is likely even higher today.
(2) Search Volume is an Estimated Number in the first place
It’s essential to emphasize that Search Volume is, first and foremost, an estimated figure. The numbers you encounter can vary significantly depending on the tool being used, and they may fluctuate over time. For instance, here’s a brief example using the United States as a market:
You get the picture. The numbers are quite similar, but don’t match 100%.
Why does it matter?
Several SEO tools, such as Ahrefs, openly state that their data is derived from Google’s Keyword Planner. It’s also worth noting that many of these tools use models based on clickstream data and other comparable sources, which can introduce some inaccuracies.
In summary, Google remains the most reliable source for this data, but it’s important to recognize its limitations. For long-tail keywords, in particular, Google’s estimates may not provide much value, as they often supply only broad budget ranges for these terms.
(3) It made us – marketers – complacent
I’d like to make another point here. Many marketing teams have leaned heavily on Search Volume as the primary factor for shaping their content strategies. While there’s nothing inherently wrong with using it as one of several criteria, many teams have overlooked another equally critical component: Search Intent.
Why is this important?
Does a specific “keyword” reflect a search intent that truly aligns with our business, our product, or the solutions we offer? For instance, compare “free CRM” with “best CRM for B2B” — the latter may have a lower search volume but signals a clearer intent and offers higher conversion potential.
Search Volume for AI Search
So, let’s go back to our introductory questions:
“How can I see the search volume for ChatGPT queries?”
“How can I see the queries people are using on ChatGPT?”
Let’s clarify a few key points:
- As of May 2025, none of the major AI search platforms (such as OpenAI, Perplexity, Claude, etc.) are providing data on search volumes.
- Tracking search volume at the individual keyword level isn’t particularly useful for AI-driven searches. Queries are now longer, more nuanced, and conversational. Instead, success should be measured at the intent level.
Here’s an illustration to put this into perspective:
Rather than searching for something like “Best CRM software,” a user might phrase their query as:
“I’m a B2B SaaS founder with a budget of X. My team consists of YY people, and our current tech stack includes A, B, and C. Can you suggest a CRM software that fits our needs? I’m specifically looking for features like D, E, and F.”
This shift is critical because it fundamentally alters how success on AI search platforms should be evaluated.
Such a query will never generate the same search volume as a generic term like “Best CRM for SaaS.” In fact, it’s likely to be entered only once. However, the quality of traffic generated from these highly specific searches will far exceed what we currently see even from bottom-of-funnel (BoFu) keywords.
The OtterlyAI solution: Relevancy Scores and Intent Volume
With consumer behavior shifting toward AI-driven search platforms, our mission is straightforward:
We aim to equip marketing teams with the tools they need to understand these changes and empower them to optimize their brands for emerging channels like ChatGPT, Perplexity, and others.
Recently, we introduced two new metrics to help marketing teams evaluate the significance of specific search queries: Relevancy Score and Intent Volume.
Relevancy Score for AI Keyword Research
Our AI Keyword Research tool was designed to help you pinpoint the most relevant search queries for your business. There are three practical ways to use it, which we’ve detailed in this dedicated article. However, one key question remained: How do you decide which queries to prioritize for your monitoring list?
To address this, we developed the Relevancy Score.
As the name implies, the Relevancy Score helps you prioritize search queries based on their relevance. It evaluates how closely these queries align with your brand, your website, and your industry.
Take a look at this example captured in the screenshot below. Here, I’ve been exploring relevant search queries for Gucci, a prominent luxury fashion brand:
Here’s another example, where I turned relevant keywords into search prompts. The AI Keyword Research tool gives me a great idea on what relevant queries I might want to start tracking.
Search Intent for ChatGPT, Perplexity
After conducting some initial research and starting to track a few search queries, we’re excited to introduce a new metric in the OtterlyAI Search Prompt Monitoring Overview: Search Intent.
Since platforms like OpenAI and other AI search tools do not provide data on search volume, we developed a model to estimate search intent. While still in its early stages, this metric shows great potential as a valuable resource for marketers.
Search Intent represents the estimated monthly intent volume for ChatGPT and Perplexity.
How does it work?
Our estimation is based on Google’s search volume data, which aggregates the number of monthly searches for specific terms or keywords. We combine this with additional data points to power the Otterly.AI algorithm. This algorithm predicts the monthly search intent for a given query across Google AI Overviews, ChatGPT, and PerplexityAI.
The calculation incorporates the ratio of each AI search engine’s monthly visit volume and their current growth trends. Using these factors, we derive the intent volume for all three AI search platforms.
Is it 100% accurate?
No, it’s not entirely accurate, but it provides a reliable estimate.
The calculation is based on the search volume of related keywords and the frequency of similar prompts used in AI-driven searches. While it’s not completely precise, it offers valuable insight into the number of people searching for a specific topic or question. This information can guide your decisions on how much effort to invest in your GEO (Generative Engines Optimization) strategies for that topic.
Why is it not called Search Volume?
To distinguish it from traditional SEO search volume metrics.
Search prompts are typically more conversational (and therefore longer) than standard keywords. Similar prompts often share the same user intent, even if worded differently.
As a result, the term “intent volume” is used to reflect the potential number of users searching for a similar question, topic, or intent. In some cases, longer prompts are simplified into a broader intent category, and the estimated intent volume is calculated based on this generalization.