B2B Catalyst

7 years of B2B consulting experience lead to B2B Catalyst. We build revenue engines that work.

CEO/Founder

SB Builders, LLC

Changed invoicing process to dramatically reduce AR and contributed in doubling revenue, passing 80k in monthly revenue

Implemented time tracking, invoicing, project management, basic CRM, contract creation, esigning system.

Developed SOP for all of the above & trained team in SOP.

Weekly checkins on project progress and invoices

Marketing and Operations

AutoVitals

-Analyzed current sales strategy, proposed changes, and implemented
-Developed and implemented channel strategies
-Managed and trained sales development team
-Developed hiring and training process
-Hired 5+ New SDRs
-Refined sales process
-Reimplemented CRM
-Managed CRM, users, and ensured CRM data quality
-Developed initiative tracking methodology to track result of sales and marketing initiatives
-Tracked sales and marketing KPIs & developed tracking tools for team use
-Set sales development team goals
-Refined team management process

Sales Strategist

Sales Development Representative

This Side Up Global

I helped develop and improve core operating processes and procedures in This Side Up Global using Scrum, JIRA, Confluence, Lastpass, and other industry standard processes and software.

I led and/or documented meetings in the company, including Sprint Planning & Review meetings, Process Retrospectives, Daily Stand-up's, and Client Meetings. I partnered with the CEO and other team members to improve operations, processes, and other business elements.

I administrated company SaaS products, adding, removing, and editing users, accounts, and other entries. I researched new software products, tested them, and if beneficial implemented them in the company. I explored existing software and found ways to use them more efficiently.

I developed, refined, and recorded company processes and procedures. I researched cutting edge business processes and concepts and worked with the CEO to implement them in the company.

I received training in content marketing, email marketing, and exposure to Facebook Ads, Google Ads, SEO, Social Marketing, and other kinds of digital marketing.

I initiated a content marketing campaign on a Facebook group, the first article of which got 25 likes, 11 comments, 1 share, and over 100 people added to a pixel.

Process Specialist

Founder | B2B GTM | Scale without headcount by mapping your playbooks into an AI revenue engine

Be honest - how many Linkedin posts have you seen this year saying that XYZ tech/playbook/widget is absolutely essential to your GTM this year?

Probably a lot

We now have thousands of sales and marketing technologies on the market

And all of them are pitching their solution as best in class

With playbooks, agencies, influencers to sell them

And yes, we have preferred tech vendors

Here's the difference

We don't throw you in canned playbook, we actually look at your Go to Market model before making recommendations

Let me tell you a funny story

I talked with an SDR team that was booking 80 meetings a month with parallel dialers and 10k emails per SDR per month

But 60% of their meetings got disqualified

Why?

They didn't qualify target accounts before doing outreach

Tech and playbooks don't save you deploy the wrong one at the wrong time

So what do we do different?

When you work with us, we start with an assessment

We look at your funnel metrics, your best customers, your messaging/copy, and get input from your team on detailed attributes that make up a great customer

That you CAN'T find in an off the shelf tool

After that we use our knowledge of best practices and tooling to identify the biggest opportunities to unlock more revenue per headcount in your team

This could look like

> Customer analysis
> Serviceable Addressable Market Mapping (because TAM is where you lose deals not win them)
> Target Account Lists
> Automated Contact Prospecting & Enrichment
> Pipeline Validation (we build out a script, test it to book meetings for you, help you take the meetings through completed discovery with next steps, then give you a completed call framework, email sequence, and discovery framework)
> Outbound Sales Team Coaching (Phone first)
> Sales Process Optimization
> Managed Cold Emails & Cold Calling
> Inbound Lead Flow Optimization
> AI Business Case Building (which we used to open a $300k+ opp at UPS)
> Implementation of Nooks, Clay, Evergrowth, and other sales tooling

Yes, we do that under one roof

Yes, it was very hard to find a team good enough to do all of this in one place

If you want to learn more, book a time here: https://calendly.com/b2bcatalyst/your-gtm-system-audit-linkedin
> Cold Email Infrastructure

Scott Martinis

So 6sense released a surprisingly great article embracing the move from intent to signals - but they missed one critical category of signal with serious consequences

Ironically, this effectively admits that their intent data didn’t actually show purchase intent... 

