Founder, P33 | Executive Thought Leadership Agency

Helped 50+ B2B tech companies build their Founder/CEO Brand and implement Executive Thought Leadership Programs for LinkedIn. Customers, results & process: project33.io

About me:

I'm Finn, 29, grew up in Bremen, Germany, studied Physics & Philosophy in Heidelberg for 3 semesters, dropped out of college in 2017 because I was doing it for other people, flew to New York with no plans, documented the journey on Linkedin, Instagram and Youtube, and started my first company (Project 33) on the back of having grown a small audience. We're a small remote agency that helps B2B founders & execs create thought leadership content for Linkedin.

In my free time, which I try to have as much as possible of, I read (fav author: Nassim N. Taleb), write, run, lift, code (currently building an app), cook, make Youtube videos, turn books into Instagram accounts, grapple (BJJ), and travel (lived in NYC, Cape Town, Bali, Minsk, CMDX, Lima & Antalya so far). In December 2020 I married the most beautiful woman in the world. In January 2023, I became dad to the most beautiful baby girl. We currently live in Berlin, Germany.

Finn Thormeier

People forget that *high engagement* usually means *easy to engage with*. What's easy to engage with? Short posts, selfies, black/white takes. 

That's the real reason why there's so much of that stuff on Linkedin.

So when your local Linkedin influenster who gets hundreds of likes on every post and whose main product is a $99 course tells you that this is the kind of content your NEED to create, remember:

In B2B, inbound/customers/conversations with VPs+ often come from high trust. 

What builds high trust? Deep insights, balanced/nuanced takes, complete breakdowns - aka stuff that can't be skimmed in 3 seconds.

Top LinkedIn ghostwriting agency for CEOs, founders & execs -- Founder at Project 33 and Host of the Executive Brand Podcast

I discovered Louis Grenier a couple weeks ago - how did it take me so long?? This man grew his LinkedIn to 39,000+ followers and built a successful solo-consulting biz while breaking ALL the rules of LinkedIn the "gurus" want you to believe in:

- Bright orange profile pic
- Uses the F word ALL the time
- Spent $8,500 to produce a YouTube (!) mini-series to market his services
- Wildly mixes his post formats
- Regularly includes links in the post copy
- Publicly ROASTS his sponsors
- Pays zero attention to the algorithm

Dave Gerhardt called him the french Harry Dry

If the all LinkedIn Gurus were right, Louis should be nowhere near where he is today, getting nowhere near the results he's getting.

Want to learn how he does it?

This Thursday at 11am EST, I'm doing a live Zoom call with Louis to ask him about his approach and how, you too, can Stand The F*ck Out. We'll include audience Q&A, so you can bring your own questions.

Join us here: https://lnkd.in/dQ7J9vXh

I strongly believe almost all companies who currently do great marketing, I'd eg. list Clay, PostHog, 37signals, have some version of this mindset when it comes to brand. Here articulated by Chris Evans, co-founder of incident.io. 

You gotta have taste, take some risks, have fun, think about the customer, and just trust that it will all somehow, in the end, benefit your company. You can't measure it and you shouldn't even try. Almost by definition, if you could measure and attribute brand marketing, it would be called demand gen.

In prepping for a podcast episode, I was reading a CEO's Linkedin content today. What stood out to me: I actually LEARNED things. It's crazy that this feels like a rare experience these days on Linkedin.

The posts weren't formatted with tons of bullet points and 5-part lists and one-line paragraphs.

The hook was just a regular sentence that didn't feel "optimized"

The overall posts and topics didn't feel engineered - no trend jacking - just grounded lessons from 10 years being in the industry.

The average post of this CEO got 20-40 likes.

There's plenty of people in his space that are getting 10x that.

But he was talking about marketing fundamentals, lessons learned, deeply thought-out takes or rebuttals on current trends, and I actually found myself taking notes, rethinking certain decisions of mind, doing additional research to fully understand his point of view.

Maybe because of this, when I looked at the 20-40 people who did engage, many were CMOs, VPs, CEOs, and a good amount of lengthy comments, people who actually, read, internalized and responded to the post with their own thoughts.

This is much rarer than it should be.

So much of content is performance. Probably my own included. Trying to fit some template. Trying to stick to some "best practices". Optimized and engineered for engagement, which is often a race to the bottom.

My sense is that this CEO has his own quality bar. Decides what to publish based on what *he* deems insightful, not what the algorithm is nudging him towards. Maybe I'm wrong here.

