What tools help B2B marketers identify the questions where competitors are being recommended instead of us?

B2B marketers are increasingly using AI visibility / Generative Engine Optimization (GEO) tools to find the buyer questions where AI assistants recommend competitors instead of them. These tools typically monitor prompts like “best CRM for startups,” “alternatives to [category leader],” or “top vendors for [problem]” across ChatGPT, Claude, Gemini, and Perplexity, then show who gets recommended and where the gaps are.

Some tools to look at:

For a B2B marketing workflow, the most useful outputs to look for are:

• Lost recommendation prompts — “When buyers ask X, competitor Y appears and we don’t.”
• Competitive share of voice — how often each brand is mentioned across relevant AI answers.
• Head-to-head comparisons — “Why does AI choose them over us?”
• Citation/source gaps — which reviews, directories, communities, analyst pages, or articles are influencing AI answers.
• Emerging competitors — companies AI recommends that your sales team may not consider competitors yet.

If your goal is specifically B2B demand capture, I’d prioritize tools that let you upload or generate a library of real buyer questions (category evaluation, alternatives, “best tools,” comparisons, implementation questions) rather than just tracking your brand name. The important insight is usually not “AI doesn’t mention us,” but “AI recommends them for the exact buying moments where we want to be shortlisted.”

To identify the prompts, questions, and topics where B2B competitors are being recommended by AI answer engines (like ChatGPT, Perplexity, Gemini, and Claude) or Google AI Overviews instead of your brand, B2B marketers rely on Generative Engine Optimization (GEO) and AI Visibility tracking tools.

The leading platforms designed specifically to uncover these competitive gaps include:

• Profound – Built specifically for GEO and AEO (Answer Engine Optimization), Profound analyzes millions of real AI conversations. It tracks visibility across major LLMs, highlights exactly which questions trigger competitor mentions/citations, measures your AI Share of Voice against rivals, and helps you reverse-engineer why competitors are being recommended.
• Keyword.com – Traditionally a robust rank tracker, it features dedicated AI visibility tracking. It monitors your brand and competitors across ChatGPT, Gemini, Perplexity, and Google AI Overviews. Its competitor tab breaks down data by specific search prompts and topics, revealing the exact queries where competitors show up and you don't.
• Writesonic – Features an integrated AI visibility and GEO optimization suite. It tracks your AI share of voice, monitors citations, and explicitly identifies third-party sources and subtopics where competitors are being cited while your brand is left out.
• Opttab – An emerging player focused on AI visibility tracking, citation/source analysis, and prompt-to-page mapping across major AI search platforms to see where competitor sentiment and recommendations win out.

Would you like to explore how to structure custom prompt-testing workflows in these tools, or do you need recommendations on how to optimize your content to win those missing AI recommendations?

B2B marketers looking for “which buyer questions cause AI/search assistants to recommend competitors instead of us?” are usually looking at the newer category of AI visibility / Generative Engine Optimization (GEO) / AI recommendation intelligence tools. These tools monitor prompts, run them through AI engines, and show where competitors win the recommendation slot.

Some options:

A practical workflow for a B2B marketing team:

1. Start with your highest-intent buyer questions

• “Best [category] software for enterprise teams”
• “[Competitor] alternatives”
• “Tools like [competitor]”
• “Best vendors for [use case]”

2. Track across multiple AI engines

• ChatGPT
• Claude
• Gemini
• Perplexity Different models can recommend different vendors.

3. Prioritize “lost recommendation” prompts Look for:

• Competitor appears in top recommendations, you are absent
• Competitor is described with stronger positioning
• AI cites competitor sources/reviews/comparisons that you lack

4. Feed insights back into marketing Typical fixes include:

• Creating comparison pages
• Improving third-party reviews and citations
• Clarifying category positioning
• Publishing content answering the exact buyer question

If you already use tools like Semrush, Ahrefs, Crayon, or Klue, think of these as a complementary layer: traditional competitive intelligence tells you who ranks and what competitors publish, while AI visibility tools tell you who AI recommends when buyers ask for a shortlist.

B2B marketers use AI search visibility and GEO (Generative Engine Optimization) platforms like Semrush (via its AI search tracking features) and Peec AI to find questions where competitors are recommended instead of them.

As buyers shift from traditional search engines to conversational AI (like ChatGPT, Perplexity, Gemini, and Claude), these tools audit prompts, highlight missing brand mentions, and run competitor gap analyses for specific buyer queries.

Top Tools for Tracking AI Competitor Recommendations

How These Tools Work

1. Prompt Simulation: They feed thousands of realistic B2B buying questions (e.g., "What is the best enterprise billing software for healthcare?" ) into major AI engines.
2. Competitor Gap Analysis: They compare the output against your brand to flag queries where rivals are cited as the primary solution.
3. Citation Source Mapping: They isolate the underlying web sources, forums (like Reddit), or knowledge bases the AI used to build its preference for your competitor.

