Beyond Mentions GEO resources

If you found us through AI, these resources explain what it probably understood.

Visibility is not only won through brand mentions.

A buyer does not only ask ChatGPT who exists in a market. They ask which criteria to use, which proof to verify, which risks to avoid and which suppliers to compare. That is where visibility becomes decisional.

After the citation What AI must understand before recommending
  1. GEO is not limited to a brand citation.
  2. AI recommends from criteria and evidence.
  3. A brand wins when its category is understood at the right level.

These guides start from concrete situations where a brand is visible, but not yet chosen.

GEO guides

What changes when your buyers go through AI.

Once the buyer asks ChatGPT to frame the need, the issue becomes concrete: are you cited, with which criteria, in which category, and with what evidence against competitors?

Market criteria

How do ChatGPT and LLMs recommend a company?

They do not apply the same grid to a local service, intellectual profession, SEO agency or complex B2B supplier.

GEO visibility

Why am I cited by ChatGPT or Perplexity but not converting?

Because a citation says nothing about the role AI assigns you in the comparison: favorite, generic alternative, premium supplier or simple source.

Decision-led GEO

What happens after brand citations?

A citation becomes useful only if AI compares you with the right criteria, proof and category framing.

B2B buying

How do ChatGPT, Perplexity and LLMs influence B2B buying?

It intervenes before the first sales conversation: need framing, qualification criteria, questions to ask and initial shortlist.

Shortlist

How does AI build a supplier shortlist?

It aggregates available evidence, weights implicit criteria and favors companies whose positioning is easiest to understand.

Tenders

Do LLMs like ChatGPT change tenders?

Yes: they can under-specify a request, omit critical standards or turn a technical advantage into a secondary option.

Premium offer

Why is my premium offer commoditized by AI?

When your differentiating criteria are not documented clearly enough, AI places you in a simpler and less demanding category.

Recommendation

Why does AI recommend some providers over others?

Because it favors the most defensible options: clear category, explicit criteria, available proof and corroborated sources.

Long cycle

Does GEO work for long sales cycles?

Yes, but its impact appears before the lead: buying criteria, shortlist, objections, expected proof and first-conversation quality.

Understanding

ChatGPT, Perplexity, Gemini: how do I know if AI really understands my offer?

Test the category, associated competitors, reused criteria, cited proof and the cases where AI recommends or excludes the offer.

Reading path

Connect the buyer question to your presence in the AI answer.

  1. 01

    See what the buyer asks AI

    Before searching for you directly, the buyer may ask ChatGPT to frame the criteria, standards, risks and suppliers to consult.

    Read the criteria shift
  2. 02

    Understand how your brand appears in that framing

    Being cited is not enough. You need to know whether AI associates you with the right criteria, evidence and level of rigor.

    See category compression risk
  3. 03

    Correct what AI does not understand yet

    Move from simple presence in answers to measurable presence in criteria, proof and shortlists.

    Read the decision-led method
Go deeper

Go deeper when you need to measure or correct.

Some resources explain why AI simplifies categories. Others show how to measure decision presence or correct the evidence AI fails to reuse.

Key resources

Read these to understand criteria, shortlist and measurement.

AI decisions · White paper · Awareness

Before the tender: how AI buying criteria form

The Silent Shift: why AI Buying Criteria now form before the first sales interaction, and how to regain control.

Method · Framework · Positioning

GEO: what happens after brand citations?

Brand citations are a first GEO signal, but they do not show whether AI recommends your offer with the right criteria, proof and category framing.

Research · Brief · Statistical brief

Category Compression Risk: when AI puts your offer in the wrong box

A Beyond Mentions brief on category compression: an offer can be visible in AI answers while being understood through a category that weakens its value.

Research · Brief · Statistical brief

Beyond Traffic: measuring Decision Presence before clicks

A Beyond Mentions brief on pre-commercial metrics: shortlist inclusion, proof reuse, category fit and Decision Share of Voice measure decision presence before traffic.

Research · White paper · Exploratory study

Pre-launch GEO: how LLMs compress B2B categories

A Beyond Mentions exploratory study of 4,320 Perplexity sonar answers: the risk is not only invisibility, but being understood through the wrong category.

Research · Brief · Statistical brief

Stable Claims Are Not Enough: why unstable signals reveal the real gaps

A Beyond Mentions brief: in the three-day Observatory wave, stable claims are not enough; unstable signals reveal documentation gaps and positioning risks.

Research · Study · Retrieval vs Citation

Why AI often cites your least visible pages in search

An investigation across three independent verticals (health YMYL, trades and construction, employment law): the pages that win AI citations are not the ones that dominate the SERPs. A Retrieval ≠ Citation model, Intent Match, and the Citation Efficiency metric.

GEO guides · Article · GEO guide

Why am I cited by ChatGPT or Perplexity but not converting?

Being cited by ChatGPT, Perplexity or an LLM is not enough if AI compares your offer on the wrong criteria, places you in the wrong category or fails to reuse your differentiating proof.

All resources

Explore by need: understand, measure, correct.

Measure how AI already understands your market.

A short diagnostic identifies category compression, documentation gaps and criteria that influence the decision.