We should normalize publishing content we feel PROUD of, in the style that feels like ourselves - that's the bar.

My podcast episode with Jessica Gilmartin is live!!! Jessica has an insanely impressive track record: CMO at Calendly, Head of Revenue Marketing at Asana, Head of Product Marketing at Google. Today, she advises founders and first-time CMOs through $100M ARR on marketing, GTM strategy, hiring and org design.

And last week, she joined me on The Executive Brand podcast.

What we cover:

- Why CMO + CRO combo roles usually fail
- Why companies now hire CMOs from smaller, scrappier startups
- Where AI is truly useful vs pure hype
- Why random acts of marketing kill momentum
- How Calendly moved from viral PLG to focused enterprise ABM
- The real reason CMOs only last 18 months
- Why taste, courage, and focus still matter more than tools
- And much more

Listen here:

-- YouTube: https://lnkd.in/grQb6kgv
-- Spotify: https://lnkd.in/gpBmkJWg
-- Apple: https://lnkd.in/gXPSpKEU
-- Substack: https://lnkd.in/gBeDP56X

Some of my takeaways:

1. We’ll replace most of our day-to-day work with AI in 5-10 years. But right now board members are mandating AI adoption without specific use cases. The reality is AI is making teams 10-20% more efficient and that it works as an enabler, but not as a replacement. The best use cases she’s seeing are data enrichment for lead prioritization, competitive research for product marketing, and using LLMs as synthetic customer panels

2. There are three paths to CMO: via product marketing, via demand gen, and via brand. In B2B, 50% of CMOs come from product marketing, 50% from demand gen, almost none from brand. That might be an opportunity

3. CEOs keep hiring the wrong CMO. They want a unicorn who's great at both strategic messaging (product marketing) and growth (demand gen). It’s like finding an engineer who's great at backend AND designing beautiful interfaces. Hire for your actual problem/bottleneck right now, not the one you’ll have at $100M

4. Attribution is broken and that’s okay. You’re getting 70-80% accuracy at best. Jessica’s approach is to use the 80-20 rule. Get directionally correct data so teams understand where they can make impact and then work from there. The bigger issue is that companies wait too long to implement basic data and reporting infrastructure

5. Random acts of marketing kill focus. At Calendly, Jessica pivoted the entire team to one thing: repositioning for enterprise customers. Marketers hate focus and they want to sprinkle seeds everywhere. But the winning strategy is making big bets, being explicit about trade-offs, and ensuring no one goes off track

Reminder: your most interesting thoughts are those you want to keep to yourself.

LinkedIn Playbook with Jess Cook and Joshua Perk of Vector 👻

Data Strategy and Optimisation expert - More Revenue, Less Cost

I’m a former investment banker with over a decade of experience in financial modeling, trading, and asset pricing.

Before founding Growth Dynamics, I worked as a Data Scientist at Skai and later as Measurement Manager and Principal Data Strategist at Oracle, helping global brands connect their marketing investments to real business outcomes.

That background taught me one thing: models only matter if they hold up in reality.

In finance, I learned that theory often breaks the moment it meets the market. Marketing is no different.

At Growth Dynamics, we bring that same real-world discipline to measurement. We specialize in long consideration journeys and offline sales, the complex paths where attribution breaks and intuition often misleads.

We’ve been on the side of operators, owning budgets, defending investments, and making trade-offs that theory can’t capture.

Our goal isn’t to build elegant models but useful ones that drive measurable impact and profitable growth.

Charles-Antoine D.

20-30% of your conversion budget is probably doing nothing.
Not underperforming. Doing nothing.

We see this in audit after audit. High-ticket B2C and long-cycle B2B brands spending 80%+ on bottom-of-funnel. The finance team points to platform ROAS and the attribution tool that costs a quarter million a year. "Every dollar is working."

The data tells another story.

Diminishing returns. Early spend captures high-intent buyers efficiently. But as you scale, you exhaust the pool of people ready to buy right now. The budget keeps growing. The available demand doesn't.

That last 20-30% of spend buys clicks, but the marginal return is often below 1. You're paying to acquire customers you would have acquired anyway.
Platform ROAS hides this because it shows an average. The average looks fine. The margin on that final tranche is gone.

We call this the Deathzone. Systematic margin bleed, invisible to standard measurement.

One example, the diminishing returns curve had completely flattened. We were 30% over-extended. We cut that 30%. Revenue didn't move. Millions freed up annually ready to be invested in preference building, topline unchanged.

