Scaling GTM Ops for B2B SaaS Startups ⚙️🛠️

As a Marketing and Revenue Operations Consultant with over 10+ years of experience, I help the top startups & Fortune 500 Companies grow their revenue through operational excellence 🚀💸

My Background & Experience: 
★ Scaled operations at 10+ Companies that were growing at 100% Year over Year 📈
★ Over 30+ certifications in Marketing & Revenue Sales Technology 🏆
★ Launched 10+ PLG & Freemium Efforts 🚀
★ Scaled 100+ Salesforce Instances 🛠️ ☁️
★ Scaled 100+ Hubspot Instances ⚙️
★ Optimized 75+ Marketing & Revenue Analytics & Attribution Tools 🛠️
★ Managed Millions of Dollars in MarTech Spend
★ Sales/Marketer Turned Ops Engineer  💸

My Portfolio: 
★Samsung / Samsung NEXT
★Connectwise
★AT&T
★WPP
★Madkudu
★15Five
★Lever
★Aerolase
★Madison Square Garden
★ControlCase
★Auvik
★Ramp
★Productiv
★John Varvatos
★ and many more.....

My Beliefs: 
★Ops Teams need more bandwidth via On-Demand Technical Talent #ExtraBandwidth
★Business Teams need solutions that make technical things easy
★Repeatable & Scalable Lead Generation is achievable
★Marketing & Revenue Operations can be strategic but requires a holistic approach to the business 
★Work can be and should be Fun! 

Outside of work, I am: 
★ Most importantly, a Family Man 👨‍👩‍👦
★ Diehard Knicks & Giants fan🏀🏈
★ Foodie 🍕🍔
★ Lover of nature 🌴
★ Sneakerhead 👟
★ Health Fanatic 💪🏽
★ Real Estate Investor 🏡

For more information on how my expertise can help your company grow, please visit www.JayOh.io.

Joe LaGrutta, MBA

MQL handoffs should not feel like a liability transfer.
Yet in most orgs, they do.

Marketing optimizes for lead volume.
Sales optimizes for revenue.

The definition sits in the middle, fuzzy.

If your MQL is based on surface level activity, you are not qualifying intent.
You are logging engagement.

Real alignment happens when:
-ICP is enforced in scoring
-Behavioral signals are weighted by buying stage
-Disqualifiers are codified
-Sales feedback loops into scoring
-SLA follow up is tracked and audited
-Recycle logic is intentional, not manual

An MQL should represent:

Fit + Context + Behavior + Timing.

Not just clicks.

If marketing and sales argue about lead quality, the issue is rarely effort.
It is math.

Loose definitions create political tension.

Tight definitions create velocity.

If your MQL to SQL conversion is under pressure, do not blame effort.

Refine the model.

Fractional RevOps & GTM Teams (and Memes) ⚙️🛠️

Many marketing teams do not have a real funnel strategy.

Most teams create content.
Run campaigns.
Drive traffic.
Score engagement.

But there is no intentional progression.

No structured path from:
-Problem unaware
-Problem aware
-Solution exploring
-Vendor comparing
-Ready to buy

If you do not design content and programs tied to specific funnel stages, you are not moving buyers.

You are collecting activity.

Full funnel means:
-Top of funnel content that reframes the problem.
-Mid funnel programs that deepen urgency and qualify fit.
-Bottom funnel assets that reduce risk and accelerate decision.

And those pieces should be sequenced.
Retargeted.
Scored differently.
Measured differently.
Owned differently.

If your blog, webinars, paid ads, nurture streams and SDR outreach are not mapped to buying stage, you are just spraying content into the void.

Then sales sits there saying the leads are cold.

Of course they are.

You never intentionally moved them.

Hope is not a funnel strategy.

Design is.

Sales and marketing arguing about MQLs is one of the biggest red flags in a GTM org.

When I see this happening, I already know the real problem.

It’s not the leads.
It’s the funnel design.

We see this pattern all the time across RevOps work at JayOh - the GTM Engineering Company  :

Marketing says:
“We’re hitting our MQL targets.”

Sales says:
“These leads are garbage.”

Leadership says:
“Why isn’t pipeline growing?”

