Track your brand's AI Sentiment

AI models don't just mention brands, they describe them. Sentiment analysis tracks the tone and framing AI platforms use when your brand comes up in a generated response: whether the language is positive, negative, neutral, or absent. As AI becomes a primary research tool for buyers, how models describe your brand shapes purchasing decisions before a prospect ever visits your site.

Gauge runs hundreds of customized prompts daily across ChatGPT, Perplexity, Gemini, and Claude, then analyzes the language used when your brand appears in the response. It goes beyond tracking whether you're mentioned to evaluating how you're described, surfacing the prompts and topics where sentiment is weakest and ranking them by impact.

Traditional brand monitoring tracks what people say about you. AI sentiment tracks what AI models say about you, which is increasingly what shapes a buyer's first impression. When someone asks ChatGPT or Perplexity to compare tools in your category, the framing in that response, not a review site, may be the deciding factor. A brand can have strong visibility and still be losing deals because of how AI describes it.

Yes, and it's more common than most teams expect. ChatGPT, Perplexity, Gemini, and Claude each form their own view of a brand based on the sources they index and how they weight them. Gauge monitors sentiment across all tracked models simultaneously, so you can see if one platform is consistently framing your brand differently and act on it specifically.

 AI models synthesize sentiment from the sources they cite. Negative reviews, critical press coverage, competitor comparison content that frames you unfavorably, or simply a lack of strong first-party content can all pull sentiment down. Because AI models scan 50-60 sources per query rather than just the top few, a handful of negative sources can have an outsized effect on how your brand is described.

The most reliable lever is first-party content: blog posts, case studies, and product pages that include brand-linked examples, proprietary data, and clear positioning. When AI models have strong, authoritative first-party sources to draw from, they're more likely to reflect your own framing. Gauge identifies exactly which prompts and topics are producing weak sentiment and connects each one to a recommended content or technical action.

Every sentiment finding in Gauge links directly to a recommended fix, whether that's a content brief, a structural update, or a citation opportunity. After you act, Gauge continues monitoring the same prompts daily so you can see sentiment shift in response to the changes you made. It's the same closed loop as the rest of the platform: identify the problem, fix it, measure the result.

Visibility measures whether your brand is mentioned. Sentiment measures how it's described when it is. A brand can have high visibility and poor sentiment, appearing frequently in AI responses but being framed as expensive, complex, or second-tier. Gauge tracks both metrics separately so you have a complete picture of your AI presence, not just a mention count.