GEO FOR b2b
An AI agent is already selling for you.
Train it
The B2B buying process has changed. Today’s buyer completes 70-80% of the evaluation before contacting a supplier, and increasingly this phase takes place through generative AI systems. ChatGPT to build shortlists. Claude to assess capabilities. Gemini to compare solutions.
In practice, AI is now doing the selling for us. The decision-making process has changed: Bliss helps B2B organisations master this market revolution.
If your company does not appear in AI answers to these queries, it does not exist in the buyer’s decision-making process. You do not even get the chance to be excluded from the shortlist: you were never on it.
The context
The B2B buying process in the generative AI era
B2B buyers have always researched thoroughly before contacting a supplier. In recent years, however, the nature of that research has changed. Where they once searched on Google, read industry reports or asked colleagues for references, today using generative AI systems has become the norm when comparing solutions or validating options.
According to several studies on B2B buyer behaviour, 70-80% of the decision-making journey is completed before first contact with the supplier. In the past, this meant searching on Google and reading content. Today it means conversations with AI systems. The supplier cited in these conversations enters the decision-making process before it is even contacted.
70–80%
of the B2B decision-making process completed before first contact with the supplier
78%
Claude
Definition of the problem and requirements
The buyer defines what they are looking for. They use AI to structure requirements, understand the options available on the market and grasp the terminology of an unfamiliar sector.
Supplier research and longlist building
The buyer asks AI for a list of suppliers. Those who appear at this stage make the longlist. Those who do not appear do not exist.
In-depth evaluation and shortlist
The buyer uses Google to look more closely at the suppliers identified by AI — searching for case studies, references, content. They return to AI for specific comparisons between the finalists.
Validation of capabilities and references
Specific validation query. Claude is the system most used at this stage by senior professionals.
First contact with the supplier
Only at this point does the buyer contact the supplier. They already have a formed opinion, built largely through AI systems. A supplier that did not appear at earlier touchpoints faces a buyer already leaning towards its competitors.
The segment with the highest impact
Why GEO matters more in B2B than in B2C
GEO has an effect across every segment, but B2B is where the impact is greatest. The reason lies in the nature of the decision-making process: complex purchases, multiple decision makers, long evaluation cycles, high risk aversion. In this context, presence in AI answers builds trust, creates authority and lifts the brand to a privileged position in the shortlisting process.
B2B · maximum GEO impact
Why GEO is decisive
- Long buying cycle: more AI touchpoints
- Group decision: every stakeholder uses AI
- High perceived risk: more pre-contact research
- Claude used by senior professionals and managers
- Verifiable case studies = high AI credibility
- The first supplier on an AI shortlist often wins
- Contract value justifies GEO investment
B2C · significant GEO impact
How it differs
- Short cycle: fewer AI touchpoints
- Individual decision: a single user
- Low risk: less pre-purchase research
- ChatGPT more relevant than Claude
- Reviews and ratings more decisive
- Brand awareness as important as citation
- High volume offsets low unit value
The value of a B2B client (often hundreds of thousands of euros in annual contracts) justifies a far higher GEO investment than in B2C. If a single citation in Gemini’s AI Overviews or in a Claude response brings in a new client, then the entire investment will have paid for itself from day one.
The sources that matter
Where AI systems learn
about a B2B company
The sources relevant to B2B GEO differ greatly from those in B2C. A B2B buyer assessing a supplier looks for different signals from the end consumer, so the sources that AI systems use to build a B2B company’s profile reflect these criteria.
Crunchbase
Critical
LinkedIn Company
Critical
Verifiable case studies
Critical
Business and trade press
High
Wikipedia and Wikidata
High
Original papers and research
High
B2B review platforms
Media
Case study
How Bliss built its own presence in AI answers
We have developed a proprietary approach to building presence in generative AI systems, and we applied it to ourselves before offering it to our partners.
When we started, there were just 10 active referring domains, no coverage in national media and no Wikipedia entry; ChatGPT, Gemini and Claude did not cite Bliss in any relevant context.