Here’s the uncomfortable truth:

The MQL itself is usually the problem.

Most companies define MQLs around activity, not buying intent.

So you get things like:

• Someone downloaded a guide → MQL
• Someone attended a webinar → MQL
• Someone clicked 3 emails → MQL

Sales gets the lead…
and the buyer isn’t remotely ready to talk.

Now trust is broken.

Sales stops following up.
Marketing sends more leads.
The argument gets louder.

The teams think they have a lead quality problem.

But it’s really a funnel definition problem.

One of the quiet fixes we push with clients at JayOh - the GTM Engineering Company  

Stop optimizing for MQL volume.

Start defining lifecycle stages around actual buying signals.

Funny thing happens when you do this:

Sales stops complaining about leads.
Marketing stops defending their numbers.
And pipeline actually starts to grow.

The best GTM teams don’t argue about MQLs.

They barely use them.

No alternative text description for this image

If your CRM only works when reps manually update everything…
you didn’t build a system.

You built homework.

This is something I see a lot when talking with CRM admins and RevOps teams.

The system is perfectly structured.
The fields are all there.
The process is documented.

But sales hates using it.

Why?

Because reps aren’t system admins.

They’re sellers.

And the real job of RevOps isn’t to force compliance with the system.

It’s to design the system so sellers barely have to think about it.

Across a lot of the work we see at , the highest-performing GTM systems follow one rule:

Make the right behavior the easiest behavior.

That means things like:

• Automating lifecycle updates
• Auto-logging activities wherever possible
• Minimizing required fields
• Pre-filling data from enrichment or integrations

Every extra field you require is friction.

Every manual update steals time from selling.

The best CRM setups don’t ask reps to maintain the system.

They quietly maintain the system for them.

Because if your sellers spend more time updating CRM than talking to customers…

The system isn’t enabling revenue.

It’s slowing it down.

Good RevOps removes friction.

Great RevOps makes the system feel almost invisible.

Everyone wants to add AI to their GTM tech stack right now.

But almost nobody wants to fix the thing AI actually depends on.

Data.

We see this constantly when talking with teams we work with at JayOh - the GTM Engineering Company .

The conversation usually starts like this:

“Which AI tools should we add?”
“Can AI help sales prospect faster?”
“Can we automate more of our funnel?”

All good questions.

But here’s the reality:

If your CRM data is messy, AI just helps you scale bad decisions faster.

The same problems show up every time:

• Duplicate accounts everywhere
• Incomplete fields across lifecycle stages
• Activities not logged consistently
• Lead sources that no one trusts

Then teams plug AI into the system and expect magic.

But AI doesn’t fix bad data.

It amplifies it.

A lot of GTM leaders are treating AI like a growth lever.

In reality, it’s more like a multiplier.

If your foundation is strong, it makes your team faster and smarter.

If your data is a mess… it just makes the mess happen at scale.

One quiet trend we’re seeing across clients :

The teams getting the most out of AI didn’t start with tools.

They started by fixing their data model and lifecycle structure.

Same lesson RevOps has always known:

Garbage in. Garbage out.

RevOps teams aren’t overwhelmed because they’re bad at their jobs.

They’re overwhelmed because their systems are broken.

Walk into almost any GTM org and you’ll see the same pattern.

The RevOps team is drowning in requests:

“Can you fix this report?”
“Why didn’t this lead route?”
“Salesforce is broken again.”
“Can we change this workflow?”

All day long it’s tickets, pings, and fire drills.

And leadership assumes the problem is capacity.

But when we look at these environments with clients, the real issue usually shows up fast:

RevOps isn’t operating strategically.

They’re operating like the GTM IT helpdesk.

Here’s what typically caused it:

• No clear ownership of GTM systems
• Poor lifecycle and funnel design
• Automations built reactively over time
• Leadership asking for fixes instead of root-cause solutions

So RevOps ends up fixing symptoms all day.

Instead of fixing the system that creates the fires.

One of the biggest shifts we help teams make is simple:

RevOps has to move from ticket taker → system architect.

That means fewer one-off fixes and more time designing how the machine actually works.

Because the truth is:

Most RevOps burnout isn’t caused by workload.

It’s caused by preventable chaos.

Every company says they need “strategic thinkers.”