Buuut I won’t knock them for telling the truth even if it's late

Why this missing category matters:

Missing it...

Kills marketing / sales alignment

Makes actual intent modeling extremely hard to scale

Removes the most reliable and scalable form of signals

And is ultimately the reason why I think intent platforms failed in the first place

6sense talks about 2 paths to get signals

“Created/Received Signals come from your own digital properties and systems. Web traffic, product usage, email engagement, CRM data, and more.”

I call these first party signals because you own the data

“Acquired Signals come from outside providers. They give you visibility into activity you wouldn’t otherwise see: content syndication, review sites, publisher networks, etc.”

I call these second party signals because you can’t independently verify the data

The most important category?

Third party signals

Public signals you acquire through structured research

Job posts, news articles, new hires, social content engagement

This category is mostly driven by growth/demand teams reinventing ABM with Clay workflows

5 reasons it’s the best category

1. Anyone can verify the signals

Sales reps trust signals they can see with their own eyeballs more

2. It tends to predict behaviour better

Public content engagement shows greater commitment

News articles either force or show company action

Job posts and hiring demonstrate a willingness to spend money on a problem

3. You can personalize off public signals without being creepy

In fact, you look thoughtful when you do

4. Lack of data isn’t a problem, it’s a signal

No hire = smaller problem

5. It’s already an account-based sales best practice

Adem Manderovic was researching job posts in 2010 to identify in market companies

Christopher Curtis was helping SDR teams overattain when the rest of their company missed… 2-3 years ago

Jacob Karp uses third party signals to build account POVs that guide all of his outbound

Put simply - 3rd party signals make sales and marketing ABM alignment possible by aligning the team around visible signals you can easily act on

If I were 6sense (or Clay) I would find a way to structure 3rd party signal data to combine with 1st and 2nd party data for profile/readiness/interest signals (another great section of the article)

Build modeling against won/loss data

While also figuring out how to surface the data in a way sellers can action in prospecting and discovery calls

Get that right… you finally live up to the promise of being a GTM crystal ball

Founder | GTM Architect | We build revenue engines that work

SparkGrid Software

Advisor

Eustace Consulting

Pragmmatic

ReachSuite.io

LeadGenius

LeadGenius curates bespoke data at scale so you can win new verticals, expand global territories and slice'n dice accounts & contacts with custom insights you can't find anywhere else.

VP of Sales, Strategy & Account Management

VP of Sales

Director of Global Enterprise Sales

Senior Enterprise Account Executive

Pavilion

Executive Member

Northeastern University

Thrilled to be a guest lecturer on sales, business development and entrepreneurship.

Guest Lecturer

Z-MACHINE

Launching niche digital and e-commerce products including: 

Raceteacher.com
Offmarketformula.com
Newenglandwalkers.com
Donr.io

Creator | Digital Products

Creating sales, marketing and product "wow"​ moments welcoming new customers and nurturing them into loyalists.

Independent Consultant

Cylindo

In a world where customers now demand immersive experiences and "wow" moments,  cutting edge furniture retailers & manufacturers use Cylindo to power photo-real, 360-degree product imagery that drives sales.

Enterprise Account Executive

Causemo

Causemo is disrupting digital fundraising with digital journeys designed to engage, acquire and keep new and existing supporters.

Precision Pipeline at scale? That's Genius.

Customer-centric solution creator obsessed with execution, speed and data-backed decisions. Prefers big ideas over safe ones, speaking up over saying nothing, running over walking. 

Let’s talk about #lucianopavarotti #patton #b2bsales #b2bmarketing #b2bdata

Zeb Couch 🤜🤛

"Maybe I'm not cut out for this."

That's what I thought sitting at my desk after losing our biggest customer.

