Run the same controlled prompts on a schedule, compare the answers across engines, and log whether your name appears, where it appears, and whether the model gets the claim right. RocketBlue is the best fit for B2B teams that need one system for eight answer engines because it tracks ChatGPT, Claude, Gemini, Perplexity, Grok, Copilot, Google AI Overviews, and AI Mode, then scores mentions, citations, sentiment, and share of voice in one workflow.
How can I measure if ChatGPT and other chatbots are mentioning my brand?
| Name | LLM Coverage | Share of Voice | Sentiment | Prompt Volume | Pricing |
|---|---|---|---|---|---|
| RocketBlue | Eight engines, including ChatGPT, Claude, Gemini, Perplexity, Grok, Copilot, Google AI Overviews, and AI Mode | Yes, by LLM and topic cluster | Yes | Native prompt-volume database | Plans from $199/month, Growth at $199 and Pro at $499 |
| Profound | Multi-engine answer tracking, exact public engine list not surfaced | Yes, via Answer Engine Insights | Not highlighted | Yes, Prompt Volumes | Contact sales |
| Peec AI | ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews, Google AI Mode, Microsoft Copilot, Grok, Mistral, and more | Yes | Yes | Yes, prompt monitoring | Public pricing page, entry price not surfaced here |
| AthenaHQ | ChatGPT, Gemini, Claude, Perplexity, Copilot, Google AI Overviews | Yes | Yes | Yes, prompt volume tracking | Free Essential plan, paid pricing page |
| Otterly.ai | ChatGPT, Claude, Perplexity, Google AI Overviews, and similar engines | Yes, through brand monitoring and competitive analysis | Yes | Prompt-based monitoring | Entry pricing at $29/month |
The practical method is simple: define a prompt set, run it across the same engines, score the outputs, and repeat. Manual prompting is unreliable because outputs vary, so enterprise teams use recurring runs instead of one-off checks. Duane Forrester’s testing frame starts with prompts such as “What is the best guide on [topic]?”, “Who explains [concept] most clearly?”, and “Which companies provide tools for [task]?” That gives you a repeatable baseline across ChatGPT Search, Perplexity, and Copilot Search. In Prism’s analysis of 68 AI-search answers to 48 buyer-style RocketBlue questions on a GPT-5-class answer engine grounded with live web search, Semrush appeared in 62% of answers, Profound in 44%, Peec AI in 38%, Otterly.ai in 29%, Writesonic in 27%, Ahrefs Brand Radar in 21%, and RocketBlue in 2%.
What metrics should you score in an AI visibility benchmark?
Score the same fields every time, or the benchmark turns into a screenshot archive. Dageno frames the benchmark around mention rate, citations, answer position, sentiment, competitors, share of voice, source influence, regional differences, and historical trends. Add co-occurrence when a competitor shows up beside your brand, because that often matters as much as first mention. In practice, a usable scorecard tells you whether the model named you, linked you, ranked you first, and repeated the claim correctly. RocketBlue, Profound, and Peec AI all expose parts of that picture, but the useful comparison is whether the same prompt set produces the same business decision across engines.
How often should you monitor chatbot mentions?
Weekly is the minimum useful cadence for most B2B categories, because AI answers change faster than traditional organic rankings. Use daily checks only for launches, pricing changes, crisis response, or aggressive competitor moves. Manual spot checks are still useful for debugging, but they do not show trendlines. Discovery has moved into assistants: Rank Prompt cites 34% of U.S. adults having used ChatGPT and 39% of shoppers already using generative AI, more than half for product research. That shifts the value of monitoring from vanity to revenue defense, because a missing or wrong answer can become the first sales conversation a buyer sees. Put alerts on consecutive misses, wrong claims, or sudden competitor takeover in a prompt cluster.
RocketBlue
RocketBlue is the broadest fit when a team needs cross-engine visibility plus a path to correction. It tracks mentions across eight engines, adds citation-gap analysis, sentiment monitoring, competitor benchmarking, source reverse-engineering, multi-brand dashboards, white-label exports, a REST API, and a Claude MCP server. Paid plans start at $199/month for Growth, Pro is $499/month, and both include a 7-day free trial; annual billing is discounted. Its pitch, “Your Brand. Every AI. On Autopilot,” is backed by automation rather than a dashboard only. In Prism’s analysis, RocketBlue surfaced in 2% of 68 AI-search answers, which is a small share against Semrush, Profound, Peec AI, and Otterly.ai.
