Sign up for the weekly B2B Marketing United newsletter
Blog
Letters
How to
Blog
I hated being called out by Ritson as ‘unqualified’ so I trained; now I share my experience with students at B2B marketing’s best Academy
I fell into marketing. I trained as a journalist.
When it came to the point at which we had to make career decisions, journalism was the nearest thing I could think of to all the things I was good at or considered fun: meeting and chatting to people; building relationships and winning their trust; writing, telling stories; finding stuff out that someone somewhere was trying to keep secret and - on regular occasions - genuinely holding powerful figures to account.
A few weeks ago, Professor Ritson caused some trademark havoc on Linkedin with a quiz he designed for some Ipsos research; a test whose results he says proves two thirds of us marketers in the UK and US are unqualified and unfit for purpose.
Like most of us in our teens, I lacked self-awareness. However, one thing I knew for sure even then - and still do - is that feeling ‘tied’ to a desk and repeating the same tasks every day was not an option. Journalism - a profession that does require training if you’re to reach a decent level - fitted. For about a decade I did well, travelled extensively, learned a great deal and laughed a lot. Right up to my last job in journalism as editor of Marketing Week magazine.
One of my most successful manoeuvres in that role was poaching Ritson from my direct competitor and persuading him to join me as Marketing Week’s top columnist and good friend. He resisted at first because he’s an honorable guy who felt some loyalty to his team and editor but we kept talking and eventually, he was persuaded.
We formed a good working partnership and he was a key part of any success I had as editor of a big business weekly.
Some years later, when I’d swapped editorial for commercial (a typical ‘me’ move: the beginning of year four in the highest profile and best job I’d ever had at the time - to get itchy feet and quit to find new adventure); Ritson launched his MiniMBA training programme.
So successful was his entrepreneurial idea that it became a monster. A decade on, Ritson has ceased the formal teaching and brand consultancy on which he built his name.
Drawing on decades of experience both advising global brands and teaching MBA students at the world’s top business schools, Ritson has built the digital, affordable and hence accessible, MBA equivalent training programme for marketers. The MiniMBA trains around 8,000 marketers every year across 40 different countries and boasts a Net Promoter Score of +84.
By comparison, in the year ending June 2025, the UK’s century-old Chartered Institute of Marketing (CIM) trained 5,100 marketers and achieved an NPS of +50.5.
Perhaps one edge that Ritson has over professional trainers is that he didn’t make his career exclusively about educating others. Yes he’s an academic but he;s been in the thick of the jungle too - consultant in the boardrooms of the world’s most famous businesses: Louis Vuitton, Dom Pérignon, Hennessy, Sephora, WD-40, Ericsson, News Corp and countless others.
That’s why the MiniMBA is trusted to train marketers from the likes of American Express, McDonald’s, Nestle, Red Bull and Tesco.
It was during this huge growth period for the MiniMBA that I found myself on the wrong side of what had become Ritson’s loudest and most repeated attack on the industry.
Year after year, Ritson would use his platform to call us out - the lot of us, the whole marketing industry - for our lack of formal training and qualifications.
He told us that if we’re running marketing for our organisations based on what we’ve learned on the job and our ‘natural’ business or people skills, then we were probably doing it wrong.
I fucking hated it - seeing my mate rant and curse about something so important and - to my mind correct - and knowing I was one of those he was pointing to.
I felt embarrassed to be herded in with the masses of mediocre marketers around me and told I lacked the required skills to properly deliver in an industry in which I was building some profile.
Needing to rid myself of Ritson-induced anxiety, I insisted to a new boss that I wanted to make my leadership position ‘real’ and that I’d be putting myself and my marketing team through the MiniMBA as my first big deliverable.
Sure enough, when I embarked on the MiniMBA I realised just how much I didn't know; just how much there is to know; how small a slice of good marketing practice we B2B marketers actually involve ourselves in, and how much of an advantage trained marketers enjoy.
Ritson and I speak about the training gap and his continuing (and curse-littered) fury at the arrogance of untrained marketers in this week’s episode of the Do More With Less podcast.
Now, I’d advise anyone to do some marketing training. I’m not close to the courses offered by the CIM or the IPA, but I do know the market lacks really good training aimed at B2B marketers specifically.
There’s really not much guidance or proper career development around for us. That’s why B2B Marketing United has taken its training offer so seriously so early on in its existence.
While the internet is groaning with free and paid-for courses teaching isolated skills and tactics: digital advertising, email marketing, content writing and so on; our Academy serves a different (and arguably more pressing) need.
I remember getting into tech scale-ups and startups around 2014, where young, new starters were more than capable of hacking together tactical campaign skills from YouTube self-training videos. I watched it happen. Anything they wanted to know, new tools they wanted to integrate and optimise - they’d watch a tutorial, practise it, train one another and ‘class’ would be over within 10 minutes.
Nobody cared about CPD points. They just wanted to get better at their jobs. Fast
With such an abundance of free opportunities to learn tactics, two half days learning ‘B2B copywriting’ for £800 isn’t really what many B2B marketers need right now.
The evolution of AI and how we use it continues to rapidly thin out marketing functions. Many of my clients at OrbitalX are $50m+ revenue businesses served by marketing functions of just one or two ‘generalists’ plus partner vendors and tech.
Huge swathes of middle management are being ripped out - often along with expensive senior executives. Young marketers are finding themselves over-promoted too quickly into senior positions with little or no support infrastructure.
Hiring managers have switched their attention to what recruiter Rowan Fisk describes as 'the ability to walk into any conversation, challenge the strategy, and have it received as contribution rather than threat'.
Bosses want "systems thinking over channel depth," writes Fisk, "orchestration over execution; [they want] critical thinking and judgment. The ability to see the whole board and make decisions that hold up across time."
The stuff marketers (young and old) most need to know has changed almost instantly. It’s not ‘digital marketing’ skills. Sure, running a YouTube account, creating videos for Linkedin campaigns, managing paid media and better email marketing are all table stakes.
But you don’t need to pay to learn them.
The valuable lessons - tools and behaviours we senior marketers learned over twenty years that the next generation needs to pick up in mere months - include how to 'win' budget discussions with CFOs; how to talk about, plan and deliver pipeline and revenue impact (rather than arguing over the definition of an 'MQL)'; how to say 'no' and make it sound like a 'yes'; how to smash Q1's numbers while building the brand marketing play to prepare the ground for Q4 and beyond.
That's why the three courses you’ll find at the Academy are about marketing leadership as opposed to tactical bits and bobs. The courses aren’t taught by professional trainers but real marketers. Lessons are based on experience; real-life scenarios; the wins; the fuck-ups; and all the lessons and other stuff we wish we’d learned much sooner. The stuff I share when mentoring and coaching.
If we're to avoid losing the current middle generation of B2B marketers being ousted out of previously secure jobs and a new generation of kids - tech-savvy but short on business smarts - they need a short-cut access to leadership and go-to-market thinking.
As the business environment changes, so does the way we train and prepare for it.
We should celebrate it. School’s getting more fun.
I hated being called out by Ritson as ‘unqualified’ so I trained; now I share my experience with students at B2B marketing’s best Academy
I fell into marketing. I trained as a journalist.
When it came to the point at which we had to make career decisions, journalism was the nearest thing I could think of to all the things I was good at or considered fun: meeting and chatting to people; building relationships and winning their trust; writing, telling stories; finding stuff out that someone somewhere was trying to keep secret and - on regular occasions - genuinely holding powerful figures to account.
A few weeks ago, Professor Ritson caused some trademark havoc on Linkedin with a quiz he designed for some Ipsos research; a test whose results he says proves two thirds of us marketers in the UK and US are unqualified and unfit for purpose.
Like most of us in our teens, I lacked self-awareness. However, one thing I knew for sure even then - and still do - is that feeling ‘tied’ to a desk and repeating the same tasks every day was not an option. Journalism - a profession that does require training if you’re to reach a decent level - fitted. For about a decade I did well, travelled extensively, learned a great deal and laughed a lot. Right up to my last job in journalism as editor of Marketing Week magazine.
One of my most successful manoeuvres in that role was poaching Ritson from my direct competitor and persuading him to join me as Marketing Week’s top columnist and good friend. He resisted at first because he’s an honorable guy who felt some loyalty to his team and editor but we kept talking and eventually, he was persuaded.
We formed a good working partnership and he was a key part of any success I had as editor of a big business weekly.
Some years later, when I’d swapped editorial for commercial (a typical ‘me’ move: the beginning of year four in the highest profile and best job I’d ever had at the time - to get itchy feet and quit to find new adventure); Ritson launched his MiniMBA training programme.
So successful was his entrepreneurial idea that it became a monster. A decade on, Ritson has ceased the formal teaching and brand consultancy on which he built his name.