📈 Run the test:
Plot mid-funnel traffic against conversion spend. When the curve flattens, you've found your waste. Cut there. You either bank the margin, or you reinvest it into growth. Second option is of course best. 

More conversion spend without a pool of potential buyers doesn’t scale revenue. It scales waste.

👇 
We put all our learnings into one growth playbook. DM me if you'd like a copy. Also reach out if you want to subscribe to our One Move to Grow newsletter and join our private Slack channel.

Charlie de Thibault

Turn $25m+ media budgets into confident growth decisions

Tomorrow I'm handing over the first printed copy of my Growth Measurement Playbook to a +$10bn B2C brand.

Not as a sales pitch. As a tool they can actually use.

 Most vendor pitches my clients see follow the same playbook:
👉Oversell the capabilities
👉Hide the limitations
👉Use jargon to obscure what the model actually can't do

Large clients don't fall for it. They know when you're hiding shortcomings.

I do the opposite.

𝐓𝐡𝐢𝐬 𝐩𝐥𝐚𝐲𝐛𝐨𝐨𝐤 𝐜𝐨𝐯𝐞𝐫𝐬:
✓ Why MTA systematically leads brands to underinvest in brand building (and over-invest in bottom of the funnel) leading to lower margins and higher customer acquisition costs
✓ Why statistical models struggle with long consideration journeys (and what to do about it)
✓ The exact limitations of MMM, incrementality testing, and surveys; not just their strengths
✓ A 5-step measurement roadmap that actually works for high-ticket products with offline sales
✓ How to detect bot traffic with GA4 (no fancy vendor needed)
✓ Why most brands waste 20-30% of budget in the "deathzone" - and how to escape it

𝐖𝐡𝐚𝐭 𝐦𝐚𝐤𝐞𝐬 𝐢𝐭 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭:

I run models rigorously. I explain things simply. And I tell you exactly where each method breaks down.

Because my job isn't to sell you a black box. It's to help you make better decisions with imperfect data.

𝐖𝐚𝐧𝐭 𝐭𝐡𝐞 𝐩𝐥𝐚𝐲𝐛𝐨𝐨𝐤?
connect with me and DM me!

Your retargeting shows a 4x ROAS. The CFO is satisfied. That’s the problem.
Algorithms optimise for attribution, not profit.

When you tell a platform to maximise conversions, it finds the easiest path. Cart abandoners. Brand searchers. People with high intent signals who were likely to convert anyway.

The algorithm ignores the harder job of reaching new people. It focuses on harvesting existing demand because attribution rewards ease, not growth.

There's a second issue. Temporal discounting. A 7-day click window trains the system to ignore anyone who takes longer to decide. In high-ticket B2B or luxury retail, that's nearly everyone.

As conversion spend scales, reach stops growing and frequency explodes. You’re not reaching more people. 

You’re showing up more often to the same ones.

LVMH didn't build a business selling $2,000 handbags through performance marketing. They invested in brand for decades. The margin they command today is the return on that investment.

Meanwhile, a lot of SaaS companies pay $100 a click hoping it leads to a $500k deal.

 The economics rarely work.

“Performance marketing rents your audience. Brand building owns it.”
How much of your conversion spend is actually incremental? If you haven’t tested it, assume less than you think.
👇 
We put all our learnings into one growth playbook. DM me if you'd like a copy. Also reach out if you want to subscribe to our One Move to Grow newsletter and join our private Slack channel.

An incrementality test is a great way to measure the impact of media on your brick-and-mortar sales… until this happens… #storyofmylife

Where is your brand winning? Where is it slipping? This map shows Share of Search by States : a proxy for brand preference that actually predicts market share.

Green = gaining ground. 
Red = losing it.
The darker the colour, the bigger the swing.

Most brands have no idea this data exists, let alone how to use it. But it's sitting right there in MyTelescope

When I first shared this map, the DMs started rolling in.
"How did you build this?"
"Can you share the methodology?"
"Is there a tool for this?"

🎁 So we're open-sourcing the code.🎁

Next Thursday, Rodrigo Pozo Graviz and I are going live to show you exactly how to build this for your brand:
→ The Google Colab notebook 
→ How to pull and structure the data 
→ How to generate maps like this one

No lead form. No paywall. Just the methodology.

Vinay W Tiwari, Bobby den Bezemer and 65 other attendees

Share of Search - Build your preference map and unlock Brand Budget

If 20–30% of your conversion budget disappeared tomorrow, would revenue move?

