8 LLM visibility tools to track your brand across answer engines

Large language model (LLM) visibility tools track brand mentions, citations, and share of voice across answer engines. According to Digitaloft, 80% of users rely on zero-click results at least 40% of the time, meaning they often get what they need directly from a search engine results page (SERP) or an AI-generated answer. That behavior can leave marketers with fewer on-site signals such as clicks, scroll depth, and engagement rate.

LLM visibility tools fill the measurement gap created by zero-click AI results by showing how often and how favorably a brand appears in AI-generated answers. Search engine optimization (SEO) metrics such as clicks, conversions, and keyword position still matter. Answer engine optimization (AEO) adds another layer of measurement by tracking repeated prompts, citations, sentiment, and competitor visibility across answer engines.

This roundup compares eight LLM visibility tools, from free diagnostics to enterprise platforms, so that marketers can evaluate the right fit for ongoing tracking.

Table of Contents

• What are LLM visibility tools?
• How do LLM visibility tools work?
• What to Look For in LLM Visibility Tools
• LLM Visibility Tools Comparison Table
• 8 LLM Visibility Tools to Consider
• How to Start AI Visibility Tracking in 30 Days
• Frequently Asked Questions About LLM Visibility Tools
• Start with the AI visibility workflow you need.

What are LLM visibility tools?

LLM visibility tools measure whether and how a brand appears in AI-generated answers across answer engines such as ChatGPT, Gemini, Perplexity, and Google AI Overviews. Unlike traditional SEO rank tracking, these tools measure patterns across repeated AI responses rather than one fixed position. They typically record:

• Whether a brand is mentioned or cited
• How the brand is described
• Which competitors appear for the same prompts
• How results change across engines and over time

How do LLM visibility tools work?

LLM visibility tools start with prompts modeled on questions people might ask while researching a category, problem, or product. The tool runs those prompts through its supported answer engines and records the responses.

A single manual check can show what an answer engine says at that moment, but reliable answer engine tracking requires repeatable prompts across multiple engines and time periods. The same prompt can return different answers between runs, so ongoing tracking tools repeat those checks on a schedule and measure patterns over time.

LLM visibility tools typically measure brand mentions, citations, sentiment, share of voice, competitor presence, and placement frequency depending on the platform. A mention within an AI tool looks like the following example:

The answer mentions five CRM brands, but none has a clickable citation. A citation includes a clickable link, and it looks like this:

A citation points readers to a source that was used or referenced in the generated answer. Citations can drive direct visits to websites, while unlinked mentions still contribute to a brand’s overall visibility.

Within the visibility tracking section, these tools measure two key dimensions: visibility tracking shows whether and how often a brand appears in generated answers, while citation analysis shows which domains, URLs, and content types appear as sources.

What to Look For in LLM Visibility Tools

Marketers can compare LLM visibility tools across six practical criteria: engine coverage, prompt management, citation insights, competitor views, reporting, and workflow fit.

Engine Coverage

Engine coverage refers to which answer engines a tool tracks and whether those engines match the places a brand wants to monitor. Coverage can vary by plan, so marketers should compare what is included at the entry tier with what requires an upgrade.

For example, HubSpot AEO tracks ChatGPT, Gemini, and Perplexity. Profound tracks ChatGPT on its Starter tier, three answer engines on the Growth tier, and up to nine on the Enterprise tier.

Prompt Management

Prompt management covers how teams add, edit, organize, and refresh the questions they track. Some products suggest prompts automatically, while others rely more heavily on manual setup.

Teams should also check what informs those prompt suggestions. Standalone HubSpot AEO uses company, competitor, and industry context, while AEO in Marketing Hub Professional and Enterprise can use CRM data to surface prompts relevant to actual buyers.

Citation Insights

Citation analysis shows which domains, URLs, and content types appear as sources in AI-generated answers. That information can help marketers identify owned-content gaps, third-party publications worth monitoring or pitching, and competitors whose content appears frequently.

Competitor Views

Competitor reporting shows how a brand’s visibility compares with other companies for the same or related prompts. Depending on the tool, comparisons can include share of voice, prompt-level visibility, citations, sentiment, and changes over time.

Reporting

Reporting options determine how easily teams can export or combine AI visibility data with other marketing data. Teams that need to move results into business intelligence tools or internal dashboards should check whether the plan they intend to buy offers exports or API access.