But when budgets tighten… they fire Dave.

Dave ships.
Dave fixes.
Dave builds.
Dave closes the loop.
Dave figures it out without a 12-slide alignment deck.

Here’s the uncomfortable pattern I see in B2B SaaS:

Headcount grows.
Titles multiply.
Documentation increases.
Alignment meetings expand.

Revenue does not.

There is a difference between:

Strategic clarity
And intellectual theater

Between:
Real operating leverage
And people who just narrate what should happen

Early stage companies win with doers.

Growth stage companies stall when talkers outnumber builders.

Late stage companies drown in governance.

If your org chart has more people reviewing work than producing it, you have a velocity problem.

Operators create cash flow.
Observers create commentary.

When I evaluate a GTM org I ask one simple question:

Who actually moves revenue forward without needing a committee?

Protect those people.

Hire more of them.

And stop firing Dave.

Incognito testing is not paranoia.

It’s respecting the fact that attribution, routing, and scoring are fragile systems.

If your pipeline depends on forms, your forms deserve production-level QA.

Most teams ship them like landing page copy.

Different game.

Test like revenue depends on it.

Because it does.

AI will agree with you all day.
That is the default setting.

It is optimized to be helpful.

Helpful often sounds like agreeable.
Agreeable feels like validation.
Validation feels like intelligence.
Dangerous combo.

If your prompts are vague, your thinking is lazy, or your assumptions are wrong, AI will still nod and say you are absolutely right.

That does not make you a super user.
That makes you amplified.

The difference between average users and killers with AI is control.

Super users:
-Frame the context precisely
-Define constraints
-Ask for opposing views
-Force tradeoff analysis
-Challenge outputs
-Iterate on structure
-Pressure test logic
-Ask what they are missing

They do not ask AI to confirm their opinion.
They use it to stress test their thinking.

If your AI never disagrees with you, that is not a flex.
That is a mirror.
And mirrors do not make you smarter.

They just reflect what you already believe.

The skill is not using AI.
The skill is steering it.

Control the inputs.
Challenge the outputs.
Exploit the iteration loop.

That is where the edge is.

Humans don’t really create from nothing either.

We remix ideas.
We learn patterns.
We build on things we’ve seen before.

That’s how innovation has always worked.

That is what I love about Ai. 

I use it more than anything as a thinking partner that helps me:

• explore ideas faster
• iterate on drafts
• test different approaches
• pressure-test thinking

AI isn’t replacing creativity.

It’s accelerating the iteration process behind creativity.

The people who win with AI aren’t the ones expecting it to do the work for them.

They’re the ones who know how to collaborate with it.

The operators who learn how to use AI become dramatically more productive than everyone else.

That gap shows up fast.

One RevOps leader uses AI to:

• analyze pipeline in minutes
• generate SQL queries
• draft documentation
• troubleshoot workflows faster

Another does everything manually.

Same job title.

Very different output.

AI isn’t the tractor replacing the horses.

It’s the tool that makes the smartest operators even more effective.

The real risk isn’t AI.

It’s someone in your same role learning how to use it better than you.

Most sales teams do not have a forecasting problem.
They have a qualification problem.

When there are no hard rules for what it means to move a deal forward, reps default to one thing:
Push the close date.

No defined entry criteria.
No required discovery fields.
No enforced MEDDICC.
No mandatory next step.
No mutual action plan.
No aging limits.

So what happens?

Deal does not close.
Rep does not want to kill it.
Close date moves 30 days.
Stage stays the same.
Pipeline looks “healthy.”

This is how Stage 2 becomes a retirement home.

If you do not force qualification standards, human nature wins.

Hope feels better than disqualification.
Optimism feels better than starting over.

Strong sales orgs bake discipline into the system:
-Cannot move to next stage without required fields.
-Cannot forecast commit without defined buying process.
-Auto flags deals aging beyond threshold.
-Clear rules for when to close lost.

Qualification should be mechanical, not emotional.

If reps can advance deals based on vibes, they will.

If the CRM enforces standards, behavior changes.

Most teams do not kick the can because they are lazy.
They kick the can because no one defined what “qualified” actually means.

High growth covers a lot of sins.
Until it doesn’t.

