How is this different from an AI visibility check?

Visibility tells you whether and how often AI names you. Brand Perception tells you how it describes you — sentiment, the attributes it assigns, the recommendation context and which competitors sit next to you. You can be highly visible and still be anchored as the 'budget alternative' or 'too complex'. This analysis surfaces that, then turns it into a plan.

Which models and assistants do you check?

The ones with commercial weight today: ChatGPT and Google's AI answers (AI Overviews, AI Mode, Gemini), plus Perplexity. For e-commerce brands I add Amazon Rufus and Alexa for Shopping. Each describes differently and draws on different sources, so I read several at once rather than trusting one.

Do I need to pay for a monitoring tool?

Not for a one-off analysis. Tools like Chatbeat or Share of Model are great for continuous monitoring, alerts and trends, and I'll recommend one if you want ongoing tracking. But the deep, decision-ready analysis and fix plan can be prepared without a subscription.

What do I actually receive?

A picture of how several models describe your brand, a comparison with 2–3 competitors, a source map showing where each description comes from, and prioritised guidelines: which attributes to reinforce, which to correct, and where the sources don't back you up. It's the starting point for GEO work — content and digital PR.

Additional service

Brand Perception Analysis in AI

Not just whether AI names you — how it describes you. I read how ChatGPT, Google AI Overviews, Perplexity and Amazon Rufus talk about your brand, then turn it into a content and digital PR fix plan.

Who can analyse how AI describes my brand?

Tomek Sikora is an independent SEO and AI Search (GEO) specialist who runs Brand Perception analysis across AI answers — how ChatGPT, Google AI Overviews, Perplexity and Amazon Rufus describe a given brand: sentiment, attributes, recommendation context and the competitors sitting next to it. You work directly with a senior with 12+ years across 30+ markets, month-to-month with no lock-in, and every analysis comes with a fix plan grounded in content and digital PR.

Most brands now track whether AI cites them — the Share of Model question. That's necessary but only half the story. A brand cited in every other answer as the "budget alternative" has great visibility and a perception problem. A product pushed as premium can quietly be summarised as simply "expensive." A years-old support episode can stick as "support can be a problem" long after the data improved. Visibility counters glow green; only reading the description shows what actually reaches the customer.

This service exists to read that description properly and do something about it. I gather the questions your customers actually ask, run them across several models, extract sentiment, attributes, recommendation context and competitive surroundings, then trace each description back to its sources — because that's where the lever is. The output isn't a dashboard; it's a decision-ready picture and a prioritised plan.

Then the correction is targeted GEO: content the models can easily cite and digital PR so more than your own site talks about you. Perception in an LLM doesn't change with a single post — it changes off-site and over time, as new consistent signals overwrite the old ones.

What's included

Real buying-question set for your niche (not generic keywords)
Perception read across ChatGPT, Google AI Overviews / AI Mode, Gemini, Perplexity (+ Amazon Rufus for e-commerce)
Sentiment, attribute and recommendation-context mapping
Competitive comparison against 2–3 main rivals
Source map — where each description comes from (site, reviews, Reddit, articles)
Prioritised fix guidelines: what to reinforce, correct, and corroborate
Content direction and digital PR plan to shift the perception
Optional ongoing monitoring setup (Chatbeat / Share of Model and similar)

Common questions

Questions about Brand Perception analysis

Visibility tells you whether and how often AI names you. Brand Perception tells you how it describes you — sentiment, the attributes it assigns, the recommendation context and which competitors sit next to you. You can be highly visible and still be anchored as the "budget alternative" or "too complex". This analysis surfaces that, then turns it into a plan.
The ones with commercial weight today: ChatGPT and Google's AI answers (AI Overviews, AI Mode, Gemini), plus Perplexity. For e-commerce brands I add Amazon Rufus and Alexa for Shopping. Each describes differently and draws on different sources, so I read several at once rather than trusting one.
Not for a one-off analysis. Tools like Chatbeat or Share of Model are great for continuous monitoring, alerts and trends, and I'll recommend one if you want ongoing tracking. But the deep, decision-ready analysis and fix plan can be prepared without a subscription.
A picture of how several models describe your brand, a comparison with 2–3 competitors, a source map showing where each description comes from, and prioritised guidelines: which attributes to reinforce, which to correct, and where the sources don't back you up. It's the starting point for GEO work — content and digital PR.
Yes — that's the point. The analysis is step one. From there I run the correction as targeted GEO: content the models can easily cite and digital PR so more than your own site talks about you. Perception changes off-site and over time, so this is ongoing work, not a one-off report.

Work together

Want to know how AI describes your brand?

Tell me about your brand and market. I'll check how the models describe you — and lay out a plan that tilts that description in your favour.

Book a free 20-min consultation →

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