Welcome! 👋 The B2BFYI newsletter is for complex B2B marketers looking for a competitive edge. Covering brand, content, technology and lead generation, B2BFYI serves as a guide to building a more effective marketing strategy.
B2BFYI is written by industry veterans Chris Bennett (Strategy), Geoff Bretherick (Creative) and Philip Bennison (Tech), and published bi-weekly. You can sign up here to get issues straight to your inbox.
In this newsletter:
The invisible excellence problem
Part 1: The problem
Part 2: What’s going on?
Part 3: The fix
Step 4: Measurement + ROI
The Breakdown: Semrush’s search impact study
Templates & resources (for subscribers): AI Overview page template
FYI: What's going on with AI and SEO?
You've probably seen loads of new acronyms like AIO, AEO or GEO pop up, likely in low-effort cold emails that promise you some golden buffet of sales results.
Here's a take that will make it make sense.
See it all as modern content optimisation.
SEO as a discipline has moved forward, like it has done every few months since it became its own industry way back in ~1997. This is simply the newest adaptation to how humans are using digital interfaces to find information.
The catch? The AI models do things with information that extend beyond the classic industry definition of what SEO is.
What should happen: it all gets merged into a new, modern SEO where the definition of SEO is extended.
What's actually happening: the industry doesn't seem to want to do a wholesale update of the definition of SEO, and instead prefer to create new disciplines with their own clear definitions. These are GEO and AEO. Anything to latch onto something new and shiny to sell you. Annoying. But is there more to it?
Quick recap: SEO means Search Engine Optimisation. We all know that. The trick here is that since the mid-90s, the term "search engine" has specifically referred to a technology that indexes and retrieves pre-existing information. For example, a page of your lovely corporate website showing up on Google.
AI platforms work differently.
The key differentiator is in how information is manifested. With SEO it is retrieved from existing sources. With AI tools it is generated - assembled in an original manner, based on previously gobbled up data that the AI model was trained on.
And this comes in two flavours.
1) A generative engine (GE) like ChatGPT, Claude or Google's Gemini, will generate an answer from nothing based on the data it was trained on.
2) An answer engine (AE) like Perplexity will perform a live web search and use generative AI to summarise and refine the results for you. Think of this as a hybrid between a Search Engine and a Generative Engine.
So if you want to optimise your content for all three methods available to users wanting to find your business, you'd need to optimise for search, generative AND answer engines. Hence the terms: SEO, GEO and AEO.
💡 Tip: Some folks like to talk about AI optimisation with the AIO acronym. This is getting into the classification weeds. GEO + AEO are subsets of AIO. Let's wait for the dust to settle on the battle for terminology.
This list of acronyms is only likely to grow in the future as technology continues to rapidly evolve, which is why - for marketers - it's now easier to just think of it all as simply content optimisation.
GEO and AEO should become just another part of your process for preparing a piece of content for publication and distribution.
SEO agencies have to decide if they want to sub-specialise, or be Content Optimisation generalists.
To summarise, AIO is here to stay - and it’s still not fully figured out, nor is it clear how it will evolve as a discipline. Let’s also not forget just how rapidly AI technology is progressing. Now let’s jump into what can happen if you ignore it.
The Invisible Excellence Problem
Your business might be the best-kept secret in professional services…but if you’re literally invisible to the 60% of prospects now using AI to find solutions? Well, it’s going to be rough getting onto vendor shortlists.
The truth is a little uncomfortable. ChatGPT, or any of the AI platforms, don't care about your 30-year track record if they can't find you. This 4-part framework shows you exactly how to fix that invisibility problem and become the answer AI gives when prospects ask for help.
🚩 Part 1: The problem
What exactly is the Invisible Excellence Problem?
It's a stark reality check for B2B marketers. Your firm has deep expertise, great case studies, and a long list of happy clients. But when 94% of B2B buyers use AI tools like ChatGPT to research vendors (Green Hat/6sense, 2025), and your brand appears in zero results - you have an Invisible Excellence Problem.
Here's what's happening. According to research analysing 800,000+ AI citations, ChatGPT includes brands in only 26% of responses. Google AI Overview performs slightly better at 37%, while Perplexity sits at 31% (ABNewswire/Ocampo, 2025). That means roughly 70% of the time, when buyers ask AI about solutions in your category, you don't exist.
The impact is brutal. TrustRadius found that 72% of buyers now encounter Google's AI Overviews during research, with 90% clicking through to cited sources (2025 B2B Buyer Research). When you're invisible to AI, you're invisible to buyers.
Real examples show the damage:
Chegg lost 49% of traffic after AI disruption
The Planet D shut down following a 90% traffic collapse
DMG Media documented up to 89% click-through rate declines
Why is this happening now?
Three converging forces:
Buyer behavior shift: 89% of B2B buyers use generative AI during their buying journey (Forrester, 2024)
AI as primary research: 50% now start their journey in ChatGPT instead of Google - a 71% increase in just four months (G2, 2024)
Trust in AI is growing: 80% of buyers trust AI-generated content at least sometimes, up 19% year-over-year (TrustRadius, 2025)
The issue? Only 44% of B2B marketers are investing in Generative Engine Optimisation (GEO), despite 94% of buyers using LLMs to "validate, summarise and confirm" decisions (Green Hat, 2025).
