Semrush Prompt Research vs Profound Prompt Volumes for Finding Real Buyer Questions

How do they compare?

How does Semrush Prompt Research find buyer questions?

Semrush's help pages describe the Prompt Research report as keyword research for AI. You enter a topic or product category and get:

• Related Topics AI Volume: estimated monthly AI search activity around the related topics.
• Prompts: hundreds of real-language prompts, showing how people phrase questions and pain points.
• Intent analysis: whether people want to learn, compare or buy.
• Brands and source domains: which brands AI answers mention, and which sites they cite.
• Topic difficulty: how hard it is to break in, based on how established the cited brands are and how many positions are available.

Semrush explains that individual prompts are too specific to measure directly, so it estimates volume at topic level, combining third-party data on real AI interactions with its own models. That makes the numbers more stable, but it means you are sizing a topic, not a sentence.

Profound Conversation Explorer review for AI citation research

Conversation Explorer was Profound's name for its tool to explore what users actually ask AI; the capability now sits in Prompt Volumes. For citation research, it works as the front end of a two-step process:

1. Find the conversations that matter. Search a keyword, see its volume, trend, related sub-topics and the audiences asking, filtered by platform, age range or income bracket.
2. Track the answers. Add the chosen prompts to Profound's answer tracking, which records which brands are named and which sources are cited, daily across its supported engines.

The value for citation research is choosing prompts from real demand rather than guesswork, so the sources you work on are the ones behind questions people actually ask. We have not run a hands-on test of Profound's panel data against other sources, so treat its volumes, like any panel estimate, as directional.

Profound Prompt Volumes review: how Conversation Intent helps plan content

In October 2025 Profound added Conversation Intent to Prompt Volumes. For every tracked keyword, it shows the share of conversations in each of four intents:

• Commercial: researching, evaluating, buying or using products and services, across the whole funnel.
• Informational: learning or finding facts without purchase intent.
• Generative: asking AI to create something, such as a plan, a draft or an image.
• Conversational or other: everything else.

Unlike traditional keyword intent, it classifies whole conversations rather than single queries, merges commercial and transactional intent, and adds the generative category that search tools never needed. For content planning, that tells you what kind of page to build:

Which formats tend to be cited for each intent is covered in which content formats get cited most often by AI.

What are the caveats with both?

• Samples, not censuses. Clickstream and panel data each come from particular groups of users, which may differ from your buyers, especially in B2B or niche markets.
• Different units. Semrush's topic volumes and Profound's keyword volumes are not directly comparable; do not mix them in one report.
• Changing scale claims. Profound's stated dataset size has grown quickly, and public descriptions do not always make the scope clear. Ask what period and population the numbers cover.
• Real questions still come from customers. Neither tool knows what your sales team hears every week.

Whether trackers rely on synthetic prompts is covered in whether GEO visibility tools use synthetic prompts instead of real buyer questions, and a free approach in how to use keyword research and topic volume to estimate AI prompt demand.

How should you validate either tool?

1. Collect your own questions: sales call notes, support tickets, site search terms and Search Console queries phrased as questions.
2. Compare topics: check whether the tool's high-volume topics match the themes in your own list.
3. Look for gaps both ways: topics the tool shows that your customers never raise, and customer questions the tool misses.
4. Test a sample: run ten prompts from each source in two assistants and see which produce answers relevant to your business.
5. Choose a blended list: high-volume topics from the tool, phrased in your customers' words.

Which should you choose?

• Semrush Prompt Research if you want affordable, self-serve prompt and topic research alongside SEO data, with brands and cited domains for each topic.
• Profound Prompt Volumes if you are on Profound already, or need keyword-level volumes, audience filters and conversation-level intent for a large content programme.
• Neither alone if your market is niche; your own customer questions will matter more.

What might this look like in practice?

Consider an illustrative project management software company, Wembstead. Semrush showed that "project management for agencies" was a high-volume topic, with mostly commercial intent, and listed the review sites AI answers cited. A Profound demo showed a large share of generative conversations around "project plan template for client onboarding". Wembstead built an agency comparison page, sought reviews on the cited sites, and published free onboarding templates. Its sales team's notes confirmed that agencies asked most about client approvals, which neither tool had surfaced, so it added a page on that too.

What do people ask about prompt research tools?

Where does Semrush get its prompt data?

From AI search clickstream data and Google's keyword data for AI Overviews, with responses captured from real requests rather than APIs.

Where does Profound get its prompt volumes?

From real user conversations collected through opt-in consumer panels, according to Profound's disclosures as summarised by independent analysis.

What is Conversation Intent?

A Profound feature that shows the share of conversations for each keyword that are commercial, informational, generative or other.

Can I compare volumes between the two?

Not directly. They use different data and different units.