Drawing on decades of experience both advising global brands and teaching MBA students at the world’s top business schools, Ritson has built the digital, affordable and hence accessible, MBA equivalent training programme for marketers. The MiniMBA trains around 8,000 marketers every year across 40 different countries and boasts a Net Promoter Score of +84.
By comparison, in the year ending June 2025, the UK’s century-old Chartered Institute of Marketing (CIM) trained 5,100 marketers and achieved an NPS of +50.5.
Perhaps one edge that Ritson has over professional trainers is that he didn’t make his career exclusively about educating others. Yes he’s an academic but he;s been in the thick of the jungle too - consultant in the boardrooms of the world’s most famous businesses: Louis Vuitton, Dom Pérignon, Hennessy, Sephora, WD-40, Ericsson, News Corp and countless others.
That’s why the MiniMBA is trusted to train marketers from the likes of American Express, McDonald’s, Nestle, Red Bull and Tesco.
It was during this huge growth period for the MiniMBA that I found myself on the wrong side of what had become Ritson’s loudest and most repeated attack on the industry.
Year after year, Ritson would use his platform to call us out - the lot of us, the whole marketing industry - for our lack of formal training and qualifications.
He told us that if we’re running marketing for our organisations based on what we’ve learned on the job and our ‘natural’ business or people skills, then we were probably doing it wrong.
I fucking hated it - seeing my mate rant and curse about something so important and - to my mind correct - and knowing I was one of those he was pointing to.
I felt embarrassed to be herded in with the masses of mediocre marketers around me and told I lacked the required skills to properly deliver in an industry in which I was building some profile.
Needing to rid myself of Ritson-induced anxiety, I insisted to a new boss that I wanted to make my leadership position ‘real’ and that I’d be putting myself and my marketing team through the MiniMBA as my first big deliverable.
Sure enough, when I embarked on the MiniMBA I realised just how much I didn't know; just how much there is to know; how small a slice of good marketing practice we B2B marketers actually involve ourselves in, and how much of an advantage trained marketers enjoy.
Ritson and I speak about the training gap and his continuing (and curse-littered) fury at the arrogance of untrained marketers in this week’s episode of the Do More With Less podcast.
Now, I’d advise anyone to do some marketing training. I’m not close to the courses offered by the CIM or the IPA, but I do know the market lacks really good training aimed at B2B marketers specifically.
There’s really not much guidance or proper career development around for us. That’s why B2B Marketing United has taken its training offer so seriously so early on in its existence.
While the internet is groaning with free and paid-for courses teaching isolated skills and tactics: digital advertising, email marketing, content writing and so on; our Academy serves a different (and arguably more pressing) need.
I remember getting into tech scale-ups and startups around 2014, where young, new starters were more than capable of hacking together tactical campaign skills from YouTube self-training videos. I watched it happen. Anything they wanted to know, new tools they wanted to integrate and optimise - they’d watch a tutorial, practise it, train one another and ‘class’ would be over within 10 minutes.
Nobody cared about CPD points. They just wanted to get better at their jobs. Fast
With such an abundance of free opportunities to learn tactics, two half days learning ‘B2B copywriting’ for £800 isn’t really what many B2B marketers need right now.
The evolution of AI and how we use it continues to rapidly thin out marketing functions. Many of my clients at OrbitalX are $50m+ revenue businesses served by marketing functions of just one or two ‘generalists’ plus partner vendors and tech.
Huge swathes of middle management are being ripped out - often along with expensive senior executives. Young marketers are finding themselves over-promoted too quickly into senior positions with little or no support infrastructure.
Hiring managers have switched their attention to what recruiter Rowan Fisk describes as 'the ability to walk into any conversation, challenge the strategy, and have it received as contribution rather than threat'.
Bosses want "systems thinking over channel depth," writes Fisk, "orchestration over execution; [they want] critical thinking and judgment. The ability to see the whole board and make decisions that hold up across time."
The stuff marketers (young and old) most need to know has changed almost instantly. It’s not ‘digital marketing’ skills. Sure, running a YouTube account, creating videos for Linkedin campaigns, managing paid media and better email marketing are all table stakes.
But you don’t need to pay to learn them.
The valuable lessons - tools and behaviours we senior marketers learned over twenty years that the next generation needs to pick up in mere months - include how to 'win' budget discussions with CFOs; how to talk about, plan and deliver pipeline and revenue impact (rather than arguing over the definition of an 'MQL)'; how to say 'no' and make it sound like a 'yes'; how to smash Q1's numbers while building the brand marketing play to prepare the ground for Q4 and beyond.
That's why the three courses you’ll find at the Academy are about marketing leadership as opposed to tactical bits and bobs. The courses aren’t taught by professional trainers but real marketers. Lessons are based on experience; real-life scenarios; the wins; the fuck-ups; and all the lessons and other stuff we wish we’d learned much sooner. The stuff I share when mentoring and coaching.
If we're to avoid losing the current middle generation of B2B marketers being ousted out of previously secure jobs and a new generation of kids - tech-savvy but short on business smarts - they need a short-cut access to leadership and go-to-market thinking.
As the business environment changes, so does the way we train and prepare for it.
We should celebrate it. School’s getting more fun.
I hated being called out by Ritson as ‘unqualified’ so I trained; now I share my experience with students at B2B marketing’s best Academy
I fell into marketing. I trained as a journalist.
When it came to the point at which we had to make career decisions, journalism was the nearest thing I could think of to all the things I was good at or considered fun: meeting and chatting to people; building relationships and winning their trust; writing, telling stories; finding stuff out that someone somewhere was trying to keep secret and - on regular occasions - genuinely holding powerful figures to account.
A few weeks ago, Professor Ritson caused some trademark havoc on Linkedin with a quiz he designed for some Ipsos research; a test whose results he says proves two thirds of us marketers in the UK and US are unqualified and unfit for purpose.
Like most of us in our teens, I lacked self-awareness. However, one thing I knew for sure even then - and still do - is that feeling ‘tied’ to a desk and repeating the same tasks every day was not an option. Journalism - a profession that does require training if you’re to reach a decent level - fitted. For about a decade I did well, travelled extensively, learned a great deal and laughed a lot. Right up to my last job in journalism as editor of Marketing Week magazine.
One of my most successful manoeuvres in that role was poaching Ritson from my direct competitor and persuading him to join me as Marketing Week’s top columnist and good friend. He resisted at first because he’s an honorable guy who felt some loyalty to his team and editor but we kept talking and eventually, he was persuaded.
We formed a good working partnership and he was a key part of any success I had as editor of a big business weekly.
Some years later, when I’d swapped editorial for commercial (a typical ‘me’ move: the beginning of year four in the highest profile and best job I’d ever had at the time - to get itchy feet and quit to find new adventure); Ritson launched his MiniMBA training programme.
So successful was his entrepreneurial idea that it became a monster. A decade on, Ritson has ceased the formal teaching and brand consultancy on which he built his name.
Drawing on decades of experience both advising global brands and teaching MBA students at the world’s top business schools, Ritson has built the digital, affordable and hence accessible, MBA equivalent training programme for marketers. The MiniMBA trains around 8,000 marketers every year across 40 different countries and boasts a Net Promoter Score of +84.
By comparison, in the year ending June 2025, the UK’s century-old Chartered Institute of Marketing (CIM) trained 5,100 marketers and achieved an NPS of +50.5.
Perhaps one edge that Ritson has over professional trainers is that he didn’t make his career exclusively about educating others. Yes he’s an academic but he;s been in the thick of the jungle too - consultant in the boardrooms of the world’s most famous businesses: Louis Vuitton, Dom Pérignon, Hennessy, Sephora, WD-40, Ericsson, News Corp and countless others.
That’s why the MiniMBA is trusted to train marketers from the likes of American Express, McDonald’s, Nestle, Red Bull and Tesco.
It was during this huge growth period for the MiniMBA that I found myself on the wrong side of what had become Ritson’s loudest and most repeated attack on the industry.
Year after year, Ritson would use his platform to call us out - the lot of us, the whole marketing industry - for our lack of formal training and qualifications.
He told us that if we’re running marketing for our organisations based on what we’ve learned on the job and our ‘natural’ business or people skills, then we were probably doing it wrong.
I fucking hated it - seeing my mate rant and curse about something so important and - to my mind correct - and knowing I was one of those he was pointing to.
I felt embarrassed to be herded in with the masses of mediocre marketers around me and told I lacked the required skills to properly deliver in an industry in which I was building some profile.
Needing to rid myself of Ritson-induced anxiety, I insisted to a new boss that I wanted to make my leadership position ‘real’ and that I’d be putting myself and my marketing team through the MiniMBA as my first big deliverable.