💡 TIP: I posted a full overview of what all the AI SEO terms are on LinkedIn.
🤔 Part 2: What’s going on?
How do AI engines decide who's an expert?
AI visibility isn't about gaming an algorithm - it's about structured, authoritative content that LLMs can parse and trust. Research shows vendor blogs now account for 56% of B2B product citations in AI responses, outperforming "neutral" sources (Ocampo, 2025).
Here's what drives AI citations:
Content structure: Clear headers, FAQ formats, comparison tables
Data density: Complete product information, specifications, integrations
Recency: 79% of citations come from content published in the last two years
Accessibility: Ungated, crawlable content (not PDFs or gated assets)
Brand mentions: Consistent mentions across multiple authoritative sources
Why does traditional SEO fail for AI?
The fundamental difference is that SEO optimises for clicks, while GEO optimises for citations. As Latane Conant (CMO, 6sense) notes: "LLMs are fond of FAQs, comparison tables, glossaries and clear headers - and so are buyers."
Traditional SEO focuses on:
Keyword density
Backlinks
Page authority
Click-through rates
GEO requires:
Semantic clarity
Factual density
Cross-platform presence
Citation worthiness
What's the real business impact?
Analysis of 30,000 AI citations found that 10% more reviews correlates with 2% more AI citations. In high-volume categories, that 2% shift fundamentally alters competitive positioning when hundreds of AI-driven queries happen monthly (Profound/G2 analysis).
Consider the cascade effect:
Day 1: Buyers create shortlists of 4-5 vendors, with 76% of the time the #1 ranked vendor winning (Green Hat, 2025)
Selection phase: 94% use LLMs to validate decisions before any sales contact
Invisible brands: Never make the shortlist, losing before they know buyers exist
The financial impact can be severe. Recent data shows:
Average B2B deal cycles are now 3.8 months (6.6 for enterprise)
82% of buyers have a top service in mind when creating shortlists
70% go on to purchase that pre-selected service
If you're not in the AI-generated consideration set, you've lost 70% of deals before your sales team even knows prospects exist.
Why haven't more marketers adapted?
A dangerous disconnect exists here. While 96% of senior marketers claim to have "AI-searchable content," only 11% have actually optimised most of their content for AI discovery (10Fold, 2025).
Three barriers get in the way:
Measurement blindness: traditional analytics don't track AI citations
Resource allocation: 63% plan to invest in GenAI, but budgets remain flat
Knowledge gap: genuine GEO/AEO expertise is scarce and most agencies still push traditional SEO
What AI rewards (clarity, structure, accessibility) is what good B2B marketing always required. As Drew Neisser (CMO Huddles) observes: "Marketers are wasting millions on tactics buyers ignore, and with search shifting to LLMs, it's only going to get worse."
Part 3: The fix
Based on analysis of what's earning citations across AI platforms, here's your tactical playbook:
1. Audit your AI visibility (this week)
Open ChatGPT, Claude, Perplexity. Ask the questions your buyers ask:
"Best [your category] solutions for [industry]"
"Compare [your company] vs [competitor]"
"[Your category] pricing comparison"
Document where you appear (if at all) and what sources get cited. This baseline reveals your invisible excellence gaps.
💡 TIP: Want to ask AI more questions like these? Simply ask the AI for ideas! Prompt it with: “Give me 10 suggestions for questions to ask here to reveal differences between how you evaluate my business and a competitors, including the wider landscape.” ⚡
2. Create AI-optimised content architecture
Structure beats keywords. Ocampo's research shows AI needs "parseable, factual, comprehensive content." Transform your existing content:
Convert long-form content into structured FAQs
Build comparison pages (yes, including competitors)
Create dedicated "/ai-info" pages with clear headers and bullet points. Your content on this page should tell an AI platform very clearly what you are about and how it can best reference you in the results it presents
Add schema markup (Note: It’s contested whether Schema markup has an effect on AIO. My own take is that those results only account for LLM tokenisation, and not how the underlying data is processed and understood. So…Schema is still fine as far as I can tell.)
3. Ungate your best content
Painful but necessary. TrustRadius found 79% of AI citations come from openly accessible content. Your gated whitepaper on industry best practices? AI can't read it. Neither will your buyers when AI can't cite it.
Priority ungating targets:
Industry guides and frameworks
Product comparisons
Pricing information
Implementation methodologies
Customer success metrics
4. Accelerate review collection
Analysis by Kevin Indig tells us that more reviews = more AI visibility. But it's not just volume - it's velocity. Fresh reviews signal current market activity to AI models.
Review optimisation tactics:
Target 2-3 new reviews monthly minimum
Focus on detailed, use-case specific feedback
Encourage reviewers to mention your product on LinkedIn
Optimise review site profiles with demos and pricing
5. Build your "AI Inside" transparency kit
58% of buyers contact vendors early specifically to understand AI capabilities (Green Hat, 2025). If your business uses AI in your service delivery, create clear, ungated content covering:
AI feature capabilities
Data privacy/security protocols
Pricing implications
Training requirements
Integration specifications
Remember: You're not optimising for algorithms here - you're structuring information for AI-assisted buyers who need confidence in their shortlist decisions.
