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.

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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.

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.

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.

My brain generates AI automation ideas faster than I can build them. This is not a humble brag. It's a problem.

The AI-native operator's curse: you see leverage everywhere.

That client intake process? Automatable. That weekly reporting workflow? 90% of it can be done by AI. That discovery call prep? Already have a system for it.

The bottleneck isn't ideas anymore. It's sequencing.

Deciding which automation to build first — based on which one moves the most revenue, saves the most time, or removes the biggest bottleneck.

Saying no to a good idea isn't easy. But it's the only way the best ideas actually get built.

#AIAutomation #OperatorMindset #Productivity #ClaudeCode #GTMOps

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.

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.

It's all too common to see teams drowning in data prep (and hating it).

The inefficiency of data cleanup doesn't just waste time; it hinders decision-making, delays insights, and lowers team morale.

So, what's the solution?

The answer lies at the source.

📈 Automate Data Collection: Use tools that automatically capture and organize data from various sources. This reduces manual entry and ensures consistency.

📏 Make Data Governance Easy: Establish clear rules and guidelines for data entry. This includes validation rules and required fields to ensure data accuracy from the start.

🗂️ Standardize Data Formats: Implement standardized formats and naming conventions across your data sources. This makes it easier to clean and integrate data without constant reformatting.

🔍 Regular Data Audits: Conduct periodic audits of your data to identify and rectify inconsistencies. This proactive approach helps maintain data integrity over time.


Then to take it to the next level, focus on transforming your data and ensuring those transfromations are the single source of truth.

🏢 Centralize Data Storage: Store all data in a centralized location accessible to all relevant teams (ideally a Data Warehouse). This eliminates the need for multiple versions of the same data and reduces errors.

🔄 Leverage ETL (or Reverse ETL) Tools: Use ETL tools to automate the process of cleaning and preparing data for analysis & push it from this source to your point solutions. This makes the data prep process faster and more efficient while ensuring everyone operates off of the same information.

Benefits? 

You get to: Spend more time on insights, not prep

Most people check email like it’s a to-do list.

That’s the mistake.

One productivity rule I picked up from The CEO Within changed how I handle inbox chaos:

Touch it once.

When you open an email, make a decision immediately:

• Reply
• Delegate
• Schedule it
• Archive it

What you don’t do is reread it five times throughout the day.

That’s where the time drain happens.

I see this a lot with operators and leaders we work with.

They’re not actually overloaded.

They’re just reprocessing the same inputs all day: email, Slack, requests, reports.

Every time you reopen something, you pay the context-switch cost again.

Simple rule:

If you open it, move it forward.

Your inbox shouldn’t be storage.

It should be a decision engine.

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

proptext

Delivering context for the intelligent real estate investor, one newsletter at a time.

Partner

Auditive

GTM for a first of its kind compliance marketplace for b2b.

Sales Strategy & Operations

propvest

Helping professionals accelerate their wealth through real estate investing.

Founder

Mynd

Newly formed role on the Growth team focused on streamlining revenue operations and scaling ancillary business products for our web-based investor marketplace.  My main mission was to drive customer lifetime value by establishing adjacent net new product offerings and removing operational bottlenecks for our retail investment sales channel. 

Highlights:

• Led strategy and execution of four new business functions (mortgage, retail investor acquisitions, insurance, and selling) driving customer lifetime value up to 362% 

• Achieved 300% increase in signed listing agreements within six months

• Launched three-member retail acquisitions team sourcing investment properties across 28 markets in 11 states; improved offer acceptance rate from 6% (Q4 21) to 45% (Q1 22) 

• Relaunched mortgage brokerage subsidiary (Mynd Mortgage) from compliance & state licensing to closed loans.  Hired critical talent, led product messaging and tech stack improvements.  Grew mortgage revenue 40% quarterly in CY22.

Head of Investor Offerings

Post acquisition role focused on managing the retail investment channel sales plan while migrating and/or adopting the naming conventions/processes/systems for sales operations.  We became hyper efficient while pivoting our focus from transactional revenue to ARR.  