Sure enough, when I embarked on the MiniMBA I realised just how much I didn't know; just how much there is to know; how small a slice of good marketing practice we B2B marketers actually involve ourselves in, and how much of an advantage trained marketers enjoy.
Ritson and I speak about the training gap and his continuing (and curse-littered) fury at the arrogance of untrained marketers in this week’s episode of the Do More With Less podcast.
Now, I’d advise anyone to do some marketing training. I’m not close to the courses offered by the CIM or the IPA, but I do know the market lacks really good training aimed at B2B marketers specifically.
There’s really not much guidance or proper career development around for us. That’s why B2B Marketing United has taken its training offer so seriously so early on in its existence.
While the internet is groaning with free and paid-for courses teaching isolated skills and tactics: digital advertising, email marketing, content writing and so on; our Academy serves a different (and arguably more pressing) need.
I remember getting into tech scale-ups and startups around 2014, where young, new starters were more than capable of hacking together tactical campaign skills from YouTube self-training videos. I watched it happen. Anything they wanted to know, new tools they wanted to integrate and optimise - they’d watch a tutorial, practise it, train one another and ‘class’ would be over within 10 minutes.
Nobody cared about CPD points. They just wanted to get better at their jobs. Fast
With such an abundance of free opportunities to learn tactics, two half days learning ‘B2B copywriting’ for £800 isn’t really what many B2B marketers need right now.
The evolution of AI and how we use it continues to rapidly thin out marketing functions. Many of my clients at OrbitalX are $50m+ revenue businesses served by marketing functions of just one or two ‘generalists’ plus partner vendors and tech.
Huge swathes of middle management are being ripped out - often along with expensive senior executives. Young marketers are finding themselves over-promoted too quickly into senior positions with little or no support infrastructure.
Hiring managers have switched their attention to what recruiter Rowan Fisk describes as 'the ability to walk into any conversation, challenge the strategy, and have it received as contribution rather than threat'.
Bosses want "systems thinking over channel depth," writes Fisk, "orchestration over execution; [they want] critical thinking and judgment. The ability to see the whole board and make decisions that hold up across time."
The stuff marketers (young and old) most need to know has changed almost instantly. It’s not ‘digital marketing’ skills. Sure, running a YouTube account, creating videos for Linkedin campaigns, managing paid media and better email marketing are all table stakes.
But you don’t need to pay to learn them.
The valuable lessons - tools and behaviours we senior marketers learned over twenty years that the next generation needs to pick up in mere months - include how to 'win' budget discussions with CFOs; how to talk about, plan and deliver pipeline and revenue impact (rather than arguing over the definition of an 'MQL)'; how to say 'no' and make it sound like a 'yes'; how to smash Q1's numbers while building the brand marketing play to prepare the ground for Q4 and beyond.
That's why the three courses you’ll find at the Academy are about marketing leadership as opposed to tactical bits and bobs. The courses aren’t taught by professional trainers but real marketers. Lessons are based on experience; real-life scenarios; the wins; the fuck-ups; and all the lessons and other stuff we wish we’d learned much sooner. The stuff I share when mentoring and coaching.
If we're to avoid losing the current middle generation of B2B marketers being ousted out of previously secure jobs and a new generation of kids - tech-savvy but short on business smarts - they need a short-cut access to leadership and go-to-market thinking.
As the business environment changes, so does the way we train and prepare for it.
We should celebrate it. School’s getting more fun.
London
Apr 22, 2026
Rich Fitzmaurice
Letters
"I am a freelance marketing consultant. My latest prospect has just told me that they've decided to try and do all their marketing for free using ChatGPT so 'Thanks, but no thanks for your proposal'.
It's becoming more and more common, marketing getting bumped into the general AI company strategy, insane. But mid-sized organisations are all starting to do it. Are you seeing this too?"
Katie, Fleet, UK
Rich's Reply
Oh Katie, we are very much in the middle of the AI honeymoon period. And I feel a rant coming…
More and more people are being exposed to, and experimenting with, basic, easily accessible AI assistants such as ChatGPT, Claude, Perplexity and Copilot. We must all admit that the first few times you play with them, they can be impressive.
But the moment you converse with them on a topic you specialise in, the limitations become glaringly obvious. You can spot the oversimplifications. The generalisations. The lack of actual nuance. The factual errors. Even the typos.
Because although AI assistants seem smart, they are not. They are simply pulling common answers together from common sources, by recognising patterns. Top and tailed with some pleasantries and faux encouragement, and you can be forgiven for wondering if they might pass the Turing test.
At this moment in time, AI assistants cannot understand. They do not understand nuance. Context. Experience. Intuition. Instinct. Creativity.
One day, maybe. But now? Absolutely not. And if anyone tries to convince you otherwise, they probably have a hard drive full of NFTs.
Before anyone accuses me of being anti-AI, I'm not. I'm just anti-stupid.
AI assistants can be extremely useful. I use them daily for different purposes. They help guide you to an answer. They can help you iterate so much faster. They can help get you to a decision point, but they just as easily give you bad ideas you do not want to explore.
The responsibility to ensure quality of output is still unmistakably on the human. AI in the right hands is extremely powerful. And I see AI making good marketers faster, better and smarter.
But the gap between those people and the average user being overconfident in AI is widening by the day. And it's the latter that we should be worried about.
I've had a CEO pull me into his office to show me that his AI assistant can quickly build a marketing plan. Spoiler: it would get a C at high school, but that's about it. So unfortunately, I can very well believe that some people out there think AI can write and execute their marketing for them (after all, marketing and HR are the two professions everyone secretly thinks they could do).
But AI can't. Not for a few more years at the very least. Even the AI tools developed by marketers are still evolving and require a real marketer on top.
In the last few months alone, I have seen real-world examples of AI-generated mistakes that have made it all the way to board level:
Invented competitors mentioned in board reports
Cited and falsely referenced statistics in business plans
Numbers which did not add up
Now obviously, the humans involved looked sheepish. It is ultimately their mistake. But these specific mistakes happened under human supervision. Remove that expert supervision and ask yourself how bad those documents become.
ChatGPT may give some a short-term dopamine boost when they see a high-level strategy presented with confidence, and maybe even an exportable file. But a real marketer will quickly see what is missing, what is generic and what hasn't even been considered.
Claude might pump out a content strategy and articles at the click of a button. But no one will want to read them, and platforms are getting much better at identifying and suppressing them automatically.
AI cannot replace experience, street smarts, creativity, judgement.
AI is not a replacement for marketing functions. It is a potential multiplier for one that already exists. Without a marketer holding the wheel, they are not saving any money. They are just automating 'meh'. Adding to the deluge of noise that their prospects are increasingly filtering out.
So how should marketing consultants like yourself react when this happens? You have several options:
Ask them to send you their AI-generated plan and offer to feedback at a high level
Highlight the pitfalls, explain why AI isn't a shortcut, and offer to help them use AI in the right way
Attend events and take courses so that in your next exploratory call, the prospect feels how much you know about marketing and AI, and how little they do
Leave the door open. "If it doesn't work out as well as you hope, you know where I am"
It is always frustrating to lose a potential client you've worked to win, but stay professional, be courteous and try your best not to burn bridges. If they engaged with you once, they must have had some interest in your offer. Prospects sometimes make mistakes. Don't cut yourself off from the option of being their saviour later.
I emphasise the word option.
Knowing which clients are a good fit for you and which ones are a bad fit is one of the most powerful levers you have as a marketing consultant. And time is your most valuable commodity.
Bad clients drain energy. Good ones give it back.
Onwards!
Rich
"I am a freelance marketing consultant. My latest prospect has just told me that they've decided to try and do all their marketing for free using ChatGPT so 'Thanks, but no thanks for your proposal'.
It's becoming more and more common, marketing getting bumped into the general AI company strategy, insane. But mid-sized organisations are all starting to do it. Are you seeing this too?"
Katie, Fleet, UK
Rich's Reply
Oh Katie, we are very much in the middle of the AI honeymoon period. And I feel a rant coming…
More and more people are being exposed to, and experimenting with, basic, easily accessible AI assistants such as ChatGPT, Claude, Perplexity and Copilot. We must all admit that the first few times you play with them, they can be impressive.
But the moment you converse with them on a topic you specialise in, the limitations become glaringly obvious. You can spot the oversimplifications. The generalisations. The lack of actual nuance. The factual errors. Even the typos.
Because although AI assistants seem smart, they are not. They are simply pulling common answers together from common sources, by recognising patterns. Top and tailed with some pleasantries and faux encouragement, and you can be forgiven for wondering if they might pass the Turing test.
At this moment in time, AI assistants cannot understand. They do not understand nuance. Context. Experience. Intuition. Instinct. Creativity.
One day, maybe. But now? Absolutely not. And if anyone tries to convince you otherwise, they probably have a hard drive full of NFTs.
