Friction

AI Sentiment Analysis

Know how AI portrays your brand in every buying context.

Go beyond positive, neutral, and negative. Measure category-specific sentiment, recommendation status, reservations, and the exact AI response behind every score.

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ChatGPT
Gemini
Google AI Overviews
Claude
Perplexity

What shapes the score

One sentiment label is not enough

friction AI looks at the factors that shape trust and choice, then gives more importance to the ones that matter for your category and customer question.

01

Trust and safety

How credible, reliable, and low-risk the brand appears for the decision being made.

02

Solution fit

How well the product is portrayed as solving the specific need in the prompt.

03

Customer experience

What the answer implies about usability, service, support, and the ownership experience.

04

Market reputation

How AI frames the brand’s standing, credibility, and perception relative to alternatives.

Category-aware by design

Context changes what good sentiment means

Buyers judge sunscreen, enterprise software, and hotels differently. The analysis should too. friction AI interprets sentiment against the risks, expectations, and proof that matter for the category.

Beauty and personal care

Safety and suitability matter more

Ingredient concerns, sensitivity, product claims, finish, and everyday experience shape the interpretation.

B2B software

Risk and implementation change the score

Security, reliability, workflow fit, onboarding, support, and vendor trust become central.

Travel and hospitality

The experience is part of the recommendation

Service consistency, traveler fit, booking flexibility, location, and reputation carry different weight.

Sentiment and recommendation context

Read what AI tells the buyer to do

Tone alone can be misleading. An answer may portray your brand positively without recommending it, or mention a drawback while still choosing it. friction AI keeps portrayal, recommendation status, and visibility distinct but connected.

01

Not mentioned

The category is discussed, but your brand is absent from the answer.

02

Merely listed

Your brand appears without a meaningful reason for the buyer to choose it.

03

Actively recommended

The answer presents your brand as a suitable choice and supports that recommendation.

04

Advised against

AI identifies a warning, limitation, or mismatch that may push the buyer elsewhere.

The answer behind the score

See exactly why AI formed that impression

Track the questions your buyers ask, compare the models they use, and open the response behind every result.

01

Use your own prompts

Analyze sentiment around the decisions, objections, products, and audiences that matter to you.

02

Compare AI platforms

See how the same brand and question are interpreted by ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews.

03

Keep market context visible

Separate results by market and language so different audiences do not get blended into one conclusion.

04

Open the evidence

Read the original answer and see the recommendations, concerns, competitors, and category factors behind every score.

Custom prompts + Brand Audit

Follow today’s questions without losing the baseline

Your custom prompts track current products, objections, campaigns, and audiences. The Brand Audit keeps the weekly prompt set and measurement method consistent, while the results remain free to reflect real changes in AI answers.

Flexible

Custom prompt sentiment

Flexible, specific, and editable whenever the business changes.

Consistent

Brand Audit sentiment

The same curated questions and method each week, with results that can still change.

From score to explanation

Answer the questions behind your brand sentiment

01Why does AI portray our brand positively or negatively?
02Are we actively recommended or only mentioned?
03Which reservations could stop a buyer from choosing us?
04Which competitors are framed more favorably?
05How does sentiment change by model, prompt, or market?
06What exact answer produced the score?

FAQ

How AI brand sentiment monitoring works

What is AI sentiment analysis?

AI sentiment analysis shows how a brand is portrayed inside generated answers. friction AI looks at the language, recommendations, concerns, and category fit instead of assigning a generic positive or negative label.

How is this different from generic sentiment analysis?

Generic sentiment tools usually classify text as positive, neutral, or negative. friction AI judges the answer in the context of your industry, category, question, market, and buying decision, then shows what shaped the score.

How do sentiment and recommendation status work together?

They are separate measures shown together. Sentiment describes how the brand is portrayed when it appears. Recommendation status shows whether it is merely listed, actively recommended, or advised against, while Not mentioned is a visibility outcome.

Can we analyze sentiment for our own prompts?

Yes. Your custom prompt set is the primary tracking layer. Add and edit questions around products, audiences, objections, markets, and campaigns whenever your priorities change.

Can we see why a sentiment score changed?

Yes. Open the prompt details to read the original answer and see the recommendation, concerns, competitors, sources, and category factors behind the score.

How does the Brand Audit support sentiment tracking?

The Brand Audit keeps a consistent weekly prompt set and measurement method while your custom prompts change. Sentiment results can still move as AI answers, platforms, and public information change.

See what AI says, why it says it, and what buyers hear

Start with your own prompts and immediately see how AI portrays, recommends, and explains your brand.

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