Highlights:

• Led team of AE’s/SDR’s achieving up to 140% plan (2.5x growth '21) for retail investment channel, all while supporting executive leadership with strategic marketplace planning

• Defined and led highly successful cross-selling campaigns resulting in $1.2M additional annual recurring revenue (ARR)

• Led RevOps tech stack migration post acquisition including reports, dashboards, APEX integrations, flows, triggers, and tools including Salesforce CRM, Revenue.io, Tableau, etc.

• Performed ad hoc analysis including customer segmentation, sales participation, propensity to buy,  and white space improving forecasting accuracy by 18%

• Collaborated with Product, Engineering, and Data Science teams to develop business requirements, prioritize projects, and offer feedback as the principal product liaison for investor marketplace initiatives.

Director of Sales (Investor Services)

HomeUnion

Led teams, wore multiple hats, navigated the ups and downs of a growth stage startup from series B to acquisition.  My primary responsibilities included leading the GTM sales motion and sales operations from tech stack to forecasting/planning with teams in the US and LatAm.

Highlights:

• Critical contributor from Series B to successful acquisition of HomeUnion to Mynd. One of a select few from the team retained to lead the business forward for Mynd

• Attained multiple promotions while serving as a go-to strategic guide for revenue growth, driving 7 consecutive quarters of exceeding targets of $30M+

• Led sales operations as Salesforce CRM administrator leveraging proprietary system integrations, streamlining the sales process, and reducing manual steps by 60%, directly contributing to a 33% reduction in the overall sales cycle 

• Developed ongoing reports, dashboards, KPIs, and data visualizations aligned with sales plan while adjusting territory planning  and sales compensation as needed

• Championed a best-in-class sales funnel that enhanced lead targeting while reducing spend. Increased sales qualified to closed won by ~85% 

• Integrated Private Client function (HNW Customer Success) and achieved a 200% boost to repeat business YoY, ranking at the top of all director-level staff

Director of Sales

Helped individual investors build passive income streams by providing consultative advice for acquiring the best buy and hold residential real estate across the country.  Met some amazing leaders of industry and still consider many personal friends. 

Highlights:

• Presidents Club (’16), averaging 160% to quota. Coached and mentored team of up 24 AEs on solution-selling principles specific to real estate investing

• Attained the highest average revenue per sale (83% above office) influencing a company-wide product strategy shift

Account Executive

Wells Fargo Advisors

Private Client Group not tied to the bank/banking activities.

Highlights:

• Completed training program passing both the Series 7 and Series 66 securities licensing exams while defining GTM strategy

• Leveraged high volume outbound prospecting finishing in the top 20% of 60-person class in new accounts, revenue, and AUM

Financial Advisor

Accomplished growth stage startup leader with 10+ years of progressive success leading revenue teams to >$500M sales.  Expertise in streamlining revenue operations with an emphasis on revenue efficiency.  Skilled at fostering cross-functional collaboration across multiple projects, effectively engaging both technical and non-technical staff alike.

Subject matter expertise in real estate technology and services businesses with a growing focus in B2B SaaS technology businesses. 

Building prop.text, the newsletter delivering invaluable context for the intelligent real estate investor, straight to your inbox. 

Highlights

→ $500M+ in sales 
→ 3x sales leader managing multiple teams/functions
→ 2x revenue operations leader, certified on Salesforce and Hubspot 
→ $100M+ lessons learned scaling venture-backed proptech companies

Real Estate Specific

→ Sold 2k+ investment properties across 27 markets, 14 states
→ 10yr+ enabling successful local and remote investing
→ 3x real estate marketplace builder
→ 1x wholesale mortgage brokerage builder 
→ 1x design/build construction company builder
→ Real estate investor with personal experience in buy/hold & flip throughout the Northeast

Always open to connect with like-minded professionals.

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The Battle

Joe LaGrutta, MBA

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