Before anyone accuses me of being anti-AI, I'm not. I'm just anti-stupid.
AI assistants can be extremely useful. I use them daily for different purposes. They help guide you to an answer. They can help you iterate so much faster. They can help get you to a decision point, but they just as easily give you bad ideas you do not want to explore.
The responsibility to ensure quality of output is still unmistakably on the human. AI in the right hands is extremely powerful. And I see AI making good marketers faster, better and smarter.
But the gap between those people and the average user being overconfident in AI is widening by the day. And it's the latter that we should be worried about.
I've had a CEO pull me into his office to show me that his AI assistant can quickly build a marketing plan. Spoiler: it would get a C at high school, but that's about it. So unfortunately, I can very well believe that some people out there think AI can write and execute their marketing for them (after all, marketing and HR are the two professions everyone secretly thinks they could do).
But AI can't. Not for a few more years at the very least. Even the AI tools developed by marketers are still evolving and require a real marketer on top.
In the last few months alone, I have seen real-world examples of AI-generated mistakes that have made it all the way to board level:
Invented competitors mentioned in board reports
Cited and falsely referenced statistics in business plans
Numbers which did not add up
Now obviously, the humans involved looked sheepish. It is ultimately their mistake. But these specific mistakes happened under human supervision. Remove that expert supervision and ask yourself how bad those documents become.
ChatGPT may give some a short-term dopamine boost when they see a high-level strategy presented with confidence, and maybe even an exportable file. But a real marketer will quickly see what is missing, what is generic and what hasn't even been considered.
Claude might pump out a content strategy and articles at the click of a button. But no one will want to read them, and platforms are getting much better at identifying and suppressing them automatically.
AI cannot replace experience, street smarts, creativity, judgement.
AI is not a replacement for marketing functions. It is a potential multiplier for one that already exists. Without a marketer holding the wheel, they are not saving any money. They are just automating 'meh'. Adding to the deluge of noise that their prospects are increasingly filtering out.
So how should marketing consultants like yourself react when this happens? You have several options:
Ask them to send you their AI-generated plan and offer to feedback at a high level
Highlight the pitfalls, explain why AI isn't a shortcut, and offer to help them use AI in the right way
Attend events and take courses so that in your next exploratory call, the prospect feels how much you know about marketing and AI, and how little they do
Leave the door open. "If it doesn't work out as well as you hope, you know where I am"
It is always frustrating to lose a potential client you've worked to win, but stay professional, be courteous and try your best not to burn bridges. If they engaged with you once, they must have had some interest in your offer. Prospects sometimes make mistakes. Don't cut yourself off from the option of being their saviour later.
I emphasise the word option.
Knowing which clients are a good fit for you and which ones are a bad fit is one of the most powerful levers you have as a marketing consultant. And time is your most valuable commodity.
Bad clients drain energy. Good ones give it back.
Onwards!
Rich
"I am a freelance marketing consultant. My latest prospect has just told me that they've decided to try and do all their marketing for free using ChatGPT so 'Thanks, but no thanks for your proposal'.
It's becoming more and more common, marketing getting bumped into the general AI company strategy, insane. But mid-sized organisations are all starting to do it. Are you seeing this too?"
Katie, Fleet, UK
Rich's Reply
Oh Katie, we are very much in the middle of the AI honeymoon period. And I feel a rant coming…
More and more people are being exposed to, and experimenting with, basic, easily accessible AI assistants such as ChatGPT, Claude, Perplexity and Copilot. We must all admit that the first few times you play with them, they can be impressive.
But the moment you converse with them on a topic you specialise in, the limitations become glaringly obvious. You can spot the oversimplifications. The generalisations. The lack of actual nuance. The factual errors. Even the typos.
Because although AI assistants seem smart, they are not. They are simply pulling common answers together from common sources, by recognising patterns. Top and tailed with some pleasantries and faux encouragement, and you can be forgiven for wondering if they might pass the Turing test.
At this moment in time, AI assistants cannot understand. They do not understand nuance. Context. Experience. Intuition. Instinct. Creativity.
One day, maybe. But now? Absolutely not. And if anyone tries to convince you otherwise, they probably have a hard drive full of NFTs.
Before anyone accuses me of being anti-AI, I'm not. I'm just anti-stupid.
AI assistants can be extremely useful. I use them daily for different purposes. They help guide you to an answer. They can help you iterate so much faster. They can help get you to a decision point, but they just as easily give you bad ideas you do not want to explore.
The responsibility to ensure quality of output is still unmistakably on the human. AI in the right hands is extremely powerful. And I see AI making good marketers faster, better and smarter.
But the gap between those people and the average user being overconfident in AI is widening by the day. And it's the latter that we should be worried about.
I've had a CEO pull me into his office to show me that his AI assistant can quickly build a marketing plan. Spoiler: it would get a C at high school, but that's about it. So unfortunately, I can very well believe that some people out there think AI can write and execute their marketing for them (after all, marketing and HR are the two professions everyone secretly thinks they could do).
But AI can't. Not for a few more years at the very least. Even the AI tools developed by marketers are still evolving and require a real marketer on top.
In the last few months alone, I have seen real-world examples of AI-generated mistakes that have made it all the way to board level:
Invented competitors mentioned in board reports
Cited and falsely referenced statistics in business plans
Numbers which did not add up
Now obviously, the humans involved looked sheepish. It is ultimately their mistake. But these specific mistakes happened under human supervision. Remove that expert supervision and ask yourself how bad those documents become.
ChatGPT may give some a short-term dopamine boost when they see a high-level strategy presented with confidence, and maybe even an exportable file. But a real marketer will quickly see what is missing, what is generic and what hasn't even been considered.
Claude might pump out a content strategy and articles at the click of a button. But no one will want to read them, and platforms are getting much better at identifying and suppressing them automatically.
AI cannot replace experience, street smarts, creativity, judgement.
AI is not a replacement for marketing functions. It is a potential multiplier for one that already exists. Without a marketer holding the wheel, they are not saving any money. They are just automating 'meh'. Adding to the deluge of noise that their prospects are increasingly filtering out.
So how should marketing consultants like yourself react when this happens? You have several options:
Ask them to send you their AI-generated plan and offer to feedback at a high level
Highlight the pitfalls, explain why AI isn't a shortcut, and offer to help them use AI in the right way
Attend events and take courses so that in your next exploratory call, the prospect feels how much you know about marketing and AI, and how little they do
Leave the door open. "If it doesn't work out as well as you hope, you know where I am"
It is always frustrating to lose a potential client you've worked to win, but stay professional, be courteous and try your best not to burn bridges. If they engaged with you once, they must have had some interest in your offer. Prospects sometimes make mistakes. Don't cut yourself off from the option of being their saviour later.
I emphasise the word option.
Knowing which clients are a good fit for you and which ones are a bad fit is one of the most powerful levers you have as a marketing consultant. And time is your most valuable commodity.
Bad clients drain energy. Good ones give it back.
Onwards!
Rich
Content
May 7, 2026
Content
How to's
Here is the number that should be on every B2B CMO's desk this quarter. In G2's August 2025 buyer survey, 87% of B2B software buyers said AI chatbots like ChatGPT, Perplexity, Gemini and Claude are changing how they research purchases. In the same study, only 12% of B2B SaaS brands appeared when buyers ran category-level searches inside those tools. The other 88% were simply absent from the moment their buyers were forming opinions.
That gap, between where buyers are researching and where brands are visible, is the single biggest unpriced risk in B2B marketing right now. It is also not a distant problem. A multi-source analysis published in March 2026, covering 680 million AI citations and almost two million browsing sessions, found that 73% of B2B buyers are already using AI tools inside their purchase research process. Forrester's 2025 buyer study put a number on the downstream consequence. 61% of the B2B buying journey now completes before a buyer ever contacts a vendor, and that figure climbs every time an AI tool synthesises a shortlist on their behalf.
Meanwhile, McKinsey estimates that around 50% of Google searches already include AI summaries, rising above 75% by 2028, and projects that $750 billion in US revenue will funnel through AI-powered search by 2028. This is a rewiring of how B2B buyers discover, compare and choose, not a marginal channel shift.
The discipline that governs whether you are visible inside those AI-generated answers has a name. It is Answer Engine Optimisation (AEO), and it is a different discipline to SEO.
Why SEO tactics don't translate (and why that matters to your budget)
For most of the last two decades, B2B marketers have optimised for a specific user behaviour. Type a query into Google, scan a list of ten blue links, click one. The entire SEO playbook (keyword targeting, backlinks, domain authority, ranking positions) is a set of levers pulled against that behaviour.
Answer engines don't work that way. When a buyer asks ChatGPT "what are the best account-based marketing platforms for mid-market B2B?", the model doesn't show them ten blue links. It synthesises an answer, names two or three vendors, and sometimes cites a handful of sources. The buyer leaves with a shortlist instead of a search results page.