When the market is hot, you can outrun:
-A leaky funnel
-High CAC
-Weak qualification
-Forecasting based on vibes
-No attribution discipline
-Random GTM experiments

Revenue growth hides operational fragility.

Then a PE firm shows up.

And suddenly the questions change:
-Why is CAC creeping?
-Why is conversion inconsistent by segment?
-Why does forecast miss every quarter?
-Why are top reps carrying the whole number?
-Why does pipeline not translate to bookings?
-Why does marketing not tie cleanly to revenue?

Growth excuses inefficiency.
Private equity exposes it.

The companies that look good post acquisition are not the ones that grew the fastest.

They are the ones that built:
-Stage discipline
-Clear ownership
-Clean data models
-Real attribution
-Repeatable sales motions
-Forecast accuracy within a tight band

If your growth depends on chaos, you are not scaling.

You are just riding momentum.

Momentum fades.

Systems compound.

“$2.5M in Stage 1.”
Translation: we have hope.

Zero deal stage rules is how pipelines turn into fiction.

I see this constantly:
-No exit criteria.
-No required fields.
-No MEDDICC enforcement.
-No defined qualification standard.
-No aging limits.
-No auto-close logic.
-No probability governance.

But somehow… massive early stage pipeline.

If everything can sit in Stage 1 forever, nothing is real.

Pipeline without rules is just CRM storage.

And here is the part Sales leaders hate hearing:

Inflated early stage pipeline feels good.
It makes the board deck look healthy.
It buys time.

But it destroys forecast accuracy.
It hides rep performance issues.
It masks qualification gaps.
It delays the hard conversations.

Revenue is not created by how much is in Stage 1.

Revenue is created by how cleanly deals move forward.

Strong orgs obsess over:
-Entry criteria
-Exit criteria
-Time in stage
-Disqualification discipline
-Close lost hygiene
-Probability tied to behavior, not vibes

If your Stage 1 is doing all the heavy lifting in your forecast, you do not have pipeline.

You have optimism.

And optimism does not compound.

Process does.

Everyone talks about “intent data” like it’s some secret weapon.
It’s not.

Using third party intent signals is table stakes now.

If you are not tracking category searches, review site spikes, competitor comparisons, pricing page visits, you are behind.

But here is where it actually gets interesting.

The real edge is not detecting buyers who know they want to buy.

The real edge is manufacturing intent before the buyer can name the problem.


It is understanding the company behind the behavior.

Knowing:
-What stage they are in
-How their org is structured
-Whether they are founder led or operator led
-If they are PE backed or bootstrapped
-What their current GTM motion looks like
-Where they are constrained
-What they are optimizing for

That is intent.

If a 15 person founder led SaaS company is consuming content about outbound process, that means something very different than a 200 person PE backed company doing the same.

If a company just raised and starts engaging with infrastructure and reporting content, that signals scale pressure.

If their org chart shows three SDRs and no RevOps, and they are reading about lead routing and attribution, that signals a systems gap.

If they are hiring demand gen but consuming pipeline forecasting content, that signals a misalignment internally.

Intent is contextual.

Downloads alone are noise.

Engagement alone is vanity.

The advantage comes from combining:
-Company stage
-Org makeup
-Strategic posture
-Hiring patterns
-Funding events
-GTM structure

With behavioral data.

That is knowing your customer.

Not just what they clicked.

But where they are.

What they are trying to become.

And what friction they are about to hit next.

That is how you move from reacting to activity to predicting need.

Let me just add one more exclamation point so they know I’m friendly and not yelling!

Acquire and expand customers quicker, cheaper, and for longer | Coaches B2B scale-ups scale more efficiently and effectively through proven frameworks | Organizing the MarTech World Forum London 2024

If your board or investors ask simple revenue questions and three people disappear into Excel, we need to talk.

Your forecast sounds confident on Monday. By Thursday, reality disagrees, and no one can explain why.
You spend more time arguing about stages than coaching deals. 
Deals do not die in your CRM. They just quietly age out while everyone watches.

The heroics that got you here are now the bottleneck. You have 15 dashboards, forecast theatre instead of truth, and a revenue engine leaking cash at invisible handoff points.

