I’ve spent 18 years in marketing. I’ve led teams, built departments, launched campaigns across four continents, and worked with companies from scrappy startups to global enterprises. And the single most consistent pattern I’ve seen is this: most marketing problems aren’t marketing problems.
They’re systems problems. Process problems. Alignment problems. Communication problems wearing a marketing costume.
The industry has it backwards
The marketing industry is addicted to execution. More campaigns. More content. More channels. More tools. The assumption is always that doing more will fix what’s broken.
It won’t.
If your funnel leaks at the consideration stage, no amount of top-of-funnel content will fix it. If your CRM doesn’t talk to your email platform, automating more workflows just speeds up the dysfunction. If marketing and sales disagree on what a qualified lead looks like, generating more leads just generates more arguments.
The fix isn’t more activity. It’s better diagnosis.
What diagnosis actually means
When I say “diagnose,” I don’t mean running an audit that produces a 200-slide deck nobody reads. I mean sitting with your team, understanding how work actually flows through your organisation, and finding the 3–5 structural issues that explain 80% of your underperformance.
The goal isn’t to find everything that’s wrong. It’s to find the things that matter most — and fix them in the right order.
This requires talking to people. Not just the marketing team — sales, customer success, product, leadership. The gaps between these teams are where most marketing problems actually live.
Why AI changes the equation
AI doesn’t replace strategy. It amplifies it. A good strategy deployed with AI-powered automation can do in weeks what used to take quarters. But a bad strategy deployed with AI just fails faster and at greater scale.
This is why I’m obsessed with getting the diagnosis right before touching any technology. AI is the accelerant. Strategy is the direction. You need both, in that order.
The companies that will win in the next decade aren’t the ones with the most sophisticated AI stack. They’re the ones who understand their problems deeply enough to know exactly where AI should — and shouldn’t — be applied.
The 3-month constraint
I work in 3-month engagements. Not because the work can’t take longer, but because constraints force clarity.
When you have 3 months, you can’t boil the ocean. You have to prioritise ruthlessly. You have to focus on the structural issues that will create the most leverage. You have to deliver something your team can actually execute — not a theoretical framework they’ll shelve.
The constraint also prevents dependency. I’m not interested in becoming a permanent fixture in your org chart. I want to make myself unnecessary. The best outcome is a team that never needs to call me again.
Design follows diagnosis
Once you understand what’s actually broken, the design becomes obvious. Not easy — but obvious. The funnel architecture writes itself when you know where buyers drop off. The automation workflows become clear when you’ve mapped the manual processes. The tech stack decisions simplify when you know what data needs to flow where.
Diagnose first. Then design.
That’s not a tagline. It’s the entire philosophy. Every engagement I run, every recommendation I make, every strategy I deliver starts with the same question: what’s actually going on here?
If you’re tired of marketing advice that starts with solutions before understanding the problem, we should talk.
The tools are never the answer
In every engagement, someone asks me which tools they should use. My answer is always the same: that depends on what you’re trying to do. And what you’re trying to do depends on what’s actually broken — which requires diagnosis.
The marketing technology landscape has over 11,000 products. Companies are drowning in tools. The average mid-market marketing team uses 12–15 platforms. And most of them were purchased to solve a symptom, not a root cause.
A tool purchased to “fix lead gen” doesn’t fix lead gen if the problem is actually a misalignment between marketing and sales on what constitutes a qualified lead. A tool purchased to “improve content” doesn’t improve content if the problem is that nobody knows who the audience is or what they care about.
Every tool purchase is a hypothesis about what’s wrong. Diagnosis turns that hypothesis into evidence. Without it, your tech stack is a collection of expensive guesses.
I don’t recommend tools until month two of an engagement — after the audit has revealed what’s actually happening. By that point, the tool decisions are almost always different from what the team expected at the start.
Who this is for
This approach isn’t for everyone. If you need a freelancer to run your Google Ads or write your blog posts, I’m not the right fit. If you want a retainer-based agency relationship with monthly reports and incremental improvements, there are thousands of options.
This is for companies that suspect their marketing problems are structural. Companies that have tried the tactical fixes — more budget, more tools, more campaigns — and found they didn’t move the needle. Companies that want someone to come in, understand the whole picture, and tell them what’s actually going on.
It’s for marketing leaders who know something is wrong but can’t quite articulate what. Who have the budget and the team but not the strategy. Who are tired of guessing and want answers backed by evidence.
If that sounds like you, let’s have a conversation.
What I’ve learned from 18 years of getting it wrong
I haven’t always worked this way. In my early career I ran campaigns first, asked questions later. I optimised channels without understanding systems. I built strategies on assumptions rather than evidence. And the results were inconsistent — sometimes things worked brilliantly, sometimes they failed spectacularly, and I often couldn’t explain why.
The shift happened when I started asking “why is this broken?” before “how do we fix it?” That single change in sequence transformed my outcomes. Diagnosis before design. Evidence before execution. Understanding before action.
After 18 years and hundreds of engagements across four continents, the data is clear: strategy built on diagnosis consistently outperforms strategy built on assumption by 2–4× in pipeline impact. Not because the tactics are different, but because they’re applied to the right problems. That’s the approach I bring to every engagement, and it’s the approach I’ll bring to yours.
I didn’t arrive at this philosophy overnight. For years, I made the same mistakes I now diagnose in others. I ran campaigns without understanding the underlying business problems. I recommended tools before mapping processes. I built strategies that looked impressive in slide decks but fell apart in execution.
The turning point came when I started asking “why” before “what.” Why are leads not converting? Not “what campaign should we run?” Why does the sales team ignore marketing-sourced leads? Not “what CRM should we buy?” Why does content get published but never drive pipeline? Not “what topics should we write about?”
The answers to “why” are almost never what people expect. The lead conversion problem turns out to be a handoff timing issue between marketing automation and the SDR team. The sales-marketing misalignment turns out to be a definitional disagreement about what “qualified” means. The content problem turns out to be a distribution architecture issue, not a content quality issue.
The moment you shift from “what should we do?” to “what’s actually happening?” is the moment marketing strategy becomes useful.
That shift — from prescription to diagnosis — changed everything about how I work. It’s why I insist on the audit phase before any strategy work begins. It’s why I interview 6–10 stakeholders instead of just the marketing team. It’s why my recommendations sometimes surprise clients: because they’re based on what I found, not what everyone assumed.
After 18 years across four continents, working with companies from 10-person startups to FTSE 100 enterprises, I’ve never seen a marketing problem that didn’t benefit from better diagnosis. The fix is usually simpler than people expect. Getting to the right diagnosis is the hard part. That’s the work I do.