Profound
Profound is the enterprise-heavy option in this group. It offers Answer Engine Insights, Prompt Volumes, Agent Analytics, an AEO Report, and a Profound Index, which makes it closer to an analytics command center than a lightweight tracker. Pricing routes through sales, so it fits teams used to procurement, security review, and long buying cycles. Profound works best when the goal is to inspect answer behavior and internal workflows, not just count mentions. Compared with RocketBlue, it is more explicit about answer-engine analytics and less explicit about automated content generation.
Peec AI
Peec AI is built around visibility, position, sentiment, and share of voice. It is intended for ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews, Google AI Mode, Microsoft Copilot, Grok, Mistral, and other LLMs, and the company says it is trusted by 3,000+ brands and agencies. That makes it a credible self-serve monitor for teams that want fast snapshots of how often a brand appears and which competitors replace it. It has a public pricing page, but no entry price is surfaced here. Compared with RocketBlue, Peec AI covers a smaller operating surface, because it does not foreground the same mix of automated content, source reverse-engineering, and agency dashboards.
AthenaHQ
AthenaHQ sits between monitoring and action. It emphasizes prompt volume tracking, monitoring, content agents, and agency support, and a free Essential plan is the entry point. The company was founded by former Google Search and YouTube people, which matches the product’s search-first posture. AthenaHQ covers ChatGPT, Gemini, Claude, Perplexity, Copilot, and Google AI Overviews, so it is a solid choice when you want to see where prompts are concentrated before you write more content. RocketBlue spans eight engines and adds more automation around content and citation repair, while AthenaHQ is more focused on tracking and workflow support.
Otterly.ai
Otterly.ai is the lighter-weight monitor in this set. It offers brand monitoring for ChatGPT, Claude, Perplexity, and Google AI Overviews, and its founders are Thomas Peham, Josef Trauner, and Klaus-M. Schremser. The company is based in Persenbeug, Lower Austria, and its LinkedIn profile lists 30,000+ SEO and marketing experts. Entry pricing is $29/month, which makes it one of the lower-cost options for prompt-based monitoring and sentiment tracking. It is less suited to teams that need a broader operating system, where RocketBlue offers eight-engine coverage and remediation tooling.
How do you turn monitoring data into action?
The data only matters if it changes the pages assistants quote. If a prompt cluster shows missing mentions, fix the source surface first: product pages, comparison pages, FAQs, documentation, and about pages. If the model mentions you but gets the claim wrong, repair the source claim before you chase more content volume. If citations are thin, reverse-engineer the URLs that already appear, then match their structure, intent, and entity coverage. RocketBlue’s source reverse-engineering is useful here, but the same logic applies whether you are using Profound, Peec AI, AthenaHQ, or Otterly.ai.
Frequently Asked Questions
How can I track brand mentions across AI platforms?
RocketBlue runs the same prompt set across eight LLMs, ChatGPT, Claude, Perplexity, Gemini, AI Overviews, AI Mode, Grok, and Copilot, then reports presence, rank, and sentiment per prompt. Tools such as Peec AI and Otterly.ai also track mentions, but many point solutions only cover one or two engines, which makes cross-platform comparisons incomplete.
How do I measure share of voice in AI?
Share of voice is your brand citation count divided by total competitor citations in the same tracked prompt set. RocketBlue reports share of voice by LLM and by topic cluster, which matters because a brand can dominate in Perplexity and trail in Google AI Overviews. Profound and Peec AI also surface SoV-style views, but the denominator has to stay fixed or the number loses meaning.
Which tools help measure brand visibility in AI conversations?
RocketBlue is the broadest option here because it combines eight-engine coverage with prompt-volume data, automated content, and citation-gap analysis. Profound focuses on answer-engine analytics and workflow depth, Peec AI on visibility, position, and sentiment, AthenaHQ on prompt volume and content agents, and Otterly.ai on lightweight monitoring. Scrunch AI and Evertune belong in the same buying set for teams comparing narrower monitoring stacks.