You are not bad at this. The system is.

I help €20 to 100M B2B SaaS scale-ups turn scattered data and forecast theatre into a revenue engine you can actually steer. Within 90 days. Without a reorg, new tools, or hiring a full-time VP RevOps.

Your RevOps team owns the system when I leave. I bring the pattern. They keep it running.

We start with a fast 4-part maturity scan to find the real constraint. Then we install three structures:
→ One-page strategy linking goals to the programs that actually move pipeline, win rates, and NRR.
→ One Revenue Room where metrics, risks, and decisions live in one view. No more "marketing numbers" vs "sales numbers." Just the number.
→ One operating cadence that replaces updates with decisions. If we are not making decisions, we are just having expensive coffee.

When it works, you explain where pipeline is healthy, where it is leaking, and how you are fixing it in 10 minutes flat. You get the headspace to think 3 years ahead, not 3 hours behind.

I am Rutger Katz, Fractional VP of RevOps.
Most RevOps people grew up in the growth bubble. They know how to spend money. I spent 15 years architecting efficient growth, so I know how to stop wasting money.

At one tech company, I uncovered €1M in unseen upsell opportunities. 
At Relay42, I rebuilt onboarding and adoption to move NRR.

Stop drifting. Start steering.
Revenue Engine Checkup in Featured. 10 minutes.
Or DM me "CHECKUP" for the questions directly.

I also speak/podcast guest on strategic RevOps, neurodivergence in leadership, and scaling to 100M ARR. 
Check www.neontriforce.com/speaking for more

Rutger Katz

I hate lead magnets. I'm also terrible at sharing files.
 
I've spent a year collecting RevOps resources, talking to ChatGPT/Claude, and formulating proven frameworks I applied the last 15 years. I extracted that in a set of Claude skills specifically for RevOps and GTM work. 

Not generic prompts. 

Skills with real methodology baked in: SPICED qualification, forecasting frameworks, HubSpot implementation patterns, change management, crisis triage, GTM comp design.
 
25 skills. 8,333 lines. Free.
 
But the more interesting thing is how they work.
 
Most people use Claude with structured prompts. "Act as a senior RevOps leader. Here is the context. Here is what I need. Format it like this." Every single time.
 
Skills are different. You upload the file to a Claude Project once. Claude reads it as background knowledge. From that point, every conversation in that project runs on the skill automatically. Claude knows which frameworks to use, which questions to ask, what to watch out for.
 
You stop prompting. You just ask questions or give assignments.
 
↳ "Why is our forecast always wrong?" 
↳ "Help me build a change management plan for this CRM migration." 
↳ "Our pipeline coverage looks fine but we keep missing. Where's the leak?"
 
Claude responds like a specialist, not a generalist.
 
Six skills stayed private. Those have client diagnostic and proposal methodology in them that people pay for.
 
The other 25 are yours.
Free (for now).
 
Comment or DM IHateLeadMagnets 
(or something else so that I can see you want it).
Put your hand up in whatever way you like, I'll send you the ZIP.

AI-native revenue engines for €15–150M B2B SaaS | Fractional VP of RevOps | Replacing spreadsheets and gut feel with compounding systems in 90 days | Double Daughter Dad

A simple new direction turns into seven things RevOps now has to rebuild.
 
Sandy Robinson, M.Ed. put words to it in Pavilion's RevOps School this week. I've seen it across enough clients to know it's not an exception. It's the pattern.
 
Leadership makes a call. New segment. Going upmarket. ICP shift. Motion change from inbound to ABM. 

It sounds like one decision. A direction. A slide in a deck.
 
By the time it reaches RevOps, it's something else entirely.
 
↳ ICP changes. Every targeting criteria, every account list, every scoring model needs rethinking. 
↳ Process changes. Qualification methods built for the old motion don't fit the new one. Handoffs break. Playbooks are wrong. 
↳ Tooling changes. Sequences, automations, configurations. Nothing carries over cleanly. All of it needs rebuilding. 
↳ Data definitions change. What does qualified mean now? What's a good fit? What does the funnel even look like?
 
Nedap is a good example of the opposite. They understand the size of what they're taking on. They want to map it properly before they start moving. That's not caution. That's how you avoid getting buried.