Workflow Fit

Workflow fit describes what happens after a tool identifies a visibility gap. Some products primarily report what happened; others add recommendations, optimization workflows, or content tools.

HubSpot AEO combines ongoing visibility, citation, competitor, sentiment, and recommendation data. AEO in Marketing Hub adds CRM-informed prompt suggestions and connects AEO insights with HubSpot’s broader marketing workflow for Marketing Hub Professional and Enterprise customers.

LLM Visibility Tools Comparison Table

The table below compares all eight tools on those criteria, so marketers can shortlist the right fit for their AI search tracking program before reading the individual write-ups.

8 LLM Visibility Tools to Consider

The tools below take different approaches to AI visibility, from standalone tracking platforms to products that combine answer-engine data with broader SEO or marketing workflows.

1. HubSpot AEO

HubSpot AEO is HubSpot’s ongoing answer-engine visibility product. Its standalone version tracks prompts daily across ChatGPT, Gemini, and Perplexity and reports brand visibility, sentiment, competitor share of voice, citations, and recommendations. Marketing Hub Professional and Enterprise include AEO with additional CRM context.

HubSpot offers AI Search Grader, a free, one-time diagnostic check that evaluates how ChatGPT, Gemini, and Perplexity represent a brand before teams commit to ongoing tracking. It scores five areas:

• Sentiment results: How positively, negatively, or neutrally answer engines characterize the brand.
• Presence quality: How substantively answer engines discuss the brand, and the quality of sources shaping that view.
• Brand recognition: How well answer engines recognize and describe the brand.
• Share of voice: How the brand’s presence compares with competitors in the category.
• Market competition: How answer engines position the brand as a leader, challenger, or niche player.

AI Search Grader is a snapshot, not an ongoing tracking product. It can give teams a baseline view before they commit to a recurring measurement workflow.

Key Features

• Daily multi-engine tracking: Standalone HubSpot AEO tracks 25 prompts across ChatGPT, Gemini, and Perplexity, with each prompt run daily across all three engines.
• Visibility, competitor, and citation analysis: The Brand Visibility Dashboard reports how frequently a brand appears. Competitor and citation views show share of voice and the sources appearing in tracked answers.
• Recommendations and Marketing Hub integration: HubSpot AEO provides prioritized recommendations. In Marketing Hub Professional and Enterprise, CRM-informed prompt suggestions and connected marketing tools add business context to the workflow.

HubSpot’s case study on its own AEO program shows how HubSpot’s marketing team built an answer-engine measurement system around visibility, share of voice, and citations. For teams already using Marketing Hub SEO Marketing Software, AEO complements rather than replaces traditional search analysis. HubSpot’s SEO tools provide search recommendations, topic planning, reporting, and Google Search Console integration, while HubSpot AEO measures visibility inside answer engines.

Best for: Teams that want ongoing AEO monitoring, especially existing HubSpot customers that can use the deeper Marketing Hub integration.

Pricing: Standalone HubSpot AEO costs $50/month or $45/month when billed annually after a 28-day free trial. It is included with Marketing Hub Professional and Enterprise. AI Search Grader is free.

What we like: AI Search Grader is free, and I put every client and their key competitors through it as a first pass because it gives an immediate diagnostic. For ongoing tracking, I like that HubSpot AEO brings visibility, citations, sentiment, competitors, and recommendations into one workflow. Marketing Hub Professional and Enterprise add the CRM-informed prompts I find most useful for grounding tracking in actual business context. I also like that AEO can sit alongside HubSpot’s SEO tools and Google Search Console data rather than being treated as a replacement for traditional search analysis.

2. Semrush

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Semrush combines traditional SEO workflows with AI Visibility in Semrush One, allowing teams to monitor conventional search and answer-engine visibility in the same product family.

Key Features

• AI visibility tracking: Starter includes 50 prompts tracked daily and AI brand-performance reporting across surfaces including ChatGPT, Perplexity, Gemini, Google AI Overviews, and Google AI Mode.
• Competitive analysis: AI Visibility reports compare brand mentions, citations, sentiment, share of voice, and competitors.
• SEO and AI search in one workspace: Teams can analyze AI visibility alongside keyword, site-audit, and other traditional SEO data.