I'd just had to fire people. Good people with families. The PE deal we'd been working on for 10 months collapsed. My wife was pregnant. 

Here's the most painful part... I was the one who made the mistake that cost us $3M in ARR.

Here's the thing nobody really talks about...

If you didn't come up the traditional way (BDR → AE → VP → CRO), you always wonder if you're good enough.

Worse yet, in the ultra competitive arena of tech sales, there are some who DO have that pedigree and enjoy making you feel like the "other." 

I never held a BDR role. I skipped it by "reframing" my resume. 

And in moments like that, you think...maybe if I'd done it the "right way," I wouldn't have screwed this up.

The imposter syndrome hits different when you're responsible for other people's livelihoods.

It's not "do I belong here?" It's "did I just ruin someone's life because I wasn't qualified?"

I questioned everything: 
→ Should I have been more careful? 
→ Should I have seen this coming? 
→ Am I actually good at this role or did I just get lucky?

What Changed:

My CEO didn't fire me. 

The board didn't fire me. 

Instead, they asked: "What's the plan to fix this?"

Not "how did you fail?" But "what's next?"

The Lesson:

Imposter syndrome never fully goes away. 

The people who succeed aren't the ones without doubt...they're the ones who move forward despite it.

If you're questioning whether you're good enough right now—that's normal. 

The question is...are you going to let it stop you, or use it to get better?

Zeb Couch

Your ABM 2.0 Platform Deserves Paid Media 2.0 | Building AdGenius to Do It | CRO @ LeadGenius

How does a guy who made money from sketchy dating apps end up as CRO launching a platform to change how people run paid media on LinkedIn, Google & Meta?

A lot of luck. Some hustle. Blissful ignorance.

2013: I'm in my mid-20s running mobile ad arbitrage. I connect third-tier publishers (like MocoSpace) with mobile app advertisers.

The apps? Dating apps. "Russia Date." "China Date." Super sketchy. 

But they paid $15-20 per install. And MocoSpace had millions of users. So I'm making rev-share deals, cold-calling advertisers, learning how platform economics actually work.

Then the advertisers stopped paying. Turns out none of those installs converted to "payers." Shocking, I know.

2014: I need a real job. But I don't have "proper" BDR experience. So I reframe my resume with help from a friend at ZoomInfo. 

Suddenly my ad arbitrage work "looks like" BDR work.

I get hired as an AE. Skip the BDR role entirely.

2018: Mark (now my CEO) calls me out of the blue. He's rebuilding a data company called LeadGenius. Wants me to join as an AE.

2020: I'm VP of Sales. We grow from $6M to $10M ARR.

2023: We lose $5M from two major churns. I almost lose my job.

2024: We rebuild to 30% EBITDA margins.

2025: I'm launching AdGenius to help marketers stop overpaying platforms.

THE POINT: 

You don't need the "right" background. You need to be willing to figure it out as you go.

Those sketchy dating apps taught me how ad platforms optimize for their own revenue. 

That knowledge is now the foundation of what we're building.

Your unconventional path isn't a weakness... 

It's your unfair advantage.

Your LinkedIn CPC quietly doubled since 2022 and you think it's just "market conditions."

It's not.

Here's what the platforms aren't telling you:

1. You're bidding against yourself.

→ Multiple ad groups targeting "Marketing Director," "VP Marketing," "CMO" 
→ These audiences overlap 
→ Your campaigns compete against EACH OTHER in the same auction 
→ You pay 2-3x for the same impression

2. You're paying for bad-fit contacts.

Campaign Manager uses the same filtering as Sales Navigator.  SalesNav filtering is notoriously broken. Gotten better, but still broken. Ask any seller.

Try this: Check your Campaign Manager audiences in SalesNav. You'll see people who have nothing to do with your ICP mixed in. If you don't have access, look at my screenshot.

Example: Filter for "Marketing" titles. LinkedIn includes "Insights" roles (apparently that's marketing?). 