That one behavioural change breaks several of the core assumptions B2B marketers have been budgeting against.
Rankings don't map to citations. A page that ranks #1 on Google may never be cited by ChatGPT, and a page that doesn't rank in Google's top 20 can be cited repeatedly by Perplexity. The 2025 AI Visibility Report from The Digital Bloom found that only 11% of domains cited by ChatGPT were also cited by Perplexity for the same queries. These are different retrieval systems with different signals.
Backlinks are no longer the dominant signal. In the same study, brand search volume was the strongest predictor of AI citations, with a correlation of 0.334. That is materially stronger than any backlink-based metric. Models are increasingly using brand familiarity as a proxy for trust.
Content freshness suddenly matters in a way SEO never rewarded. Roughly 65% of log hits to cited content were for pages published in the last year, and 79% were from the last two years. AI systems lean toward recent, actively maintained sources.
Traditional measurement is silent on the question that matters. GA4 will not tell you how often ChatGPT recommends you. Your rank tracker will not tell you whether Perplexity is citing your competitor. The measurement stack most B2B marketing teams rely on was built for a world where discovery happened on a SERP.
These differences add up. The inputs, the signals, the measurement and the skills required are distinct enough that treating AEO as "the SEO team's next project" is already producing a second wave of wasted budget across the industry.
The four pillars of AEO for B2B marketers
The methodology breaks down into four pillars. They work as concurrent workstreams rather than sequential steps, and each one pulls a different lever.
1. Entity positioning: make the model understand who you are
Before an answer engine can recommend you, it has to understand what you are. Large language models reason in terms of entities: companies, products, categories, people. If the model's internal representation of your brand is vague, incomplete or confused with a competitor, no amount of content will fix it.
Entity positioning is the work of making sure every AI system has an unambiguous understanding of who you are, what category you compete in, what you do better than alternatives, and who your ideal customer is. The practical work includes Wikidata entries, Knowledge Panel optimisation, structured data (Organization, Product, Software Application schemas), and consistent entity descriptions across high-authority third-party sources.
Diagnostic question for your team: open ChatGPT and ask "What does [your brand] do?" Then ask "Who are [your brand]'s main competitors?" If the answers are vague, wrong, or list your brand alongside companies you don't actually compete with, you have an entity problem. Entity sits upstream of every other AEO lever, so this is usually where the work starts.
2. Answer architecture: structure content so models can extract and cite it
Most B2B content is written for humans scrolling on a laptop. Answer engines don't scroll. They extract. Content that wins citations is content that answers specific questions directly, in a structure the model can parse.
The brands that get cited repeatedly across platforms usually aren't the ones producing the most content. They are the ones whose content is architected for extraction: clear definitions, direct answers at the top of sections, FAQ blocks with schema, concise paragraphs, well-structured headers, and explicit comparisons. Seer Interactive's data on AI Overviews found that brands cited in Google's AI answers earn 35% more organic clicks and 91% more paid clicks. The same Seer analysis showed that when AI Overviews are present and your brand is not cited, organic CTR drops 61% and paid CTR drops 68%. Answer architecture is what determines which side of that line you sit on.
3. Source signal: earn mentions in the places LLMs actually weight
Not all sources are weighted equally. Each AI platform draws from a different constellation of trusted inputs, and the differences are significant. The same 2025 cross-platform analysis found that Reddit accounted for 46.7% of top Perplexity citations but under 10% on ChatGPT after a September 2025 rebalancing. ChatGPT leans heavily on Wikipedia and long-standing editorial sources. Google AI Overviews favour a diversified cross-platform presence.
Source signal is the discipline of earning mentions, reviews and references in the specific places each platform treats as authoritative for your category. For a B2B SaaS brand, that usually means G2 and Gartner Peer Insights (G2's own internal study confirms they are heavily cited across LLMs), plus category-specific industry publications, relevant subreddits, and any analyst coverage that ends up in the training corpus. This is PR, earned media and community work done with a very specific retrieval target in mind.
4. Measurement: track what your rank tracker can't see
If you can't measure AI visibility, you can't manage it, and you certainly can't defend the budget in front of a board. The four metrics we track for clients map directly to the commercial question every B2B CMO cares about: are we showing up when our buyers are choosing?
AI Mention Rate. For a defined set of 20 to 50 buyer-intent queries, what percentage of the time does your brand appear in the answer across ChatGPT, Perplexity, Claude, Gemini and Google AI Overviews?
Citation Authority. When those platforms cite sources, how often is your domain among them, and how does that compare to your top three competitors?
Entity Clarity Score. When you ask the model directly "What does [brand] do?", is the answer accurate, complete and differentiated, or generic and interchangeable?
Answer Ownership. For the queries that matter most to your pipeline, are you the primary recommendation or a supporting mention?
This is the layer most B2B marketing teams are missing entirely. Only 22% of marketers currently track AI visibility and traffic, and only 25.7% plan to develop content specifically for AI citations. That gap is, for the moment, the single biggest competitive opportunity in B2B marketing.
You can read the full methodology behind each of these pillars on the [growthvibe AI search optimisation methodology page](https://www.growthvibe.com/ai-search-optimization-services/).
A worked example: what this looks like in martech
Consider a mid-market martech category, say, account-based marketing platforms. Ask ChatGPT, Perplexity and Google's AI Overview the same question: "What are the best account-based marketing platforms for B2B companies with 200 to 2,000 employees?"
Run it once and you'll notice a pattern. Two or three vendors show up consistently across all three engines. A handful appear on one platform but not the others. And a long tail of category players, some of them with significantly better products, bigger marketing budgets and stronger Google rankings, don't appear at all.
When we dig into the brands that win across all three platforms, the same four things are usually true. Their entity is clear (the model knows what they do without hesitation). Their owned content is structured for extraction, with direct answers, comparison pages and FAQ schema. They have strong, recent source signal across G2, Gartner coverage, analyst mentions, and in Perplexity's case, organic Reddit discussion. And they are measuring AI visibility as a discipline rather than guessing at it.
The brands that lose? Usually strong on traditional SEO, weak on entity clarity, inconsistent on answer architecture, and invisible in the places the models trust. Their dashboards look healthy. Their pipeline is quietly leaking.
The mistakes I see most often
After running diagnostics across dozens of B2B brands, the same patterns recur.
Treating AEO as a content problem. Most teams respond to the AI search shift by publishing more blog posts about AI. That is content marketing with the word "AI" in the title. AEO requires work across entity, architecture, source signal and measurement. Content is one of four levers.
Over-indexing on a single platform. Teams obsess over ChatGPT and ignore Perplexity, or vice versa. The retrieval systems are different enough that you need a cross-platform view. The 11% citation overlap figure is the most important number most B2B marketers haven't heard.
Letting the incumbent SEO agency redefine AEO as "SEO plus schema". This is the most expensive mistake in the market right now. Schema helps, but it is a single lever inside the second pillar. If your AEO strategy can be executed by adding FAQ markup, it is not an AEO strategy.
Waiting for measurement to get easier. It will not. The teams winning in 2026 are the ones who built a measurement layer manually, accepted the rough edges, and used the data to make decisions. Waiting for a perfect dashboard is a way of conceding ground to the brands who didn't wait.
A 30-minute AEO self-audit for B2B marketers
If you want to stress-test your own position before the next board meeting, here is a condensed version of the audit we run for clients. It takes about half an hour.
1. The entity test. Open ChatGPT, Perplexity and Google's AI Overview. Ask each one "What does [your brand] do?" and "Who are [your brand]'s main competitors?" Note the answers verbatim. If any of them are wrong, vague or list competitors you don't actually compete with, flag an entity issue.
2. The category test. Run your three most important buyer-intent queries across all three platforms. Example: "What are the best [your category] platforms for [your ICP]?" Note whether your brand appears, and if so, where in the answer.
3. The competitor test. Run the same three queries again, but replace your brand name with each of your top three competitors. Compare who gets cited, how often, and in what position.
4. The source test. For every citation that appears across those queries, note the source. Which domains are being pulled? Is your domain among them? If not, which domains are, and do you have a presence on those surfaces?
5. The freshness test. Check the publication dates on your most important category pages. If your pillar content hasn't been updated in the last 12 to 18 months, you are likely losing ground to competitors whose content is fresher.
If you do nothing else this quarter, run this audit. It will tell you, in thirty minutes, whether you have an AEO problem, and roughly how big it is.
The window is open, and it won't stay open
AEO is in the phase every new marketing discipline goes through before it becomes table stakes. The market data is clear enough that ignoring it is a choice. The measurement tooling is rough but workable. The playbooks are being written in real time by the brands who decided not to wait.
