Chatbeat

Brand visibility in AI-generated answers

Chatbeat helps marketing and search teams study how AI platforms describe and recommend a brand. Instead of tracking a conventional search results page alone, it analyzes responses to customer-like questions. The product reports visibility, position, share of voice, and sentiment across platforms including ChatGPT, Gemini, and Perplexity.

This is useful when a business wants to understand whether its products appear in category comparisons and which competing brands appear alongside them. The unit of analysis is a monitored prompt and its responses. A dashboard score therefore describes the questions and platforms being monitored; it should not be read as a census of every private conversation people have with AI assistants.

Sources, context, and competing brands

Chatbeat combines brand visibility tracking with analysis of sources cited in AI answers. Teams can examine the websites associated with a response, compare competing brands, and inspect how a brand is described. Sentiment and narrative context add detail that a simple mention count would miss: appearing in a list and receiving a negative description are different results.

Suggested prompts and recommended actions help turn the analysis into a working research queue. They are starting points for editorial investigation. A cited page can reveal where an answer obtained information, but seeing that citation alone does not prove that editing the page will change the next answer.

An example monitoring workflow

A software company's search team could begin with purchase questions for its main use case, separating general category questions from brand-specific comparisons. It would track those prompts, inspect responses where its product is absent or misdescribed, and read the cited sources. A content owner could then correct outdated information on pages the company controls or prepare clearer product documentation.

Keep the prompt set stable while evaluating a change, and record any additions separately. Otherwise, a higher score may reflect a different collection of questions rather than improved representation. Review actual response text when a sentiment or position metric changes sharply, then compare the finding with referral and conversion data in the company's own analytics.

Plan scope and access

The pricing page organizes paid subscriptions around prompt allowances, model coverage, and response analysis. Listed packages include 30, 100, and 300 prompts with daily refresh, while enterprise options include custom analysis, advanced exportable data and API access, white-label reporting, and dedicated project support. Confirm the selected model package rather than assuming every subscription includes identical coverage.

The official site advertises a 14-day trial without a credit card. Its resources page provides a product demo and materials on prompt selection, including a tutorial using Google Search Console. Those materials can help a team decide which existing customer questions belong in its monitoring set before paying for a larger allowance.

What the findings can and cannot establish

AI answers vary with the question, platform, and time of collection. Treat movement as evidence to investigate across repeated observations. Visibility and citations can inform content priorities, but they do not guarantee recommendation placement, website traffic, or sales. Chatbeat is most useful when someone owns the follow-up work of checking sources and resolving unclear or outdated product information.