Sure, you can try to exclude them. But within Campaign Manager, how are you supposed to know "Insights" people are considered "Marketing?" You can't exclude what you don't know to exclude.

Oh, and Campaign Manager disclaims they can't always "honor" exclusions. Sorry!

Sellers have complained about the filtering for years. Marketers have no idea.

You're forced into overlap.

Tighten targeting to avoid bad fits? LinkedIn says your audience is "too narrow."

Broaden to fix it? You create overlap with other campaigns.

Back to problem #1.

WHY THIS HAPPENS: 

Platforms aren't incentivized to fix it. More self-competition + more bad-fit contacts + more overlap = more money for them.

It's not just LinkedIn. It's ALL your digital advertising channels. 

I learned this running ad arbitrage. Platforms optimize for THEIR revenue, not yours.

WHAT YOU CAN DO: 

→ Check Campaign Manager filters in SalesNav (if you're a lucky marketer who has access) 
→ Audit campaigns for audience overlap 
→ Use tools that fix targeting data before it reaches platforms (cough cough, AdGenius)

The game is rigged. But once you know the rules, you can play smarter.

Stop blaming "market conditions." That's what the platforms want you to do. 

Start asking:

Am I bidding against myself? 
Am I paying for bad-fit contacts? 
Am I being forced into overlap?

There's a huge wave of AE's leaving ABM platform vendors. AI isn't replacing them, the whole category is dying....

Here are 3 reasons the "all-in-one" ABM platform model is 86’d and what's replacing it: 

1) It's the era of "The Great Unbundling."  

ABM platforms promised to do everything: advertising, orchestration, intent, personalization, analytics. But "everything platforms" optimize for their own expansion revenue, not your results. The market is moving toward best-of-breed point solutions that do one thing exceptionally well.

2) ROI scrutiny is real now, not just a buzzword

78% of CMOs say proving ROI is more important than ever. Yet ABM platforms report "engagement minutes" and "intent scores"...not pipeline and closed deals. C-Suiters are asking: "If we're spending $150K-$300K/year, where's the *EXPLETIVE* revenue and why are these 'results' so *EXPLETIVE* suspect?"

3) Buyers want performance, not platforms

The market doesn't want another $200K orchestration platform. It wants solutions that directly lower CPAs (lower CPAs = lower Cost Per Opportunity) and proves pipeline impact. Clear input. Clear output. No platform sprawl.

ABM was once the hill marketers would die on to secure budget. Now it's the platform they're trying to escape. 

Better, cheaper point solutions tied to revenue production are out there. 

I hope those displaced AEs are finding their new homes there.

I've spoken to 63 B2B marketers in the last 30 days. Every single one thought they were running "cross-channel" campaigns. They weren't.

What they're running are "multi-channel" campaigns. 

And honestly? I also didn't understand the difference at first.

HERE'S THE TEST: 

If you need to install a separate pixel for each ad channel, you're running multi-channel. Not cross-channel.

What hurts is that the difference is costing you up to 30% in wasted spend.

THE CONFUSION:

Platforms like Demandbase, 6sense, and AdRoll call what they do "cross-channel advertising."

For years, I nodded along. Made sense to me. We're running ads across multiple channels, seeing everything in one dashboard—must be cross-channel, right?

Nope.

It's multi-channel with a unified dashboard. 

HERE'S THE DIFFERENCE

Multi-channel: 
→ Running ads on LinkedIn, Meta, Google,  programmatic & others. 
→ Each channel has its own pixel. Each campaign is optimized separately. 
→ You see all your data in one place, but behind the scenes, nothing talks to each other.

True cross-channel: 
→ Running ads on LinkedIn, Meta, Google, programmatic & others. 
→ One universal pixel. All channels learn from each other. When LinkedIn drives a conversion, Meta knows. When Google finds a winning audience, LinkedIn adjusts. Real-time optimization across every platform.

The 'ABM platform' Example:

You install 'ABM Platform's' pixel. 

Great, now you can track conversions across their publisher network.

