B2B buyers usually research problems before speaking to a supplier. They compare options, read technical information, check company websites, and look for signals of expertise. In March 2026, Gartner reported that 67% of B2B buyers prefer a rep-free buying experience.
The same survey found that 45% of B2B buyers used AI during a recent purchase, suggesting that AI is becoming part of the research and evaluation process before direct sales contact. For companies, this makes clear and credible public information more important. If buyers are researching more independently, company content needs to answer practical questions before the first conversation.
From SEO to GEO
As buyers use AI tools alongside search engines, marketing discussions are expanding from SEO to GEO. SEO, or search engine optimisation, focuses on helping content appear in traditional search results. GEO, or generative engine optimisation, focuses on making company information clear, structured, and credible enough to improve its chances of being understood, cited, or mentioned in AI-generated answers.
This does not mean abandoning SEO or creating content only for AI tools. It means making information more specific, useful, and easy to interpret. The same content that helps a buyer understand an application, limitation, or technical requirement can also help AI tools interpret the company more accurately.
Use customer questions and concerns as content signals
A CRM is often treated as a place to record customer activity. But it can also show what customers are trying to understand before they make contact or move forward. Repeated questions, objections, and hesitation points in calls, emails, quotes, and service cases are useful signals. They show where buyers may need clearer information earlier in their research.
If several customers ask about the same application, product comparison, delivery constraint, installation condition, compatibility issue, or technical limitation, that topic may deserve a short explanation. This can become a website FAQ, newsletter article, LinkedIn post, or sales support note.
This matters because AI-assisted search depends on available public information. If a company’s public content is limited to general phrases such as “quality solutions” or “reliable partner,” it may not show the real strengths of the company. Clear explanations of applications, limitations, use cases, and common questions give both buyers and digital tools better material to work with.
How the content is presented also matters. For AI-assisted search, useful content should be easy to interpret: clear headings, direct answers, practical examples, and enough context to explain when something applies or does not apply. A short FAQ, comparison page, application note, or technical explanation can be more useful than a general marketing page.
Tip: Use CRM tags or notes to mark recurring questions, objections, and reasons for hesitation. Over time, this makes it easier to see which topics should be explained more clearly. Review lost opportunities and stalled deals in the CRM. Look for repeated reasons why customers hesitated. These topics often make strong educational content.
Keep the focus on useful information
AI search is still developing, so companies should not treat GEO as a replacement for SEO, reputation, relationships, or technical consultation. The practical starting point is simpler: understand what buyers repeatedly want to know, and make those answers more structured and easier to find.
CRM data can help with that. It shows the questions, concerns, and hesitation points that already come up in real customer conversations. When companies turn those patterns into clear public explanations, they make their expertise easier for buyers to find, understand, and trust.