Best for: Teams already using Semrush that want traditional SEO and AI visibility in one workspace.

Pricing: Starter, $199/month or $165.17/month billed annually; Pro+, $299/month or $248.17/month billed annually; Advanced, $549/month or $455.67/month billed annually.

What we like: Semrush has been a long-standing tool in my arsenal, and I’d be lost without it. I like that Semrush One puts answer-engine visibility next to the SEO data I already use, so teams can compare both channels without stitching together separate platforms.

3. Profound

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Profound is an answer-engine visibility platform that combines brand monitoring with prompt-demand data and enterprise reporting. Self-service plans start with narrower engine coverage, while the Enterprise plan expands to up to nine answer engines.

Key Features

• Multi-engine tracking: Starter tracks ChatGPT, Growth tracks three answer engines, and Enterprise supports up to nine.
• Prompt Volumes: Profound surfaces data about the prompts people use across AI platforms so teams can understand demand alongside brand visibility.
• Enterprise reporting and integrations: Enterprise supports multi-company and multi-region tracking plus API access.

Best for: Enterprise teams that need broader engine, company, and regional coverage.

Pricing: Starter, $99/month billed yearly; Growth, $399/month billed yearly; Enterprise, pricing available on request.

What we like: We like that Profound pairs visibility monitoring with Prompt Volumes instead of treating every tracked question as equally important. Its broader engine and regional coverage also give larger organizations room to expand beyond a basic three-engine monitoring setup.

4. Peec AI

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Peec AI is a standalone AI search analytics platform focused on brand visibility, competitor performance, citations, sentiment, and next steps.

Key Features

• Flexible prompt and model tracking: Starter includes 50 prompts, Pro 150, and Advanced 350. Self-service plans let teams choose three models, while Enterprise supports up to 13.
• Visibility and source analytics: Peec AI tracks visibility, position, sentiment, share of voice, competitors, domains, and URLs across monitored AI answers.
• Prioritized Actions: The platform turns visibility and source gaps into recommended actions so teams can decide which opportunities to address first.

Best for: Teams that want dedicated AI-search analytics without buying a broader SEO suite.

Pricing: Starter, $95/month; Pro, $245/month; Advanced, $495/month; Enterprise, pricing available on request. Annual billing receives a 15% discount.

What we like: We like Peec AI’s focused approach to AI visibility and its Actions workflow, which moves beyond reporting by giving teams a prioritized set of visibility and source opportunities to investigate.

5. Tracksuit

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Tracksuit is an always-on brand tracking platform that measures how consumers perceive a brand and its competitors. Unlike answer-engine visibility tools, Tracksuit does not track AI-generated answers directly. Instead, it provides consumer brand-health data showing how awareness, consideration, preference, usage, and brand associations compare across a category, which can complement answer-engine visibility data.

Key Features

• Brand funnel tracking: Tracksuit measures awareness, consideration, usage, and preference over time and compares those metrics with competitors.
• Brand perception: Imagery and Statements show the words, attributes, and associations consumers connect with a brand and how those perceptions compare with competitors.
• AI-assisted insights: Coach’s Notes summarizes significant changes across brand-health data, while Ask AI lets marketers ask plain-language questions about their dashboard data and receive explanations, charts, and links to relevant reports.

Best for: Brands that want always-on consumer brand-health and competitor tracking as a complement to answer-engine visibility data.

Pricing: Tracksuit starts at $19,500 per brand per year. Multi-brand and multi-market commitments may use different commercial models, and exact pricing requires a demo.

What we like: Tracksuit gives marketers a consumer-research counterpoint to answer-engine visibility data. It can help teams compare what AI systems say about a brand with how consumers actually perceive it. At the same time, social listening tools add another view of how audiences discuss the brand across public channels.

6. Rankshift AI

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Rankshift is an AI visibility platform that tracks how brands appear across answer engines and combines visibility reporting with competitor, citation, crawler, and content-analysis tools.

Key Features

• Broad engine coverage: Rankshift supports ChatGPT, Gemini, Google AI Overviews, Google AI Mode, Claude, Perplexity, Mistral, and Llama.
• Prompt tracking: Starter includes up to 150 prompts per day, with flexible refresh frequency and unlimited projects and seats.
• Citation and competitor analysis: Teams can monitor citation sources, sentiment, visibility, share of voice, and competitor tracking across repeated runs.