Since then we have built a network of editorial citations that AI models read as a signal of authority. La Repubblica has written about Bliss twice. La Stampa, Il Messaggero, Milano Finanza, Engage, Startup Italia. Today blissagency.it appears in ChatGPT, Gemini and Perplexity answers to strategic industry queries (“best branding agencies Italy”, “luxury communications agency Rome”, “GEO consultancy Italy”). And all this because AI systems reached that conclusion by analysing millions of sources.
the method
Five phases,
to build your B2B company's AI presence
B2B GEO requires a different approach from B2C GEO. Optimising for citation volume is pointless. The real key lies in expertise and in presence on specific touchpoints. To build an effective AI presence, Bliss follows a five-phase method.
How does AI describe you compared with your direct competitors?
The starting point is mapping competitive AI presence by identifying the B2B industry prompts that active searchers send to the three main AI systems (ChatGPT, Gemini, Claude). The result shows exactly where the brand sits in the AI's mind during the buyer's shortlisting phase, and where the gaps lie that must be closed to make the shortlist before first contact.
Organization schema with expertise, typical clients, certifications.
For a B2B company, the Organization schema requires specific fields that B2C GEO does not consider: knowsAbout with declared areas of expertise, hasCredential for certifications and awards, memberOf for trade associations, and a precise areaServed by geographic market and sector. These fields determine which category queries AI models consider the brand relevant for, and which queries it is not even evaluated for.
Case studies are the proof of expertise that Claude looks for.
Structured case studies for B2B GEO are documents with a stated methodology, verifiable metrics and specific sector context. We structure B2B case studies in a format optimised for AI citability, creating ideal content for Claude to use in its answers.
The publications buyers read and models learn from.
LLM Digital PR for B2B targets different sources from B2C: the business press (Milano Finanza, Il Sole 24 Ore), professional portals (Harvard Business Review Italia, Sole 24 Ore Management), papers and original research. We build B2B editorial presence through expert opinion on industry trends, original proprietary data and participation in industry reports that AI models will use as a knowledge base for their answers.
Monitor position in the AI shortlist for each target sector.
GEO monitoring for B2B focuses on competitive position in AI answers, establishing not only whether the brand is cited, but whether it is cited before or after direct competitors, how its expertise is described, and in which sectors it is recognised as a specialist. The data are then aggregated into a monthly Competitive AI Score.
FAQ
Frequently asked questions on GEO for B2B
Why is GEO particularly important for B2B companies?
The B2B buyer completes 70-80% of the decision process before contacting a supplier, and this phase increasingly takes place through AI systems. ChatGPT to build the longlist, Claude to validate capabilities, Gemini to compare solutions.
A B2B company that does not appear in AI answers to sector queries is excluded from the shortlist before it even has the chance to present itself. The value of a single B2B client justifies a significantly larger GEO investment than in B2C.
How do you build a B2B company's AI presence?
Through: a complete Knowledge Graph (Organization schema with expertise, typical clients, certifications), an up-to-date Crunchbase profile (the primary source for ChatGPT and Claude), editorial presence in the business press and sector-specific trade media, verifiable case studies with a stated methodology, and an active presence on LinkedIn.
Consistency of information across all sources is the fundamental requirement — contradictions between Crunchbase, LinkedIn and the website create ambiguity in the brand’s AI entity.
Is Claude more important than ChatGPT for B2B?
Yes, significantly. Claude is the most widely used AI system in professional and corporate settings: integrated into B2B workflows, used by managers for competitive research, adopted by procurement teams to evaluate suppliers. The demographic profile of Claude users matches the B2B buyer exactly: highly educated, in decision-making roles, used to structured research.
Owning Claude for sector-specific B2B queries often has more impact than owning ChatGPT, because its audience has greater purchasing power and stronger decision-making intent.
Do case studies help B2B GEO?
Case studies are one of the most powerful GEO tools for B2B. AI models, Claude in particular, favour sources with verifiable data and a stated methodology. A case study with measurable results, a specific sector, a described process and concrete metrics is exactly the type of content an AI model uses to answer questions about expertise.
Bliss structures B2B case studies with a specific schema for AI citability: a title combining sector and result, methodology in numbered steps, metrics in table format, factual conclusions.
How is the impact of GEO on the B2B pipeline measured?
B2B GEO measurement combines: AI Brand Mentions on sector queries (citation frequency in shortlisting responses), Competitive AI Score (position relative to competitors in comparative responses), AI referral tracking in GA4, and qualitative attribution of inbound contacts (asking leads how they found the company).
Bliss integrates this data with commercial metrics (number of qualified leads, pipeline value, close rate) in the monthly report to correlate GEO activity with business results.