Last verified: February 11, 2026
What's New
A recent update introduces a capability to track whether AI models speak positively about your brand. This feature allows B2B marketing teams to monitor how their brand is perceived across various AI-driven platforms. By analyzing sentiment in AI-generated responses, this tool provides insights into brand reputation and visibility in AI search recommendations. This addition addresses the growing need for brands to understand their positioning in AI-driven buyer journeys.
The capability leverages automated daily scans to assess brand mentions and sentiment across six major AI models, including ChatGPT, Claude, and Perplexity. By doing so, it offers a comprehensive view of how AI models discuss your brand, enabling you to make informed decisions about your marketing strategies.
Why This Matters
For B2B marketing teams, understanding how AI models perceive and recommend their brand is crucial. This update addresses a significant pain point: the lack of visibility into AI-driven brand sentiment. Previously, marketers had limited tools to gauge how AI platforms discussed their brand, often relying on anecdotal evidence or manual searches.
This capability enhances workflow efficiency by providing automated insights into brand sentiment, allowing teams to quickly identify and address negative perceptions or capitalize on positive mentions. It also supports strategic decision-making by offering a clear picture of brand positioning in AI-driven environments, which is increasingly important as AI continues to influence buyer decisions.
How It Works
The sentiment tracking capability operates through automated daily scans of brand mentions across six major AI models. It analyzes the sentiment of these mentions, categorizing them as positive, negative, or neutral. This information is then compiled into a report that provides actionable insights into brand perception.
By integrating this feature into existing workflows, marketing teams can seamlessly incorporate sentiment analysis into their strategic planning, ensuring that their brand maintains a positive presence in AI-driven conversations.
What to Consider
Integration with Existing Tools — Consider how this capability will fit into your current marketing technology stack. Ensure compatibility with existing systems to maximize efficiency and insights.
Data Accuracy — Evaluate the accuracy of sentiment analysis. Since this feature relies on AI-driven assessments, verify that the sentiment categorization aligns with your brand's perception goals.
Strategic Application — Think about how these insights can inform broader marketing strategies. Use the data to refine messaging, address negative sentiment, and enhance brand visibility in AI-driven environments.
Sources
- AI Sentiment Analysis: Understanding the Basics
- The Role of AI in Modern Marketing
- How AI is Shaping Brand Perception