Sentiment

Sentiment shows how AI systems describe brands in your tracked prompt results. It goes beyond visibility and answers a different question:

When AI mentions us or our competitors, is the framing positive, neutral, or negative?

What Sentiment measures

Finseo analyzes competitor and brand mentions in AI answers and extracts:

Sentiment score
Positive, neutral, and negative phrase counts
Aspect-level scores
Criticisms and risks
Awards and “best for” claims
Reputation trend over time
Comparison win rate where comparative claims are available

Brands tab

The Brands tab is a leaderboard of brands mentioned in your tracked prompts. It shows:

Mentions
Average sentiment score
Positive/neutral/negative distribution
Strongest aspects
Weakest aspects
Your own brand marker
Reputation trend where available

Use it to compare your brand against competitors in the same prompt set.

Scorecard tab

The Scorecard tab compares brands across aspects such as:

Quality
Price
Value
Performance
Features
Reliability
Design
Support
Service
Ease of use
Availability

Green cells mean AI framed the brand positively for that aspect. Red cells mean the framing was negative. Neutral cells are factual or mixed.

Criticism tab

The Criticism tab surfaces negative phrases found in AI answers. Each row can include:

Brand
Aspect
Negative phrase
Score
Model
Source domain where available
Prompt/result context

Use this to find reputation risks and repeated objections, for example:

"expensive for smaller teams"
"limited integrations"
"poor availability"
"not ideal for enterprise use"

Awards tab

The Awards tab shows “best for” style claims and recommendation labels extracted from AI answers. Examples:

Best for agencies
Best budget option
Best for enterprise
Best for ecommerce
Best for beginners

This helps you see which buying situations AI associates with each brand.

Filters

Sentiment supports the same analysis filters as other tracking views:

Date range
AI model
Tags

Use tags to compare prompt groups such as:

branded
unbranded
comparison
product-category
de
us

Where the data comes from

Sentiment is generated from tracked prompt results. When a prompt runs, Finseo analyzes the AI answer, extracts brand mentions, and stores sentiment phrases and aspect scores. If a prompt result has no extracted sentiment phrases, it may still count as a mention, but it will not contribute as much to aspect-level sentiment views.

How to improve sentiment data quality

Track enough prompts in each market and category.
Include comparison and recommendation prompts, not only brand prompts.
Use tags to separate prompt groups.
Enable the models your audience actually uses.
Review the Criticism tab regularly and update content to address repeated objections.
Use Awards to see where your positioning is already strong.

Visibility vs sentiment

Visibility and sentiment are different:

Metric	Question
Visibility	Does AI mention the brand?
Position	Where does the brand appear compared with competitors?
Sentiment	How positively or negatively does AI describe the brand?
Awards	What use cases or “best for” labels does AI assign?
Criticism	What negative claims or objections appear repeatedly?

A brand can be highly visible but framed negatively. It can also be mentioned less often but with stronger sentiment. Use both views together.

​Sentiment

​What Sentiment measures

​Brands tab

​Scorecard tab

​Criticism tab

​Awards tab

​Filters

​Where the data comes from

​How to improve sentiment data quality

​Visibility vs sentiment