Part 4: The payoff
What results can marketers expect from fixing their invisible excellence?
Early movers are seeing dramatic shifts. Companies optimising for AI visibility report:
34% of qualified leads now coming from AI-native platforms (Transmission Agency, 2025)
436% conversion spikes from ChatGPT-driven recommendations
Pipeline velocity increasing as buyers arrive more educated
The compound effect is pretty powerful. As Sebastian Ocampo's analysis revealed:
Companies that understand how to structure content for citations are winning while competitors optimise for search rankings that matter less every month.
How do we measure AI visibility impact?
Shift from traditional metrics to AI-era KPIs:
Leading indicators:
AI citation frequency (target: 1,000+ monthly)
Share of voice in AI responses vs competitors
Branded query performance in LLMs
Review velocity and recency scores
Business impact metrics:
Lead quality scores (AI-sourced vs traditional)
Sales cycle compression
Win rates for AI-influenced deals
Pipeline contribution from "dark social" sources (ask your sales team to ask your customers where they heard about you from)
What's the first-mover advantage?
The window is closing fast. With only 11% of marketers having "most content" optimised for AI discovery (10Fold study, 2025), the opportunity remains massive. But as Ocampo warns: "Build content infrastructure now while adoption ramps, and you'll compound visibility as AI usage increases. Wait, and you'll be playing catch-up against competitors who already own the citations."
European markets have particular advantage. US buyer AI adoption (48%) far exceeds other regions (14%), creating a strategic window for early movers globally.
What happens if we don't act?
Oh, boy. The math doesn’t paint a rosy picture here. If 76% of B2B purchase decisions happen before sales contact (Green Hat, 2025), and you're invisible during AI-assisted research, you're eliminated before you know opportunities exist.
As one director told TrustRadius: "When making a large purchase, I want to hear directly from real people with experience using the product." But if AI can't find those experiences, neither can your buyers.
You have two choices: become visible to AI-assisted buyers now, or watch competitors who figured it out capture your market share. There's no middle ground in the age of AI search.
💡 TIP: For more specifically on Thought Leadership, read Issue #1: Why your thought leadership isn't leading anyone.
Real results: how AI search is already transforming professional services
We’ve read and analysed the report so you don’t have to.
While most businesses are still debating whether AI search matters, Semrush just dropped data that should end the conversation. They analysed over 500 high-value business topics to understand exactly how AI search is reshaping the professional services landscape.
The results are in. AI search visitors are worth 4.4x more than traditional Google visitors. They convert better. They're more qualified. And they're growing exponentially.
The content that wins in AI search doesn’t look much like traditional SEO winners. Pages ranking 21st in Google are getting cited more than pages ranking 1st. Wikipedia and Reddit are beating Fortune 500 websites.
This isn't some far-off future scenario, either. It's happening right now, and the data proves it.
Company: Semrush (Digital Marketing Platform)
Study scope: 500+ high-value digital marketing and SEO topics
Timeline: Historical data analysis with projections through 2028
Key findings with real metrics:
1. AI visitor value: 4.4x higher
AI search visitors convert at 4.4x the rate of traditional organic search visitors
Despite lower volume, the economic value is significantly higher
2. Citation patterns revealed
ChatGPT cites pages ranking 21+ in traditional search 90% of the time
Only 10% of citations come from top 20 Google results
50% of ChatGPT links point to business/service sites
3. Platform-specific insights
Quora is the most-cited website in Google AI Overviews
Reddit ranks second for citations
High-authority domains dominate AI citations
4. Traffic projections
AI search visitors expected to surpass traditional search by 2028
Current ChatGPT weekly active users: 800M (8x growth from Oct 2023)
💡 Note: Oh, and “traditional” SEO is still alive and well. If HubSpot - one of the biggest and best companies when it comes to creating great content - is dramatically and rapidly ramping up their own link-building efforts, you shoud stop and pay attention!
Chris Bennett
Head of Strategy @ Fablr | Marketing Strategist | Expert B2B Marketer | GTM, Demand Gen & Brand Growth Leader | MCIM
When not writing about marketing or advising clients, you can find dad-of-one Chris reading history, playing the piano, or keeping old age away in the gym.
Years in the trenches: 16
Favourite tool: Gemini
Common saying: “Move the needle.”
Favourite food: Chinese
Templates + resources
For subscribers only - links directly to these assets are available below the subscription break.
This month we have the following resources for you:
An AI overview page template: A quick start for putting together a new page on your website which will help inform AI platforms about your business.
AI overview page template
This template gives you a simple document that you can complete and then publish the information on your company website. We recommend a simple content page, something similar to your privacy page should do the trick. Once published, keep it updated and include a link in your footer with the link text: “AI Overview”.
You can find a link to the template here.
To make a copy: Go to File > Make A Copy
To use in Word: Go to File > Download > Word