Introducing AI Sentiment Analysis

What is Sentiment Analysis?

Omnia already shows you how often your brand appears in AI responses: your share of voice, your citations, how you benchmark against competitors.

But visibility and perception are two different things. A brand can show up in every AI answer and still lose the conversation. AI models don't just mention brands. They evaluate them. They form views on your pricing, your product, your customer service, your reputation, your values, and how you compare to everyone else in your category. And those views influence what they recommend.

Sentiment Analysis is how you find out what those views are.

It breaks down AI responses at the feature level, showing you where AI praises your brand, where it criticizes it, and how that compares to your competitors, side by side.

Think of visibility tracking as knowing whether you're in the room. Sentiment Analysis tells you what the room thinks of you.

Some Context Before We Continue

This is a first version. Sentiment Analysis is available today at the topic, brand, and prompt level. Insights don't incorporate it yet. There is more to build, and we know it.

We could have waited and shipped everything at once. We chose not to, because what's live today is already genuinely useful and we'd rather you get value from it now than wait for a bigger announcement that's still months away.

Each time sentiment data appears somewhere new in Omnia, it will do more. That's the pattern we're committing to.

How It Works

Omnia runs structured queries across AI engines and analyzes how each model describes your brand across specific dimensions: pricing, product, customer service, reputation, values, and how you compare to everyone else in your category.

For each feature, you get a score based on how AI models actually talk about your brand. You see where you're being endorsed, where you're being undermined, and where competitors are getting credit you're not.

The core loop is simple: Track prompts, analyze sentiment by feature, benchmark against competitors, act on the gaps.

What Sentiment Analysis Actually Measures

Feature-level scores. Sentiment is broken down by product dimension, not just overall brand impression. Knowing that AI has a positive view of your brand in aggregate tells you almost nothing. Knowing it consistently underrates your onboarding while praising a competitor's tells you exactly where to focus.

Endorsement and criticism counts. For each feature, you see how many times AI responses actively praised or undermined your brand. Volume matters. A single negative signal is noise. A pattern is a problem worth fixing.

Competitor benchmarking. Your sentiment scores sit next to your competitors', feature by feature. You can see where you lead, where you trail, and which gaps a competitor's content is quietly feeding into AI answers.

Shifts over time. Net sentiment scores are tracked over time, so you catch perception changes before they compound into something harder to fix.

Turning Perception Data Into Action

Knowing how AI sees your brand is only useful if it tells you what to change.

Sentiment data points to specific content and positioning decisions. If AI consistently underrates a feature you're strong on, the gap is usually a content problem: the right sources aren't feeding that signal into AI answers. If a competitor is winning a feature where you're objectively comparable, their positioning is doing work that yours isn't.

Sentiment Analysis surfaces those gaps. What you do with them is up to you, and in future versions of Insights, Omnia will start connecting that data directly to recommended actions.

How to Get Started

Sentiment Analysis is available now in your prompt panel.

1. Open Omnia and go to the Sentiment tab to get a high-level read on how AI is perceiving your brand right now.
2. Drill into any prompt you're monitoring and open its Sentiment tab for a more granular view.
3. Review feature-level scores and endorsement counts for your brand and your competitors, side by side.

The more prompts you analyze, the clearer the pattern becomes: where your brand consistently wins, where it consistently loses, and which features are most worth going after.

Questions or feedback? We'd love to hear how it's working. Reach us at hello@useomnia.com.