B2B marketing teams that treat AEO as a discipline now, with its own strategy, its own measurement, and its own owned workstream inside the marketing function, will compound an advantage every month their competitors spend arguing about whether it matters. The ones that treat it as a side project, or hand it to an agency still thinking in terms of rankings and links, will spend 2027 trying to catch up on ground they didn't realise they were losing.
The brands being cited by AI today are the brands being chosen tomorrow. Everything else is a dashboard.
Request a free AI Visibility Report
---
*Sources: [G2: Does G2 Get Ranked in AI LLM Search?](https://learn.g2.com/tech-signals-does-g2-get-ranked-in-ai-llm-search); [PR Newswire: 73% of B2B Buyers Use AI Tools in Purchase Research](https://www.prnewswire.com/news-releases/73-of-b2b-buyers-use-ai-tools-in-purchase-research-multi-source-analysis-finds-302733319.html); [The Digital Bloom: 2025 AI Visibility Report](https://thedigitalbloom.com/learn/2025-ai-citation-llm-visibility-report/); [McKinsey: The new front door to the internet](https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/new-front-door-to-the-internet-winning-in-the-age-of-ai-search); [Seer Interactive: AIO impact on Google CTR](https://www.seerinteractive.com/insights/aio-impact-on-google-ctr-september-2025-update); [SparkToro: 2024 Zero-Click Search Study](https://sparktoro.com/blog/2024-zero-click-search-study-for-every-1000-us-google-searches-only-374-clicks-go-to-the-open-web-in-the-eu-its-360/); [Adobe: The explosive rise of generative AI referral traffic](https://business.adobe.com/blog/the-explosive-rise-of-generative-ai-referral-traffic); Forrester 2025 B2B Buyer Journey Study.*
Here is the number that should be on every B2B CMO's desk this quarter. In G2's August 2025 buyer survey, 87% of B2B software buyers said AI chatbots like ChatGPT, Perplexity, Gemini and Claude are changing how they research purchases. In the same study, only 12% of B2B SaaS brands appeared when buyers ran category-level searches inside those tools. The other 88% were simply absent from the moment their buyers were forming opinions.
That gap, between where buyers are researching and where brands are visible, is the single biggest unpriced risk in B2B marketing right now. It is also not a distant problem. A multi-source analysis published in March 2026, covering 680 million AI citations and almost two million browsing sessions, found that 73% of B2B buyers are already using AI tools inside their purchase research process. Forrester's 2025 buyer study put a number on the downstream consequence. 61% of the B2B buying journey now completes before a buyer ever contacts a vendor, and that figure climbs every time an AI tool synthesises a shortlist on their behalf.
Meanwhile, McKinsey estimates that around 50% of Google searches already include AI summaries, rising above 75% by 2028, and projects that $750 billion in US revenue will funnel through AI-powered search by 2028. This is a rewiring of how B2B buyers discover, compare and choose, not a marginal channel shift.
The discipline that governs whether you are visible inside those AI-generated answers has a name. It is Answer Engine Optimisation (AEO), and it is a different discipline to SEO.
Why SEO tactics don't translate (and why that matters to your budget)
For most of the last two decades, B2B marketers have optimised for a specific user behaviour. Type a query into Google, scan a list of ten blue links, click one. The entire SEO playbook (keyword targeting, backlinks, domain authority, ranking positions) is a set of levers pulled against that behaviour.
Answer engines don't work that way. When a buyer asks ChatGPT "what are the best account-based marketing platforms for mid-market B2B?", the model doesn't show them ten blue links. It synthesises an answer, names two or three vendors, and sometimes cites a handful of sources. The buyer leaves with a shortlist instead of a search results page.
That one behavioural change breaks several of the core assumptions B2B marketers have been budgeting against.
Rankings don't map to citations. A page that ranks #1 on Google may never be cited by ChatGPT, and a page that doesn't rank in Google's top 20 can be cited repeatedly by Perplexity. The 2025 AI Visibility Report from The Digital Bloom found that only 11% of domains cited by ChatGPT were also cited by Perplexity for the same queries. These are different retrieval systems with different signals.
Backlinks are no longer the dominant signal. In the same study, brand search volume was the strongest predictor of AI citations, with a correlation of 0.334. That is materially stronger than any backlink-based metric. Models are increasingly using brand familiarity as a proxy for trust.
Content freshness suddenly matters in a way SEO never rewarded. Roughly 65% of log hits to cited content were for pages published in the last year, and 79% were from the last two years. AI systems lean toward recent, actively maintained sources.
Traditional measurement is silent on the question that matters. GA4 will not tell you how often ChatGPT recommends you. Your rank tracker will not tell you whether Perplexity is citing your competitor. The measurement stack most B2B marketing teams rely on was built for a world where discovery happened on a SERP.
These differences add up. The inputs, the signals, the measurement and the skills required are distinct enough that treating AEO as "the SEO team's next project" is already producing a second wave of wasted budget across the industry.
The four pillars of AEO for B2B marketers
The methodology breaks down into four pillars. They work as concurrent workstreams rather than sequential steps, and each one pulls a different lever.
1. Entity positioning: make the model understand who you are
Before an answer engine can recommend you, it has to understand what you are. Large language models reason in terms of entities: companies, products, categories, people. If the model's internal representation of your brand is vague, incomplete or confused with a competitor, no amount of content will fix it.
Entity positioning is the work of making sure every AI system has an unambiguous understanding of who you are, what category you compete in, what you do better than alternatives, and who your ideal customer is. The practical work includes Wikidata entries, Knowledge Panel optimisation, structured data (Organization, Product, Software Application schemas), and consistent entity descriptions across high-authority third-party sources.
Diagnostic question for your team: open ChatGPT and ask "What does [your brand] do?" Then ask "Who are [your brand]'s main competitors?" If the answers are vague, wrong, or list your brand alongside companies you don't actually compete with, you have an entity problem. Entity sits upstream of every other AEO lever, so this is usually where the work starts.
2. Answer architecture: structure content so models can extract and cite it
Most B2B content is written for humans scrolling on a laptop. Answer engines don't scroll. They extract. Content that wins citations is content that answers specific questions directly, in a structure the model can parse.
The brands that get cited repeatedly across platforms usually aren't the ones producing the most content. They are the ones whose content is architected for extraction: clear definitions, direct answers at the top of sections, FAQ blocks with schema, concise paragraphs, well-structured headers, and explicit comparisons. Seer Interactive's data on AI Overviews found that brands cited in Google's AI answers earn 35% more organic clicks and 91% more paid clicks. The same Seer analysis showed that when AI Overviews are present and your brand is not cited, organic CTR drops 61% and paid CTR drops 68%. Answer architecture is what determines which side of that line you sit on.
3. Source signal: earn mentions in the places LLMs actually weight
Not all sources are weighted equally. Each AI platform draws from a different constellation of trusted inputs, and the differences are significant. The same 2025 cross-platform analysis found that Reddit accounted for 46.7% of top Perplexity citations but under 10% on ChatGPT after a September 2025 rebalancing. ChatGPT leans heavily on Wikipedia and long-standing editorial sources. Google AI Overviews favour a diversified cross-platform presence.
Source signal is the discipline of earning mentions, reviews and references in the specific places each platform treats as authoritative for your category. For a B2B SaaS brand, that usually means G2 and Gartner Peer Insights (G2's own internal study confirms they are heavily cited across LLMs), plus category-specific industry publications, relevant subreddits, and any analyst coverage that ends up in the training corpus. This is PR, earned media and community work done with a very specific retrieval target in mind.
4. Measurement: track what your rank tracker can't see
If you can't measure AI visibility, you can't manage it, and you certainly can't defend the budget in front of a board. The four metrics we track for clients map directly to the commercial question every B2B CMO cares about: are we showing up when our buyers are choosing?
AI Mention Rate. For a defined set of 20 to 50 buyer-intent queries, what percentage of the time does your brand appear in the answer across ChatGPT, Perplexity, Claude, Gemini and Google AI Overviews?
Citation Authority. When those platforms cite sources, how often is your domain among them, and how does that compare to your top three competitors?
Entity Clarity Score. When you ask the model directly "What does [brand] do?", is the answer accurate, complete and differentiated, or generic and interchangeable?
Answer Ownership. For the queries that matter most to your pipeline, are you the primary recommendation or a supporting mention?
This is the layer most B2B marketing teams are missing entirely. Only 22% of marketers currently track AI visibility and traffic, and only 25.7% plan to develop content specifically for AI citations. That gap is, for the moment, the single biggest competitive opportunity in B2B marketing.
You can read the full methodology behind each of these pillars on the [growthvibe AI search optimisation methodology page](https://www.growthvibe.com/ai-search-optimization-services/).