Best for: Teams that want broad engine coverage, flexible prompt frequency, and generous project and user limits.

Pricing: Starter costs $82/month billed annually. Professional costs $189/month billed annually. Business costs $425/month billed annually. Enterprise pricing is available on request.

What we like: Rankshift combines broad engine coverage with flexible prompt frequency, citation analytics, and unlimited projects and users instead of reserving those basics for an enterprise tier.

7. ZipTie

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ZipTie is an AI search intelligence platform that monitors brand mentions, citations, sentiment, competitors, and full responses across seven AI search engines. ZipTie’s pricing is configurable by engine coverage, prompt volume, and tracking frequency.

Key Features

• Engine coverage: ZipTie tracks ChatGPT, Google AI Overviews, Perplexity, Google AI Mode, Microsoft Copilot, Bing AI Overview, and Gemini.
• AI Success Score: The score combines mention rate, sentiment, and citation rate to provide a single visibility trend.
• Action-oriented analysis: Teams can use monitoring data, citations, source analysis, and optional content tools to identify what to work on next.

Best for: Teams that want to customize the engines, prompts, and tracking frequency they pay for.

Pricing: ZipTie uses usage-based pricing. Its current presets start at $35.63/month for Starter, $549.67/month for Professional, and $2,614.34/month for Enterprise. Teams can adjust those configurations, and annual billing discounts the prompt subtotal by 20%.

What we like: ZipTie lets teams configure engine coverage and tracking cadence instead of forcing every customer into the same fixed bundle. Its combination of visibility, sentiment, citations, competitor data, and action-oriented analysis also makes the reporting easier to connect with content work.

8. Gumshoe

Gumshoe is an AI search management platform built around persona-based Visibility Audits. Gumshoe tests prompts across multiple models, shows which brands and competitors appear, and lets teams examine the citations and context behind those answers.

Key Features

• Persona-based audits: Starter uses eight personas with 10 prompts per persona across six models.
• Recurring visibility tracking: Starter includes a monthly Visibility Audit plus weekly Snapshot Audits.
• Deeper audits on Pro: Pro adds dedicated Citation, Sentiment, and Content Audits alongside the core visibility workflow.

Best for: Teams that want to analyze AI visibility by buyer persona and topic rather than using one flat prompt list.

Pricing: Starter costs $99/month. Pro starts at $299/month.

What we like: We like Gumshoe’s emphasis on the context behind a visibility score. Persona, model, citation, topic, and competitor views make it easier to see where a brand’s results differ instead of treating every AI answer as part of one undifferentiated average.

How to Start AI Visibility Tracking in 30 Days

AI visibility tracking for beginners is best managed as a staged rollout. A marketing team that tries to monitor every prompt across every platform on day one usually ends up with data nobody reviews. The sequence below builds a baseline in four weeks, starting with a free snapshot and moving into ongoing monitoring.

Week 1: Build the prompt set.

A prompt set is the group of questions a team tracks to see how answer engines represent a brand during research and buying decisions. When building your prompt set, start with prompts that reflect meaningful buyer questions rather than trying to maximize the number of prompts. Use several prompt types so the set covers different stages of discovery:

Source the wording from real audience inputs where possible. Sales-call transcripts, support tickets, search-query data, and social listening tools can all surface language customers already use. The right number of prompts depends on the product’s limits, the markets being tracked, and how broad the buying journey is.

Week 2: Establish the baseline.

Before making answer-engine optimization (AEO) changes to your content or strategy, capture a baseline measurement of your current visibility. HubSpot’s AI Search Grader can provide a free one-time diagnostic of how answer engines characterize a brand across dimensions such as sentiment, recognition, presence quality, share of voice, and competitive position.

Treat that result as a snapshot, not an ongoing measurement system. Once the team chooses a tracking platform, record the first results for the exact prompt set it will monitor. Those prompt-level results provide the baseline for measuring later changes in visibility, citations, sentiment, and competitor performance.

Week 3: Review citations and prioritize fixes.

Mentions show when a brand appears in an answer, while citations show which domains or URLs the answer engine references as sources. Review the citations across your tracked prompt set and separate them into three categories: owned sources your brand controls, third-party sources from other publishers, and prompts where your brand does not appear.