But you still need to separately install: 
→ LinkedIn's pixel 
→ Meta's pixel
→ Google's pixel

'ABM Platform' shows you the results in one dashboard. 

But your campaigns are still optimizing in silos. 

LinkedIn doesn't know what's working on Meta. Google doesn't learn from LinkedIn's conversions.

You're manually adjusting each channel based on data that's days or weeks old.

WHY THIS MATTERS 

Cross-channel optimization means every platform learns from every conversion, regardless of where it happened.

That's how you lower your CPAs.

TAKEAWAYS 

→ 'Multi-channel' sounds the same as "cross-channel."

→ But if you're still installing multiple pixels, you're not getting cross-channel optimization. You're getting multi-channel reporting.

→ There's a huge difference AND it's making your CPAs more expensive than they should be. 

→ Digital advertising is deliberately complex. The terminology is vague on purpose. But once you understand what's actually happening behind the dashboard, you can't unsee it.

→ One pixel to rule them all. That's real cross-channel. Everything else is theater.

Last week I had a call with the global paid media lead at an $80B cloud storage company.

They've been through the exact evolution most B2B marketers are trying to make right now.

Over the last 3 years they've made the move from following the "budget," to following the "buyer." 

Here's what I mean...

THE OLD WAY (2-3 years ago, following "budget"):
→ Agency-run campaigns 
→ Channel specialists (Facebook person, LinkedIn person, Google person) 
→ Fixed quarterly budgets per channel 
→ Native platform pixels and dashboards 
→ Export everything to spreadsheets 
→ Attribution was foggy at best 
→ Adjustments came days or weeks after campaigns ended

THE NEW WAY (today, following the "buyer"):
→ In-house, channel-agnostic teams 
→ Regional leaders (Americas, EMEA, APJ) with all platforms as tools 
→ Custom unified pixel feeding into their data warehouse 
→ Real-time cost-per-MQL tracking 
→ Real-time visibility into budget shifts based on performance and seasonality 
→ Multi-touch attribution connecting ad exposure to closed deals 

The key shift: "Follow the buyer, not the budget."

They stopped organizing around channels and started organizing around customer journey.

Here's what's working:
→ LinkedIn costs more per click, but quality is higher 
→ Cost-per-MQL ends up comparable to cheaper channels 
→ They can see which regions need which platforms 
→ Budget moves to where it's working, regardless of original plan

Here's what's still manual:
→ Shifting budgets between native channels and ad groups.
→ Campaign setup. Creative activation. UTM tagging.

Even with all that sophistication, someone's still logging into each platform to build ads, adjust spending and build attribution mechanics. 

Reporting: ✅ Solved 
Attribution: ✅ Solved 
Dynamic Optimization: ⏳ Still manual
Activation workflow: ⏳ Still manual

The Lesson:

Most marketers think they need to solve everything at once.

This team solved one problem at a time:

→ Took it from the agency, brought it in-house (control)
→ Unified the data (visibility)
→ Built attribution (insights)

Now tackling activation (efficiency) and real-time optimization (speed) 

If you're spending at least $50K+/month on B2B ads and trying to figure out the path forward, this is the roadmap.

Don't try to jump from silos to perfect in one move. Solve one layer at a time.

JSESSIONID

li_at

Yesterday I took a meeting for a $100 gift card and had the weirdest acid trip flashback to 2013.

Back then, I was running Tapjoy offer walls, paying users in-game coins to install "Russia Date" and "China Date."

User installs app → gets 100 coins → I get paid $15 → advertiser gets a "user."

The model exploded. Incentivized installs went from $0 to a multi-hundred-million dollar market in 18 months.

Why? 

Cheap scale. Installs at $0.06 vs $1.22 organic. Dashboards looked amazing.

Then advertisers checked retention: 90% deleted within a week.

The users had no intent. Just incentive.

Google and Apple cracked down. 

The market collapsed by 2015.

Sitting in yesterday's demo, I realized I'm doing the exact same thing.

The AE asked about my challenges. I said "just exploring options."