A worked example: what this looks like in martech
Consider a mid-market martech category, say, account-based marketing platforms. Ask ChatGPT, Perplexity and Google's AI Overview the same question: "What are the best account-based marketing platforms for B2B companies with 200 to 2,000 employees?"
Run it once and you'll notice a pattern. Two or three vendors show up consistently across all three engines. A handful appear on one platform but not the others. And a long tail of category players, some of them with significantly better products, bigger marketing budgets and stronger Google rankings, don't appear at all.
When we dig into the brands that win across all three platforms, the same four things are usually true. Their entity is clear (the model knows what they do without hesitation). Their owned content is structured for extraction, with direct answers, comparison pages and FAQ schema. They have strong, recent source signal across G2, Gartner coverage, analyst mentions, and in Perplexity's case, organic Reddit discussion. And they are measuring AI visibility as a discipline rather than guessing at it.
The brands that lose? Usually strong on traditional SEO, weak on entity clarity, inconsistent on answer architecture, and invisible in the places the models trust. Their dashboards look healthy. Their pipeline is quietly leaking.
The mistakes I see most often
After running diagnostics across dozens of B2B brands, the same patterns recur.
Treating AEO as a content problem. Most teams respond to the AI search shift by publishing more blog posts about AI. That is content marketing with the word "AI" in the title. AEO requires work across entity, architecture, source signal and measurement. Content is one of four levers.
Over-indexing on a single platform. Teams obsess over ChatGPT and ignore Perplexity, or vice versa. The retrieval systems are different enough that you need a cross-platform view. The 11% citation overlap figure is the most important number most B2B marketers haven't heard.
Letting the incumbent SEO agency redefine AEO as "SEO plus schema". This is the most expensive mistake in the market right now. Schema helps, but it is a single lever inside the second pillar. If your AEO strategy can be executed by adding FAQ markup, it is not an AEO strategy.
Waiting for measurement to get easier. It will not. The teams winning in 2026 are the ones who built a measurement layer manually, accepted the rough edges, and used the data to make decisions. Waiting for a perfect dashboard is a way of conceding ground to the brands who didn't wait.
A 30-minute AEO self-audit for B2B marketers
If you want to stress-test your own position before the next board meeting, here is a condensed version of the audit we run for clients. It takes about half an hour.
1. The entity test. Open ChatGPT, Perplexity and Google's AI Overview. Ask each one "What does [your brand] do?" and "Who are [your brand]'s main competitors?" Note the answers verbatim. If any of them are wrong, vague or list competitors you don't actually compete with, flag an entity issue.
2. The category test. Run your three most important buyer-intent queries across all three platforms. Example: "What are the best [your category] platforms for [your ICP]?" Note whether your brand appears, and if so, where in the answer.
3. The competitor test. Run the same three queries again, but replace your brand name with each of your top three competitors. Compare who gets cited, how often, and in what position.
4. The source test. For every citation that appears across those queries, note the source. Which domains are being pulled? Is your domain among them? If not, which domains are, and do you have a presence on those surfaces?
5. The freshness test. Check the publication dates on your most important category pages. If your pillar content hasn't been updated in the last 12 to 18 months, you are likely losing ground to competitors whose content is fresher.
If you do nothing else this quarter, run this audit. It will tell you, in thirty minutes, whether you have an AEO problem, and roughly how big it is.
The window is open, and it won't stay open
AEO is in the phase every new marketing discipline goes through before it becomes table stakes. The market data is clear enough that ignoring it is a choice. The measurement tooling is rough but workable. The playbooks are being written in real time by the brands who decided not to wait.
B2B marketing teams that treat AEO as a discipline now, with its own strategy, its own measurement, and its own owned workstream inside the marketing function, will compound an advantage every month their competitors spend arguing about whether it matters. The ones that treat it as a side project, or hand it to an agency still thinking in terms of rankings and links, will spend 2027 trying to catch up on ground they didn't realise they were losing.
The brands being cited by AI today are the brands being chosen tomorrow. Everything else is a dashboard.
Request a free AI Visibility Report
---
*Sources: [G2: Does G2 Get Ranked in AI LLM Search?](https://learn.g2.com/tech-signals-does-g2-get-ranked-in-ai-llm-search); [PR Newswire: 73% of B2B Buyers Use AI Tools in Purchase Research](https://www.prnewswire.com/news-releases/73-of-b2b-buyers-use-ai-tools-in-purchase-research-multi-source-analysis-finds-302733319.html); [The Digital Bloom: 2025 AI Visibility Report](https://thedigitalbloom.com/learn/2025-ai-citation-llm-visibility-report/); [McKinsey: The new front door to the internet](https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/new-front-door-to-the-internet-winning-in-the-age-of-ai-search); [Seer Interactive: AIO impact on Google CTR](https://www.seerinteractive.com/insights/aio-impact-on-google-ctr-september-2025-update); [SparkToro: 2024 Zero-Click Search Study](https://sparktoro.com/blog/2024-zero-click-search-study-for-every-1000-us-google-searches-only-374-clicks-go-to-the-open-web-in-the-eu-its-360/); [Adobe: The explosive rise of generative AI referral traffic](https://business.adobe.com/blog/the-explosive-rise-of-generative-ai-referral-traffic); Forrester 2025 B2B Buyer Journey Study.*
Here is the number that should be on every B2B CMO's desk this quarter. In G2's August 2025 buyer survey, 87% of B2B software buyers said AI chatbots like ChatGPT, Perplexity, Gemini and Claude are changing how they research purchases. In the same study, only 12% of B2B SaaS brands appeared when buyers ran category-level searches inside those tools. The other 88% were simply absent from the moment their buyers were forming opinions.
That gap, between where buyers are researching and where brands are visible, is the single biggest unpriced risk in B2B marketing right now. It is also not a distant problem. A multi-source analysis published in March 2026, covering 680 million AI citations and almost two million browsing sessions, found that 73% of B2B buyers are already using AI tools inside their purchase research process. Forrester's 2025 buyer study put a number on the downstream consequence. 61% of the B2B buying journey now completes before a buyer ever contacts a vendor, and that figure climbs every time an AI tool synthesises a shortlist on their behalf.
Meanwhile, McKinsey estimates that around 50% of Google searches already include AI summaries, rising above 75% by 2028, and projects that $750 billion in US revenue will funnel through AI-powered search by 2028. This is a rewiring of how B2B buyers discover, compare and choose, not a marginal channel shift.
The discipline that governs whether you are visible inside those AI-generated answers has a name. It is Answer Engine Optimisation (AEO), and it is a different discipline to SEO.
Why SEO tactics don't translate (and why that matters to your budget)
For most of the last two decades, B2B marketers have optimised for a specific user behaviour. Type a query into Google, scan a list of ten blue links, click one. The entire SEO playbook (keyword targeting, backlinks, domain authority, ranking positions) is a set of levers pulled against that behaviour.
Answer engines don't work that way. When a buyer asks ChatGPT "what are the best account-based marketing platforms for mid-market B2B?", the model doesn't show them ten blue links. It synthesises an answer, names two or three vendors, and sometimes cites a handful of sources. The buyer leaves with a shortlist instead of a search results page.
That one behavioural change breaks several of the core assumptions B2B marketers have been budgeting against.
Rankings don't map to citations. A page that ranks #1 on Google may never be cited by ChatGPT, and a page that doesn't rank in Google's top 20 can be cited repeatedly by Perplexity. The 2025 AI Visibility Report from The Digital Bloom found that only 11% of domains cited by ChatGPT were also cited by Perplexity for the same queries. These are different retrieval systems with different signals.
Backlinks are no longer the dominant signal. In the same study, brand search volume was the strongest predictor of AI citations, with a correlation of 0.334. That is materially stronger than any backlink-based metric. Models are increasingly using brand familiarity as a proxy for trust.
Content freshness suddenly matters in a way SEO never rewarded. Roughly 65% of log hits to cited content were for pages published in the last year, and 79% were from the last two years. AI systems lean toward recent, actively maintained sources.
Traditional measurement is silent on the question that matters. GA4 will not tell you how often ChatGPT recommends you. Your rank tracker will not tell you whether Perplexity is citing your competitor. The measurement stack most B2B marketing teams rely on was built for a world where discovery happened on a SERP.
These differences add up. The inputs, the signals, the measurement and the skills required are distinct enough that treating AEO as "the SEO team's next project" is already producing a second wave of wasted budget across the industry.
The four pillars of AEO for B2B marketers
The methodology breaks down into four pillars. They work as concurrent workstreams rather than sequential steps, and each one pulls a different lever.
1. Entity positioning: make the model understand who you are
Before an answer engine can recommend you, it has to understand what you are. Large language models reason in terms of entities: companies, products, categories, people. If the model's internal representation of your brand is vague, incomplete or confused with a competitor, no amount of content will fix it.