In a lot of audits we run, it doesn’t.
That spend sits in what I call the Deathzone:
 
Money that looks productive in dashboards, but produces no incremental sales and quietly bleeds margin.
I break down:
• Why ROAS hides the problem
• How saturation shows up before revenue drops
• And the exact test we use to identify dead spend
 
Video link in the comments:


👇 
We put all our learnings into one growth playbook. DM me if you'd like a copy. Also reach out if you want to subscribe to our One Move to Grow newsletter and join our private Slack channel.

You can't complain about stalling growth while using multi-touch attribution to evaluate your marketing impact.

That's like being upset your car ran out of petrol because you didn't stop at the station.

The benchmarkit report shows it clearly: marketers know they need to spend more on brand. They want to. But then we use MTA to evaluate their impact. A tool that is completely unable to truly understand what drove the sale. 

So that's where the budget goes.

Here's the problem: marketing is a two-stage process.
1. You build an audience willing to buy from you. 
2. You capture demand.

This isn't astrophysics.

Most buyers choose a brand they already know before they start their purchase journey.

MTA only sees the capture stage. It targets everyone who's in-market, but the people who've never heard of you? They're not buying regardless of how many touchpoints you serve them.

Should a fisherman buy more nets and stop buying bait to catch more fish?
Should a football team only hire strikers because they're the ones scoring?
Should a farmer reduce spend on seeds to buy more harvesting tools?

None of the above makes sense. But that's exactly what MTA leads you to do with your budget.  

On top of that just a few interviews with prospects will tell you that the MTA story is very different from what prospects say. 

So if your growth is flattening and you're still using MTA to judge what's working, the attribution isn't revealing your problem. It is your problem.

👇 
We put all our learnings into one growth playbook. DM me if you'd like a copy. Also reach out if you want to subscribe to our One Move to Grow newsletter and join our private Slack channel.

When someone in my team says “I am not good at it” my answer is always: you haven’t done it enough yet.

You are what you repeatedly do, and you can be good at it by doing it long enough.

I wish I understood that earlier in my career, and I’m making sure my team understands it earlier in theirs.

There are very few things you can’t do.

You can be good at anything just by doing it long enough.

Once I understood that, I stopped believing in “talent.” A term often used to justify why one person can do what we can’t.

The truth is that “talented” person just showed up more often than somebody else did.

Here’s what you’ll mess up:
❌Your first set of push-ups
❌Your first sales call
❌Your first post on LinkedIn
❌Your first networking event
❌Your first marketing campaign
❌Your first year as an entrepreneur

Here’s what you’ll do great:
✅Your hundredth set of push-ups
✅Your hundredth sales call
✅Your hundredth post on LinkedIn
✅Your 50th networking event
✅Your 50th marketing campaign
✅Your 10th year as an entrepreneur

Small, daily, seemingly insignificant improvements, when done consistently over time, lead to stunning results.

Now, does talent exist? Sure. If you’re 5’3”, you’re likely not going to have a great basketball career. 

But for the skills that actually move your career most people quit long before talent ever becomes the limiting factor.

Just stick to one thing you really want to do and show up. It’s that simple.

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Our 2026 objective: geo-level growth optimisation.
We're sharing the full plan publicly. We'll post learnings openly as the year unfolds.

👉 Here's the shift:
Most brands optimise marketing at market level. That averages away the differences that actually drive ROI.

$100k in one geo can generate $350k gross profit. The same $100k in another generates $150k. Same channel, same creative, same week. Completely different outcome.

The difference comes down to local factors: competition, media costs, saturation, offline footprint, demand. A blended view hides this and leads to wrong allocations.

So we're moving clients to a geo-first operating system. The geo becomes the unit of action, whether that's DMAs or states depending on market and media mix. Budget moves based on where the next dollar delivers the most incremental profit.

👉The reason: 
We are selling growth, not measurement. 

A lot of approaches look rigorous at national level but quietly fall apart at geo level, especially when offline is in the mix. The output looks precise, but the decisions are wrong. We are not building something elegant. We are building something that gives the right answer, even if less tidy.

👉What changes:
- One financial target:
Incremental profit by geo: (incremental revenue × margin) minus spend. Online and offline. No vanity metrics. CFOs can read it without translation.

- One growth target:
Durable buyer preference by geo, tracked with leading indicators like Share of Search and branded demand. These move before revenue lands and stop you over-optimising conversion at the expense of future demand.

- MMM remains the strategic backbone:
We move from one slow national model to a layered approach connecting brand demand, mid-funnel behaviour, and profit. MMM stays the anchor for long-run allocation. Geo signals and local tests provide speed and granularity for weekly reallocation.

