How to get mentioned by ChatGPT

A Practical AEO Playbook for B2B and SaaS

AI-driven discovery is no longer experimental. Tools like ChatGPT, Perplexity, and Google AI Overviews are already shaping how decision-makers research software, services and vendors. For B2B and SaaS companies, this introduces a new discipline: Answer Engine Optimization (AEO) — the practice of optimising content so it is retrieved, trusted, and cited inside AI-generated answers. This guide distils what actually works today, grounded in public research, industry case studies, and first‑party insights from GeoBuddy.

Quick takeaway (scan first)

What consistently improves AI visibility:

• Question-led content beats keyword-led pages
• Complete topic coverage beats isolated blog posts
• Help docs and FAQs outperform marketing copy
• Off-site mentions (forums, videos, reviews) matter
• AI traffic is often low-volume but high-intent
• Last-click analytics frequently miss AI’s influence

How AI search really works (and why this matters)

Most modern AI systems rely on Retrieval‑Augmented Generation (RAG).

RAG (definition): a method where an AI model retrieves relevant external content first, then summarises or synthesises an answer based on those sources.

This means AI answers are not random. They are assembled from content that appears:

• relevant to the question
• clear and unambiguous
• consistent across multiple sources
• trustworthy based on external validation

Implication: if your content is retrievable, understandable, and corroborated, you can influence whether your brand is mentioned.

Step 1: Optimise for questions, not keywords

AI prompts are phrased as questions. Your content should be too.

High-value question sources inside your company

• Sales objections (“Is X better than Y?”)
• Demo and onboarding questions
• Support tickets and help desk logs
• Paid-search queries rewritten in natural language

Why this works: research from HubSpot and Seer Interactive shows AI tools preferentially surface content that directly answers user prompts, rather than content optimised only for keyword density.

Practical example:
Instead of publishing “CRM features overview”, publish:

• “Is this CRM suitable for small remote teams?”
• “How does it compare to HubSpot?”
• “What are the limitations?”

Each answered question becomes a potential inclusion point for AI.

Step 2: Build topic hubs not isolated pages

AI systems favour content that:

• covers a topic comprehensively
• anticipates follow-up questions
• connects related subtopics clearly

How to structure a topic hub

1. Choose one core buying topic
2. Create a pillar page explaining the topic end-to-end
3. Add subpages for comparisons, FAQs, use cases, and limitations
4. Interlink everything logically

Industry insight: content teams analysed by HubSpot found that structured topic coverage is more likely to be retrieved and summarised accurately by AI systems than fragmented blog strategies.

Rule of thumb: one strong topic hub beats ten shallow posts.

Step 3: Treat help content as a strategic asset

Help centres, documentation, and FAQs often contain:

• precise language
• real-world scenarios
• high-intent phrasing

These traits make them ideal for AI retrieval.

Best practices

• Keep help content on your primary domain
• Avoid blocking AI crawlers unnecessarily
• Expand FAQs intentionally using real user language
• Add clear headings and Q&A formatting

Observed pattern: multiple AI visibility studies show help docs are cited more frequently than blog posts — yet are rarely optimised.

Step 4: Earn off-site mentions AI can verify

AI systems cross-check information across many sources, including:

• Reddit and professional forums
• YouTube videos and transcripts
• Niche blogs and comparison articles
• Public documentation and reviews

Research from Ahrefs and Awario indicates that mentions — even without backlinks — increasingly influence AI discovery.

What actually works

• Participate genuinely in community discussions
• Publish transparent comparisons
• Collaborate with niche reviewers
• Encourage users to reference your product publicly

Authenticity consistently outperforms scale-driven spam.

Step 5: Measure “share of answer”, not rankings

Traditional SEO tracks rankings. AI discovery requires a different lens. Share of Answer (definition): how often your brand appears in AI-generated answers for relevant questions compared to competitors.

What to track

• Frequency of mentions across AI tools
• Consistency of positioning
• Which pages or sources are cited

Studies from Seer Interactive and Microsoft Clarity show AI referrals are often undercounted due to last-click attribution models.
Tip: include “How did you hear about us?” with an “AI assistant” option to capture early signals.

What the data shows (real-world evidence)

Ahrefs: AI referrals remain a small share of traffic but contribute a disproportionately high share of signups for SaaS and subscription businesses.
Seer Interactive: B2B visitors arriving via AI often convert more efficiently due to later-stage intent.
Microsoft Clarity: AI-referred visitors show higher conversion rates for demos and signups.
Adobe: AI-driven referral traffic in the US grew more than 10× year-over-year.

Key insight: AI visibility is a quality channel before it becomes a volume channel.

GeoBuddy insights (first-party observations)

Across AI visibility audits performed with GeoBuddy, we consistently observe:

• AI tools citing outdated or secondary sources
• Help centres outperforming blogs in AI answers
• Inconsistent messaging leading to partial or incorrect summaries
• Small structural changes significantly improving mention consistency

The GeoBuddy methodology

GeoBuddy turns AI visibility into a measurable system:

1. Discoverability mapping
2. Source validation analysis
3. Consistency scoring across platforms
4. Execution support (we fix what we find)
5. Share of Answer tracking over time

This moves AI visibility from guesswork to a repeatable growth channel.

Key terms (quick glossary)

AEO (Answer Engine Optimization): Optimising content to be selected and cited in AI-generated answers.
RAG (Retrieval-Augmented Generation): AI retrieves external content before generating responses.
AI Visibility: How often and how accurately your brand appears in AI answers.
Share of Answer: AI-era equivalent of search rankings.

Final takeaway

AI systems are becoming the first stop in the B2B buying journey. The brands that win won’t chase traffic — they’ll earn trust, clarity and consistency where decisions are formed.

Author credentials

This article was written by the team behind GeoBuddy, a platform focused on AI visibility and discoverability for B2B and SaaS companies. We help teams audit, fix, and improve how they appear in AI-generated answers — and support execution, not just strategy.