Owned pages that already receive citations can reveal useful topics or formats to develop further. Third-party citations can identify publications, review sites, communities, or comparison pages where earned visibility may matter. Prompts where the brand does not appear can identify content or distribution gaps. The same fundamentals used to increase visibility for existing blog content can inform that work, while AEO adds the answer-engine-specific citation layer.

Prioritize changes by business relevance, the size of the visibility gap, and the team’s ability to act. Correct factual information the brand controls, review important third-party sources, and create or update owned content where the prompt and citation data show a meaningful gap.

Week 4: Move into ongoing tracking.

A one-time audit cannot show whether visibility changes over time, so ongoing tracking requires repeated measurements. HubSpot AEO runs tracked prompts daily across ChatGPT, Gemini, and Perplexity, and HubSpot recommends evaluating results across multiple days or weeks instead of drawing conclusions from isolated daily changes.

For Marketing Hub Professional and Enterprise customers, AEO in Marketing Hub adds CRM-informed prompt suggestions and places AEO insights alongside other marketing data. Teams can compare those results with the sales KPIs they already report while treating AI visibility as one input in the measurement path to leads and pipeline rather than claiming complete attribution for zero-click AI influence.

Market-level context can also help explain sudden changes. HubSpot’s free AI Search Sensor tracks industry-level AI visibility and answer-engine volatility. It does not report a specific brand’s visibility, but it can help marketers see whether a change coincides with broader movement across AI search.

Frequently Asked Questions About LLM Visibility Tools

Which LLMs should I prioritize for visibility tracking?

Prioritize the answer engines that matter to the business and that your chosen tracking platform supports. Keep in mind that while analytics tools can show visits arriving from AI platforms through referral traffic, they cannot measure people who see your brand in an AI answer but never click through—another reason visibility monitoring matters beyond click-based metrics.

For broad coverage, teams commonly monitor major surfaces such as ChatGPT, Gemini, Perplexity, Google AI Overviews, and Google AI Mode, then refine the mix as they collect their own audience and referral data.

How many prompts do I need to get a reliable visibility read?

No universal prompt count guarantees a reliable result. A useful prompt set should cover the buyer questions, products, use cases, competitors, and markets the team actually needs to understand.

Start with a focused prompt set that fits your chosen tool’s plan limits, then expand to additional prompts only when those new prompts answer distinct business questions about different buyer segments, products, use cases, or competitors — rather than adding volume for its own sake.

Can I track AI visibility for multiple brands and countries?

Yes, but the limits vary by product and plan. Some platforms include multiple projects, regions, or countries on self-service tiers, while others reserve expanded geographic or multi-brand tracking for higher tiers or custom plans.

Check the number of projects, supported locations, languages, models, and prompt allowances before choosing a plan.

How do I connect AI visibility to revenue in our CRM?

Start by measuring AI-referred sessions, conversions, and contact-source data from your CRM, then compare those outcomes with visibility trends in your AEO tool. This approach creates a measurement path from AEO activity toward leads and pipeline without assuming every zero-click AI interaction directly caused a conversion.

AEO in Marketing Hub adds CRM-informed prompt suggestions and places AEO insights alongside marketing data. Standalone HubSpot AEO provides ongoing visibility tracking without requiring another HubSpot subscription.

Do LLM answers change too often to be tracked?

Individual responses can vary between runs, which is why visibility tools repeat prompts on a schedule rather than relying on single measurements. Unlike traditional search rankings, AI-generated answers fluctuate between runs, so avoid treating a single answer as a durable position.

Repeated tracking can reveal directional patterns across a prompt set. HubSpot, for example, runs its tracked prompts daily and recommends reviewing performance over multiple days or weeks before evaluating trends.

Start with the AI visibility workflow you need.

AI-generated answers now sit alongside traditional search during product discovery and research. That makes AI visibility worth measuring, while the clicks, conversions, rankings, and other SEO metrics marketers already use remain important.

Teams that want ongoing monitoring can start with HubSpot AEO, which tracks prompts across ChatGPT, Gemini, and Perplexity and adds citation, competitor, sentiment, and recommendation data. Marketing Hub Professional and Enterprise customers can use the deeper CRM-informed version inside Marketing Hub.

For teams that want to understand their current position before setting up ongoing tracking, HubSpot’s AI Search Grader provides a free one-time snapshot.