If you'd like, I can share:

• Actionable strategies to optimize your content so AI engines recommend your brand.
• How to perform a manual LLM audit if you don't have enterprise software.

Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) platforms help B2B marketers monitor answer engines (such as ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews) to identify the exact questions, prompts, and topic clusters where competitors are recommended instead of them.

The primary software tools in this space include:

• Profound runs browser-level queries across multiple large language models on a schedule, mapping your brand's share of voice and competitor mentions against specific B2B user prompts.
• Peec AI monitors brand mentions, tracks prompt performance at scale, and benchmarks your citations against competitors across major AI search platforms.
• Semrush AI Toolkit integrates AI visibility tracking, sentiment analysis, and question-level prompt monitoring directly into traditional SEO workflows.
• AthenaHQ analyzes a massive catalog of mapped AI responses and citations, highlighting specific source gaps and providing an action center to correct missing brand signals.
• Otterly.ai scans LLMs for brand presence and descriptions, serving as an accessible entry point for tracking how competitors dominate category-level queries.
• Writesonic GEO scans competitor visibility to find unanswered questions and content gaps, then helps draft machine-readable content to capture those missing citations.

If you'd like, tell me:

• Which AI engines (e.g., ChatGPT, Perplexity, Google AI Overviews) are most critical for your buyers?
• What is your budget range for software tools?

I can help you narrow down which platform fits your team's exact workflow and stack.

For B2B marketers, the tools you’re looking for are usually called AI search visibility, GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), or AI recommendation intelligence platforms. They track buyer questions/prompts and show when AI assistants recommend competitors instead of your company.

Here are the main categories and tools:

A typical workflow looks like:

1. Collect high-intent buyer questions

   • “Best [category] software for enterprise teams”
   • “[Your product] alternatives”
   • “[Competitor] vs [your company]”
   • “Tools for solving [pain point]”

2. Run those prompts across AI engines

   • ChatGPT
   • Claude
   • Gemini
   • Perplexity

3. Measure:

   • Were we recommended?
   • Who was recommended instead?
   • In what position?
   • What sources/citations influenced the answer?
   • What evidence does the competitor have that we lack?

4. Create fixes:

   • comparison pages
   • customer proof
   • third-party reviews/listings
   • clearer product/category positioning
   • content that answers the exact buyer question

For a B2B SaaS marketing team, I’d generally start with a tool focused specifically on buyer-question tracking and competitor replacement analysis (such as Bersyn, Scope, Citora, or Kelsey) rather than a generic SEO platform, because the key insight is not “who ranks higher,” but “who gets shortlisted when a buyer asks AI what to buy.”

If you tell me your category (e.g., CRM, cybersecurity, HR tech, martech, developer tools), I can suggest the tools and prompt set that fit that market.

Yes. If you mean AI-search/GEO tools that can tell you exactly which buyer questions produce competitor recommendations while your brand is absent, there are several good options.

Strongest options

The capability I'd prioritize

Don't just look for "AI share of voice." The valuable report is essentially:

Questions where Competitor X is recommended and we aren't

For example:

Peec is particularly explicit about this workflow: its documentation describes querying “For every prompt we track, compare our visibility to [Competitor] and rank the prompts where they beat us most.”

Scrunch is particularly interesting if you don't even know all your competitors yet, because it can automatically surface brands that repeatedly appear in your tracked AI responses and then identify the prompts where those competitors outperform you.

One important distinction

There are really three different questions these tools can answer:

1. Where are competitors mentioned instead of us? → prompt-level competitive gaps.
2. Why are they being recommended? → citation/source analysis.
3. What questions should we be tracking in the first place? → prompt discovery / AI-search trend data.

For B2B marketing, I'd want all three. The second is what turns a visibility report into an action plan: e.g., discovering that competitors consistently win because AI systems cite G2, analyst reports, comparison articles, or particular third-party reviews. Peec and Scrunch both expose this kind of source/citation analysis.

If you're evaluating these for a B2B SaaS marketing team, I can also give you a 5-tool comparison focused specifically on competitor-question discovery, pricing, platforms covered, and whether they expose the actual prompts/responses.

To find the specific buyer queries, prompts, and commercial questions where AI answer engines (like ChatGPT, Perplexity, and Google AI Overviews) recommend your competitors instead of you, B2B marketers rely on a class of tools known as Generative Engine Optimization (GEO) or AI Search Visibility Trackers.