- Testing becomes local:
We run geo tests to confirm incrementality and learn local dynamics. Results are true for the geos tested. Extrapolation requires modelling, not assumption. This goes against the view that averaging treated market impact and extrapolating nationally is fine. We ran enough tests last year to say it is not.

- Offline is in scope:
Same system answers ROI questions for new shops or their local impact. If it moves demand at geo level, we measure it. Vendor algos are great online but not perfect with offline. We are not trying to beat the algos. We want to define how spend should split between brand preference and in-market conversion, taking offline into account.

We're not proving "$X on a channel drives $Y revenue." We're deciding where to place the next dollar.

Follow along. We'll share what works, what doesn't, and what we learn.
______
If you work with high-ticket products, long consideration journeys, or offline sales, we've put everything we know into a growth measurement playbook. 𝐃𝐌 𝐦𝐞 𝐚𝐧𝐝 𝐈'𝐥𝐥 𝐬𝐞𝐧𝐝 𝐢𝐭 𝐨𝐯𝐞𝐫!

At any given moment, roughly 5% of your market is ready to buy. The other 95% will buy later. 

Three months, six months, a year from now.

A lot of brands put 80-90% of their budget into that 5% slice. Paid search, PMAX, shopping, retargeting. All chasing the same small group of people who've already decided to purchase.

Two problems with this.
First: you’re paying to intercept demand, not create it. Someone searches your brand, you bid on it, they convert, the dashboard takes credit. Incrementality tests consistently show many of those conversions would have happened anyway. You didn’t drive the sale. You paid a tax to the platform to be present when it happened.

Second: While you fight over today’s buyers, you ignore tomorrow’s. In high-ticket categories, roughly 80% of buyers choose a brand they already knew before their buyer journey. By the time the first search happens, the decision is mostly made.

By the time they enter the market, the winner is already decided. It’s whoever built familiarity before the search.

How much of your spend is creating future demand, and how much is just harvesting demand that already exists? If you can’t answer that, that’s the problem.

We put all our learnings into one growth playbook. DM me if you'd like a copy. Also reach out if you want to subscribe to our One Move to Grow newsletter and join our private Slack channel.

ROI is essential. But if its only lens, competitors will quietly win the shortlist.

Most marketing debates break down because we treat marketing like finance.

In finance, the model is straightforward:
Money in, money out. what's the ROI? 

Marketing behaves differently. its a two-stage system:
1. Build preference 
2. convert that preference  

Why that matters:
- Only a small share of your ICP is in-marketing at any given time.
-  And when they are in-market , many buyers start with a shortlist of brands they already trust. 

So the real job of marketing is not only to "capture demand".
It is to earn a place on that shortlist before the buying cycle begins.

If you do not invest in preference, you are leaving the door open for competitors to shape that's shortlist and take market share and your overall ROI will decrease,

Short-term attribution works best when the click is close to the purchase.
But preference is built over time ,and it shows up indirectly:
more branded demand , high win rates, faster cycles, lower CAC.

The risk  is when we apply short-term measurement expectations  to long-term work. 

That's when teams optimise for attributed ROI instead of focusing to this question: "Are we increasing the percentage of the market willing to buy from us when they enter the buying cycle?"

👇 
We put all our learnings into one growth playbook. DM me if you'd like a copy. Also reach out if you want to subscribe to our One Move to Grow newsletter and join our private Slack channel.

Mid-Funnel Reveals Truth
Attribution tells you where people convert, not where they discover you.
 Mid-funnel modeling connects the dots between first touch and final sale, revealing your real buyer journey.
 It’s not magic. It’s just better measurement.

Buyers Don’t Convert Where They Discover
 Most people don’t buy through the same channel where they found you. That’s why top-of-funnel looks weak in attribution. Mid-funnel modeling helps you see what really creates demand.

Share of Search - Build Your preference map and unlock Brand Budget

A lot of people really like the idea of creating a preference map using brand searches by DMA. The good news is we're moving the code to open source so everybody can use it. On Thursday during a LinkedIn Live, Rodrigo and Charlie are going to cover how to use the code in a Google Colab notebook and create reports.

Matt Rubinstein, Goddy Tams George and 4 other attendees

Share of Search - Build Your preference map and unlock Brand Budget

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The Battle

Finn Thormeier

Charles-Antoine D.

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The Battle

Finn Thormeier

Charles-Antoine D.

Followers

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Engagements

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Finn Thormeier's LinkedIn Performance

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