They scoped change across technology, data, process, upskilling, kpis and more. A big program, but it will stick.
 
The younger scale-ups I've worked with often hit this mid-execution. Three months in, RevOps is buried. Not because they're slow. Because nobody showed them what was coming.
 
The fix isn't complicated. Bring RevOps into the strategic conversation before the announcement. Not after. Not to slow it down. To map the avalanche while there's still time to prepare.
 
One decision at the top. Everything moves underneath. They should probably know it's coming.

I stopped writing long AI prompts. Built skills instead. The output quality jumped.

Next week I'm releasing a free GTM skill set for Claude. The skill carries the structure, the frameworks, the context. You describe what you need. It already knows how to think about it.

The RevOps set I built:
↳ RevOps Strategy
↳ RevOps Diagnostic
↳ RevOps Crisis
↳ RevOps Change Management
↳ RevOps Data Governance
↳ RevOps Forecasting
↳ RevOps Four-Capability Maturity Assessment
↳ RevOps HubSpot
↳ RevOps Metrics
↳ RevOps Tech Stack
↳ Revenue Operating Cadence
↳ CS Operations

Plus curated sales and marketing skills — GTM planning, compensation, sales methodology, marketing operations — so you have the full picture, not just one function.

No prompt engineering. The expertise is baked in.

There aren't any freely available RevOps skill sets out there right now. Feels like the right moment to change that.


Other things compounding quietly this week:

↳ 22 push-ups this yesterday. Was grinding through 10 a week ago. 1% improvements are invisible until they aren't.

↳ 60 sign-ups for the next Scale Up with HubSpot event. We were bracing to scrape to 50. Keep making the thing better, the numbers follow. Same principle, different context.

↳ EU roadshow conversations starting. Small, intimate events by design. Quality exchange only happens in a room where everyone knows everyone's name. The Dutch say massa is kassa. We respectfully disagree.

↳ If you're a sponsor whose ears just twitched, my DMs are open.


Drop a comment below if you want a heads-up when the skills drop next week. I'll come find you.

Governance is the most boring word in RevOps.
 
It is also the one thing that separates strategic partners from ticket-takers.
 
Everyone wants RevOps to be strategic. Few companies give RevOps the governance, decision rights, and process ownership that make strategic work possible.
 
I sat down with Jeff Ignacio on The RevOps Review Podcast to talk about what that shift actually looks like in practice.
 
We covered:
 
↳ What I think Winning by Design gets right about how revenue should work 
↳ Why governance and clear decision-making matter more as you scale 
↳ The real blockers when RevOps tries to move from tactical to strategic 
↳ Why customer adoption is a revenue conversation, not just a CS conversation 
↳ My Revenue Ops Maturity Model and where most scale-ups honestly sit on it
 
21 minutes. And we managed to talk about revenue operations without mentioning AI once.
 
Funny how much there is to sort out before the robots take over.
 
Link in comments.

Two companies deployed AI in their GTM. Same tools. 
One grew revenue per seller by 61%. 
The other lost 26%.

The difference wasn't the technology.

The 2026 Fullcast × Pavilion benchmark just made this painfully clear across 361,000 opportunities and 316 companies.

Group one focused on leverage. They closed fewer deals, moved upmarket, and used AI to sharpen qualification, routing, and deal prioritisation. 
R͟e͟s͟u͟l͟t͟: revenue per seller up 61%. Average deal size up 44%.

Group two focused on volume. They hired 38% more reps, flooded the top of funnel, and used AI to scale outreach and activity. 
R͟e͟s͟u͟l͟t͟: pipeline grew 72%. But revenue per seller dropped 26%. And deal sizes shrank.

Both groups adopted AI. Only one built the operating system to make it work.

And by operating system I don't mean software. I mean the decisions baked into how you run revenue: who you target, how deals qualify, what triggers action, and what gets ignored.

This is the pattern I keep seeing at scale-ups between €15M and €150M. The instinct when growth slows is to add volume: more reps, more pipe, more tools. The data (and my experience) says the opposite works: fewer, better-qualified deals with rules that enforce quality at every stage.
AI is an accelerant. It doesn't care what it accelerates.