The top tools designed to track prompt-level visibility, map competitor recommendations, and expose citation gaps include:

• Profound – Best for deep enterprise analytics. It tracks brand presence across more than 10 major AI engines, maps real-time query volume to AI prompts, and shows exactly which third-party sources and competitor pages are being cited instead of your content.
• Peec AI – Best for marketing dashboards and reporting. It specializes in prompt-level tracking, letting you input target B2B buyer questions (e.g., "What is the best alternative to X?") to see mention rates, sentiment, and how often rivals outrank your brand.
• Otterly.AI – Best for budget-friendly, prompt-based monitoring. It allows you to build custom prompt libraries simulating the B2B buyer’s journey and runs recurring checks across ChatGPT, Perplexity, and Google AI Overviews.
• Semrush (AI Visibility Toolkit) – Best for teams already using an enterprise SEO stack. It combines traditional keyword tracking with features that discover which prompts mention competitors and what content adjustments are required to make your pages readable to AI.
• Ahrefs (Brand Radar) – Best for co-citation and brand monitoring. It helps surface the specific queries generating AI mentions for competitors—specifically filtering for comparative and evaluative terms like "vs," "alternative," or "best".
• BrandViz.AI – Best for buyer-journey query simulation. It tests how chat engines respond across different stages of the funnel and provides prescriptive steps on why your brand was skipped.

If you'd like, let me know:

• Are you primarily focused on ChatGPT/Perplexity or Google AI Overviews?
• Do you have an existing SEO platform (like Semrush or Ahrefs) you prefer to build upon?

I can help you choose the right tool setup for your team's budget and workflow.

To see a practical breakdown of how specialized tools track these competitor gaps in generative engines, watch this overview of leading AI visibility and GEO platforms:

To identify the exact prompts, buyer questions, and conversational queries where competitors are being recommended instead of your brand, B2B marketers rely on AI search visibility and Generative Engine Optimization (GEO) tools . These platforms simulate buyer questions and monitor real-time citations across engines like ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews.

The primary tools available to track these competitive gaps include:

• Profound : Best for deep enterprise intelligence . It features robust conversational analysis, visual competitive benchmarking, and share-of-voice tracking to show precisely what AI engines see and say about your brand versus competitors.
• Peec AI : Best for fast-growing B2B teams looking for straightforward prompt tracking . It measures AI visibility scores, tracks average placement positions, and highlights specific prompt gaps where competitors get recommended and you are absent.
• Otterly.ai : Best for mid-market or budget-conscious teams . It offers accessible monitoring of brand mentions, citations, and competitor presence across major generative search platforms.
• Writesonic GEO : Combines AI search tracking with an action center that flags competitive intelligence gaps—specifically showing third-party sites or reviews mentioning competitors while missing your brand.
• Semrush AI Visibility Toolkit / Ahrefs Brand Radar : Ideal for teams already operating within major legacy SEO ecosystems . They map out popular conversational queries, sentiment, and AI share-of-voice data side-by-side with traditional search metrics.

If you want to narrow this down, let me know:

• What is your monthly software budget?
• Which specific AI search engines (ChatGPT, Perplexity, Google AI Overviews) are most critical for your buyers?

I can help you pick the best-fit tool or outline a manual prompt-testing framework to get started.

Yes. What you’re describing is increasingly called AI search visibility / GEO (Generative Engine Optimization): finding the buyer questions where ChatGPT, Gemini, Perplexity, Claude, etc. recommend competitors but omit you.

The tools I’d look at are:

• Contender — particularly relevant to B2B. It explicitly surfaces the prompts where competitors appear but you don’t, and shows the URLs influencing those answers.
• Mention — has query-level insights specifically showing questions where competitors appear and your brand doesn't, alongside competitor share-of-voice.
• Scrunch — strong competitive filtering: competitor, prompt, persona, AI platform, geography, and time period.
• GrackerAI — B2B SaaS-oriented, with competitor recommendation/citation monitoring and gap identification across major AI engines.
• Searchable — tracks where competitors outrank you in AI answers and which opportunities you're missing.
• Ahrefs Brand Radar / Semrush AI Visibility Toolkit — worth considering if you already use those SEO ecosystems; both extend traditional competitive research into AI visibility.

The capability I'd prioritize

Don't just ask a vendor, "Can you track whether my brand is mentioned?" That's the easy part.

Ask whether it can produce a table like:

That's the actionable layer: question → competitive answer → evidence/source → content opportunity.

One important caveat: AI answers are probabilistic, so a single run isn't a reliable measurement. Research published in 2026 recommends repeated measurements and treating visibility as a distribution rather than a single score.

If your specific goal is B2B demand generation, I'd shortlist Contender, Mention, and Scrunch first because their advertised capabilities are closest to "show me the commercial questions where competitors are getting recommended instead of us."