Translation: I'm here for the gift card.

No intent. Just incentive.

But I'll be counted as an MQL in marketing's dashboard.

Three months from now, that AE's manager will ask "Why aren't these closing?"

Same question advertisers asked me in 2013 "Why aren't these users converting?"

Same answer: Because they never actually cared!

THE PATTERN: 

→ Fast growth on volume, not quality. 
→ Great dashboard metrics (installs/meetings). Terrible metrics that matter (opp creation/close rates).
→ Gift card meetings close at 2-5% vs 15-20% organic.
→ Just like app stores cracked down on fake installs, platforms will crack down on fake intent.
→ LinkedIn already flags "incentive-based lead gen" in policies.

THE LESSON (I learned in 2013):

→ If you have to pay someone to care, they don't. No intent. Just incentive.
→ B2B marketers are learning this right now.
→ Stop optimizing for leads. Start optimizing for pipeline (duh, but hard to do when leadership wants you to drive "More leads!") 
→ The people taking your gift cards? They're just people who like free money.

Huge difference between unified reporting and unified execution.

Unified reporting = all your channels’ performance in one place. You optimize “after the fact” natively within each channel separately. 

Unified execution = all your channels’ performance in one place. You optimize in real-time with AI (fancy af) in the same place across each channel simultaneously. 

Unified reporting is the status quo…and if you change nothing you’ll keep spending 30% more on your MQA signals.

Unified execution is where things are going and teams that operate this way will be the ABM 2.0 iconoclasts.

Paid media advice: "Follow the buyer, not the budget." Easy to say. Hard to pull off…

The paid media lead at the #1 company on the Future 50 list did it…here’s his journey:

THE OLD WAY:

→ Large agency running everything

→ Teams organized by territory and channel (NORAM Facebook specialist, EMEA LinkedIn specialist, etc.)

→ Fixed budgets per channel decided upfront ("$300K on Facebook this month, $500K on LinkedIn")

→ Individual tracking pixels for each platform in GTM

→ Export results from each channel natively, crunch in spreadsheets

→ Could see which audiences engaged on which channels, but couldn't adjust in real-time

→ Changes came post-campaign, days or weeks later

→ Actual conversion by channel? Foggy at best

THE NEW WAY:

→ Moved in-house for control, transparency, efficiency

→ Built their own unified pixel (not relying on each platform's conversion pixel claiming last-click attribution)

→ Strict UTM parameters track which visitors came from which channel

→ All raw data feeds into their data warehouse

→ Custom dashboards show real-time performance by actual MQL conversion

→ MQL conversion takes place based on engagement threshold rather than “webinar lead” or “form fill lead”

→ Platform APIs allow dynamic spend adjustment, stop/start ads, reallocate budget by channel

→ Still organized by territory, but channel-agnostic

→ Focus on MQL conversion goal, not budget and CPC targets

→ Each advertising channel is a tool in the territory's toolbox to hit conversion targets

THE RESULT:

They can now optimize at cost-per-MQL down to cost-per-opp, instead of cost-per-click. 

They move budget dynamically based on what's actually driving qualified pipeline, channel by channel.

WHAT'S STILL BROKEN:

Even this incredible team (at one of the world's largest, most admired tech companies) has room for improvement:

→ Unified REPORTING pixel ✅
→ Unified EXECUTION across channels ❌
→ Dynamic creative setup ❌

Each channel still operates in a silo for learning and optimization. They don't talk to each other. 

Launching campaigns is still highly manual…creative setup, UTM setup, audience targeting all done in-platform.

THE TAKEAWAY:

This is the journey:

From agency → in-house → unified reporting → channel-agnostic execution.

Most marketers are stuck at step 1 or 2.

This team made it to step 3 and is honest about what's next.

If you're spending $50K+/month on B2B ads and trying to figure out the path forward, this is the high level roadmap.

taplio

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Zeb Couch 🤜🤛

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taplio

The Battle

Scott Martinis

Zeb Couch 🤜🤛

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