→ Precise ICP, enforced stage gates, signal-based routing? AI compounds that.
→ Fuzzy targeting, no governance, activity-based KPIs? AI compounds that too. Faster.

Before you buy the next tool, ask one uncomfortable question:

Are the decisions underneath it worth accelerating?

📊 Data: Fullcast × Pavilion 2026 GTM Benchmark Report
h/t Guy Rubin

The worst feeling in SaaS:
 
Huge pipeline. Missed target. Again.
 
Here's the pattern I see with every founder past €5M ARR:
 
They're targeting €5M this quarter. 
They've got €20M in pipeline. 
They're converting 20%.
 
That's €4M. They miss.
 
So what's the reflex?
 
"We need more pipeline."
 
I've watched founders double down on this for 6 months straight. 
More outbound. More content. More events. 
The CRM looks like a crime scene. 
The sales team is drowning in demos they'll never close.
 
And conversion stays flat at 20%.
 
Because if your conversion is broken, more pipeline just means you're burning CAC faster on deals you'll never win.
 
It's like hiring more waiters when the kitchen's on fire. Everyone's very busy. Nothing's getting served.
 
𝗛𝗲𝗿𝗲'𝘀 𝘄𝗵𝗮𝘁 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘄𝗼𝗿𝗸𝘀:
 
𝗙𝗶𝗿𝘀𝘁, 𝗱𝗲𝗳𝗹𝗮𝘁𝗲 𝘁𝗵𝗲 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲.
 
That €20M is contaminated. Zombie deals. Wrong-fit ICPs. Opportunities your reps keep "nurturing" because killing feels like losing.
 
Cut it to €15M. Same target. Less noise.
 
Now you're converting 27% instead of 20%. Same €4M. Way less waste.
 
𝗧𝗵𝗲𝗻 𝗽𝘂𝘀𝗵 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 𝗮𝗻𝗼𝘁𝗵𝗲𝗿 𝟲 𝗽𝗼𝗶𝗻𝘁𝘀.
 
Fix the handoffs. Sharpen the enablement. Give people clear next actions instead of dashboards they never open.
 
33% of €15M = €5M.
 
Target hit. Zero extra pipeline required.
 
𝗧𝗵𝗶𝘀 𝗶𝘀 𝘄𝗵𝗮𝘁 𝗥𝗲𝘃𝗢𝗽𝘀 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗱𝗼𝗲𝘀. 
Not dashboards. Not Salesforce janitor work.
 
It turns pipeline chaos into a system that compounds.
 
Most founders skip it. They hire GTM Engineers and Clay gurus instead. Then wonder why two quarters later they're still missing the target with twice the CAC.
 
Same pattern every time:
 
They think it's a pipeline problem. It's a conversion problem. 
They think it's a people problem. It's a system problem.
 
If you're past €5M ARR and this feels familiar, there's a 10-minute diagnostic in my featured section Rutger Katz.
 
It shows you where your revenue is actually leaking and what not to touch yet.
 
If it's worth going deeper, we book 45 minutes and make it practical.

Move pipeline is not the answer, RevOps is

Most revenue architecture rollouts plateau at the same point.
 
Teams are enthusiastic. Bowtie gets mapped. SPICED gets trained. Early wins show up.
 
Then it stalls. Quietly.
 
It's almost never the framework.
 
What's missing sits underneath it. Two layers and one rare resource that most companies leave completely unprotected.
 
↳ Swipe through for the full breakdown.
 
The short version: Governance protects the investment. Enablement makes the new way of working stick. Champions carry both.
 
I've seen what happens when you lose them. Eight people driving a platform rollout at a bank. Strategy shifted. All eight scattered overnight. Two years of work, gone in a week.
 
If you're rolling out revenue architecture or any operating model across multiple teams, one question before you start:
 
What system protects this when priorities shift?
 
If you can't answer that, you're hoping it lands. And hope doesn't scale.

Change fails without governance and enablement

Suffering from success. I hate lead magnets. Made one anyway. Then spent an evening emailing .zip files to strangers.
 
Last week I posted "25 Claude Skills for RevOps & GTM." Built them because they didn't exist and I wanted them for client work. Posted them because other people probably need them too.
 
About 50 people responded.
 