Entity positioning is the work of making sure every AI system has an unambiguous understanding of who you are, what category you compete in, what you do better than alternatives, and who your ideal customer is. The practical work includes Wikidata entries, Knowledge Panel optimisation, structured data (Organization, Product, Software Application schemas), and consistent entity descriptions across high-authority third-party sources.
Diagnostic question for your team: open ChatGPT and ask "What does [your brand] do?" Then ask "Who are [your brand]'s main competitors?" If the answers are vague, wrong, or list your brand alongside companies you don't actually compete with, you have an entity problem. Entity sits upstream of every other AEO lever, so this is usually where the work starts.
2. Answer architecture: structure content so models can extract and cite it
Most B2B content is written for humans scrolling on a laptop. Answer engines don't scroll. They extract. Content that wins citations is content that answers specific questions directly, in a structure the model can parse.
The brands that get cited repeatedly across platforms usually aren't the ones producing the most content. They are the ones whose content is architected for extraction: clear definitions, direct answers at the top of sections, FAQ blocks with schema, concise paragraphs, well-structured headers, and explicit comparisons. Seer Interactive's data on AI Overviews found that brands cited in Google's AI answers earn 35% more organic clicks and 91% more paid clicks. The same Seer analysis showed that when AI Overviews are present and your brand is not cited, organic CTR drops 61% and paid CTR drops 68%. Answer architecture is what determines which side of that line you sit on.
3. Source signal: earn mentions in the places LLMs actually weight
Not all sources are weighted equally. Each AI platform draws from a different constellation of trusted inputs, and the differences are significant. The same 2025 cross-platform analysis found that Reddit accounted for 46.7% of top Perplexity citations but under 10% on ChatGPT after a September 2025 rebalancing. ChatGPT leans heavily on Wikipedia and long-standing editorial sources. Google AI Overviews favour a diversified cross-platform presence.
Source signal is the discipline of earning mentions, reviews and references in the specific places each platform treats as authoritative for your category. For a B2B SaaS brand, that usually means G2 and Gartner Peer Insights (G2's own internal study confirms they are heavily cited across LLMs), plus category-specific industry publications, relevant subreddits, and any analyst coverage that ends up in the training corpus. This is PR, earned media and community work done with a very specific retrieval target in mind.
4. Measurement: track what your rank tracker can't see
If you can't measure AI visibility, you can't manage it, and you certainly can't defend the budget in front of a board. The four metrics we track for clients map directly to the commercial question every B2B CMO cares about: are we showing up when our buyers are choosing?
AI Mention Rate. For a defined set of 20 to 50 buyer-intent queries, what percentage of the time does your brand appear in the answer across ChatGPT, Perplexity, Claude, Gemini and Google AI Overviews?
Citation Authority. When those platforms cite sources, how often is your domain among them, and how does that compare to your top three competitors?
Entity Clarity Score. When you ask the model directly "What does [brand] do?", is the answer accurate, complete and differentiated, or generic and interchangeable?
Answer Ownership. For the queries that matter most to your pipeline, are you the primary recommendation or a supporting mention?
This is the layer most B2B marketing teams are missing entirely. Only 22% of marketers currently track AI visibility and traffic, and only 25.7% plan to develop content specifically for AI citations. That gap is, for the moment, the single biggest competitive opportunity in B2B marketing.
You can read the full methodology behind each of these pillars on the [growthvibe AI search optimisation methodology page](https://www.growthvibe.com/ai-search-optimization-services/).
A worked example: what this looks like in martech
Consider a mid-market martech category, say, account-based marketing platforms. Ask ChatGPT, Perplexity and Google's AI Overview the same question: "What are the best account-based marketing platforms for B2B companies with 200 to 2,000 employees?"
Run it once and you'll notice a pattern. Two or three vendors show up consistently across all three engines. A handful appear on one platform but not the others. And a long tail of category players, some of them with significantly better products, bigger marketing budgets and stronger Google rankings, don't appear at all.
When we dig into the brands that win across all three platforms, the same four things are usually true. Their entity is clear (the model knows what they do without hesitation). Their owned content is structured for extraction, with direct answers, comparison pages and FAQ schema. They have strong, recent source signal across G2, Gartner coverage, analyst mentions, and in Perplexity's case, organic Reddit discussion. And they are measuring AI visibility as a discipline rather than guessing at it.
The brands that lose? Usually strong on traditional SEO, weak on entity clarity, inconsistent on answer architecture, and invisible in the places the models trust. Their dashboards look healthy. Their pipeline is quietly leaking.
The mistakes I see most often
After running diagnostics across dozens of B2B brands, the same patterns recur.
Treating AEO as a content problem. Most teams respond to the AI search shift by publishing more blog posts about AI. That is content marketing with the word "AI" in the title. AEO requires work across entity, architecture, source signal and measurement. Content is one of four levers.
Over-indexing on a single platform. Teams obsess over ChatGPT and ignore Perplexity, or vice versa. The retrieval systems are different enough that you need a cross-platform view. The 11% citation overlap figure is the most important number most B2B marketers haven't heard.
Letting the incumbent SEO agency redefine AEO as "SEO plus schema". This is the most expensive mistake in the market right now. Schema helps, but it is a single lever inside the second pillar. If your AEO strategy can be executed by adding FAQ markup, it is not an AEO strategy.
Waiting for measurement to get easier. It will not. The teams winning in 2026 are the ones who built a measurement layer manually, accepted the rough edges, and used the data to make decisions. Waiting for a perfect dashboard is a way of conceding ground to the brands who didn't wait.
A 30-minute AEO self-audit for B2B marketers
If you want to stress-test your own position before the next board meeting, here is a condensed version of the audit we run for clients. It takes about half an hour.
1. The entity test. Open ChatGPT, Perplexity and Google's AI Overview. Ask each one "What does [your brand] do?" and "Who are [your brand]'s main competitors?" Note the answers verbatim. If any of them are wrong, vague or list competitors you don't actually compete with, flag an entity issue.
2. The category test. Run your three most important buyer-intent queries across all three platforms. Example: "What are the best [your category] platforms for [your ICP]?" Note whether your brand appears, and if so, where in the answer.
3. The competitor test. Run the same three queries again, but replace your brand name with each of your top three competitors. Compare who gets cited, how often, and in what position.
4. The source test. For every citation that appears across those queries, note the source. Which domains are being pulled? Is your domain among them? If not, which domains are, and do you have a presence on those surfaces?
5. The freshness test. Check the publication dates on your most important category pages. If your pillar content hasn't been updated in the last 12 to 18 months, you are likely losing ground to competitors whose content is fresher.
If you do nothing else this quarter, run this audit. It will tell you, in thirty minutes, whether you have an AEO problem, and roughly how big it is.
The window is open, and it won't stay open
AEO is in the phase every new marketing discipline goes through before it becomes table stakes. The market data is clear enough that ignoring it is a choice. The measurement tooling is rough but workable. The playbooks are being written in real time by the brands who decided not to wait.
B2B marketing teams that treat AEO as a discipline now, with its own strategy, its own measurement, and its own owned workstream inside the marketing function, will compound an advantage every month their competitors spend arguing about whether it matters. The ones that treat it as a side project, or hand it to an agency still thinking in terms of rankings and links, will spend 2027 trying to catch up on ground they didn't realise they were losing.
The brands being cited by AI today are the brands being chosen tomorrow. Everything else is a dashboard.
Request a free AI Visibility Report
---
*Sources: [G2: Does G2 Get Ranked in AI LLM Search?](https://learn.g2.com/tech-signals-does-g2-get-ranked-in-ai-llm-search); [PR Newswire: 73% of B2B Buyers Use AI Tools in Purchase Research](https://www.prnewswire.com/news-releases/73-of-b2b-buyers-use-ai-tools-in-purchase-research-multi-source-analysis-finds-302733319.html); [The Digital Bloom: 2025 AI Visibility Report](https://thedigitalbloom.com/learn/2025-ai-citation-llm-visibility-report/); [McKinsey: The new front door to the internet](https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/new-front-door-to-the-internet-winning-in-the-age-of-ai-search); [Seer Interactive: AIO impact on Google CTR](https://www.seerinteractive.com/insights/aio-impact-on-google-ctr-september-2025-update); [SparkToro: 2024 Zero-Click Search Study](https://sparktoro.com/blog/2024-zero-click-search-study-for-every-1000-us-google-searches-only-374-clicks-go-to-the-open-web-in-the-eu-its-360/); [Adobe: The explosive rise of generative AI referral traffic](https://business.adobe.com/blog/the-explosive-rise-of-generative-ai-referral-traffic); Forrester 2025 B2B Buyer Journey Study.*
Content
Apr 7, 2026
Content