LinkedIn doesn't allow .zip files in DMs. So I did the only logical thing: emailed them individually.
 
This morning, I built a resource page on Lovable. Took 30 minutes. Drop your email, get the files. I can add every free resource I build going forward.
 
One follow-up email goes out a week later: "Did any of it stick?"
 
Not to sell. To learn. The skills only get better if I know what's broken.
 
I build revenue systems for companies stuck doing things manually. Apparently, I needed a LinkedIn limitation to apply that to myself.
 
Link in first comment (which LinkedIn probably buries).

I was a terrible corporate employee.
 
Held back in school, not because I couldn't do it, but because it bored me. Tried five different study programmes before finishing. Six companies in 12 years (low for most salespeople). Failed spectacularly at project management. Frustrated every manager I worked for.
 
My brain has one setting: obsessed or checked out.
 
ADD means I can't tolerate noise. Broken processes, meetings without purpose, misaligned KPIs... My brain physically rejects them. In corporate that made me "difficult." In consulting, it became a diagnostic instrument.
 
Every role taught me what a broken system looks like from the inside:
 
→ At a marketing consultancy, five disciplines refused to collaborate because each had separate KPIs 
→ At a logistics company, three leadership changes produced zero improvement because the company's operating system never changed 
→ At a 100-person consultancy, I watched brilliant frameworks die because nobody installed the cadence to make them stick
 
I didn't collect these experiences on purpose. But now I walk into a company and within two weeks the patterns are screaming. Not because I'm brilliant (but it does help 😉).
 
Because I've been inside six versions of the same broken system.
 
What looked like a messy career was actually pattern recognition in training.
 
If you've ever felt like the wrong fit for the system, maybe the system was wrong, not you.

P.S. Guys, it's Women's Day, so grab a bouquet of flowers for your wife and shower her with love

Three people will describe your sales process. None of them are right.
 
The CEO describes the one they designed two years ago. 
The VP describes the one they trained on last quarter. 
The rep describes the one they follow when their manager is watching.
 
Ask what actually happens when push comes to shove: last week of the quarter, big deal on the line, pipeline review in two hours, and you get a fourth answer. From nobody, because nobody has looked.
 
I spend my first week sitting on sales calls. Not to understand the product. To see what reps actually do when it matters.
 
Then I open HubSpot.
 
Deals stuck in the same stage for 60 days. Missing qualification fields. Stages that do not reflect the conversation that actually happened. You can see the gap between what the process says and what people do. Right there in the deal records.
 
That gap is where revenue leaks. Not in the strategy deck. Not in the methodology training. In the space between what leadership thinks is happening and what reps actually do under pressure.
 
The first 90 days are not about building something new.
 
They are about making visible what is already there, standardising what works, and removing what does not.
 
Most companies try to fix what they think is broken. The ones that improve fix what is actually broken. That requires seeing it first.

Your pipeline just shrank. Congratulations. That is progress.
 
First thing I do in any engagement: kill deals. Zombie opportunities that have not moved in three months. Prospects who went dark after the demo. Deals sitting in late stage because nobody wanted to close them out and watch the coverage number drop.
 
Strip those out and the pipeline is €3M lighter.
 
The CRO panics. 


Understandable.
 
But here is what actually changed. The forecast is now honest. The conversion rate now reflects reality. The team stops spending cycles on deals that were never going to close and starts focusing on the ones that might.
 
Nobody asks about the ROI of that.
 
They ask about the ROI of the system, the process, the engagement. Fair question. But the ROI is not always a bigger number. Sometimes it is a smaller number you can actually trust.
 
Zombie deals made your pipeline look healthy right up until you missed. They made your conversion rate meaningless, your forecast unreliable, and your team's effort invisible, because effort spread across dead deals looks like activity without results.
 
Killing them does not cost you revenue. It just removes the illusion of it.
 
It gets worse though...


 
Strip out the zombies and you might discover your pipeline is not just dishonest. It is too small.
 
You were not over-covered. You were under-covered and did not know it because the dead deals were filling the gap.
 
Now you have a different problem to solve. A real one.
 
That is still progress. You cannot fix what you cannot see.

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The Battle

Joe LaGrutta, MBA

Rutger Katz

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