Bill Stathopoulos

Founder

👋 I'm Bill, and here's my story:

1. Building SalesCaptain, an Outbound & AI GTM agency for B2B SaaS to $3M+ ARR, while being a digital nomad for 4 years.
2. Authored a book - "Cold Email Secrets"
3. Scaled a Growth Marketing Agency to $1M ARR at the age of 28. Grew the team from 7 to 25+ employees in 3 years. Closed clients like Nestle, Revolut, GE, and the Singapore Airport.
4. Helped multiple startups go from zero to $5M+ revenue in 18 months since 2015
5. Trained 2,500+ Growth Marketers in the last 5 years
6. Built the speakers lineup for Ad World, with 50k+ attendees and 100+ speakers, making it the largest advertising conference in the world
7. Interviewed Seth Godin, Scott Galloway, Arianna Huffington, Rory Sutherland, the CMO of Samsung, the CMO of Hubspot, and 30+ world-class Marketing executives.
8. Published the book “Cold Email Secrets”, the bible of modern Outbound & GTM. 
9. Named “Top Lead Generation Voice” on LinkedIn in 2024
10. Became the Clay Club Host in London, leading a team of 15+ GTM Engineers

What you'll get working with me:
🧲 Your Go-To-Market (aka GTM) Strategy
🏀 Optimize your Marketing channels; make the most of your budget
🏆 Build systems for User Acquisition, Activation, Retention, and Revenue

Peace, love & growth ✌️

Bill

Co-Founder

We build and scale Outbound Sales systems that include multi-channel prospecting, lead response, and our cutting-edge processes to help you build your business.

If I asked you right now:
Who owns pipeline end-to-end in your GTM motion?

If the answer isn’t crystal clear,
that’s a problem.

In many teams, GTM looks like this:

- Marketing runs inbound
- Sales runs outbound
- RevOps fills the gaps

Everyone cares about pipeline.
But nobody owns the full motion.

Does this work? No.

What actually works in 2026 (in practice)

After seeing hundreds of GTM motions up close, one pattern keeps winning:
Inbound, outbound, and signals treated as one system.
Not three separate plays.

Here’s how we make that work 👇

1️⃣ Outbound isn’t just top-of-funnel

Outbound should exist across the entire funnel:
Top: ICP-based awareness (relevant, not clever)
Middle: Signal-triggered follow-ups (timing > volume)
Bottom: Direct offers when buyers are already close

2️⃣ Inbound is not “wait and hope”

Inbound-led outbound means this:
Someone visits your site, attends a webinar, or signs up → you act, instead of letting the lead sit untouched.

Inbound creates interest.
Outbound creates momentum.

3️⃣ Signals don’t create pipeline, ownership does.

Signals only matter if someone is accountable for:
- who acts
- when they act
- and through which channel

No owner = dead signal.

4️⃣ Judge the system by pipeline, not activity

If your dashboards celebrate:
- emails sent
- sequences launched
- campaigns shipped
You’re measuring effort, not outcomes.

The only question that matters:
Is this system producing pipeline predictably?

Between SalesCaptain, HeyReach.io, and Zapmail.ai,
this exact system helped generate ~$25M in revenue.

This is exactly what we’re breaking down live in an upcoming GTM Roundtable, with operators from the 3 companies building these systems every day. I will be speaking with:

Ilija Stojkovski (CRO, HeyReach.io)
Kaustubh Wadhwa (Product & Growth, Zapmail.ai)
Bojana Petkovic (Ecosystem Lead, HeyReach.io)

This isn’t an inbound vs outbound debate.
It’s about how teams are using both to build one coherent revenue motion.

We're meeting live on Zoom, next Tuesday, Jan 27, at 19:00–20:00 EET.
Link to register: https://luma.com/udv8tm4q

If pipeline predictability matters to you this year,
this session will be worth your time.
(come with all your questions).

CEO, SalesCaptain | Clay London Club Lead 👑 | Top lemlist Partner 📬 | Investor | GTM Advisor for $10M+ B2B SaaS

No, your GTM engineer can’t fix your outbound.
Read this before you hire a GTME.

(This is part 1/5 GTM mistakes you shouldn’t carry with you into 2026.)

I was on a sales call this week with a founder who said:
"We hired a GTM Engineer 6 months ago… but our pipeline growth is minimal."
I asked: “What’s your team structure?”
She said: “I have a GTME.”
....

One of the most common GTM mistakes I see:
Founders hire a technical expert, 
and expect them to drive both pipeline and revenue.

It doesn’t work that way.

Here’s what actually works (and how we structure GTM at SalesCaptain):

You need these 3 roles
1️⃣ GTM Strategist: owns strategy (ICPs, messaging, cross-channel orchestration)
2️⃣ GTM Engineer: builds AI/data workflows, connects APIs, scales infra
3️⃣ Full-Stack AEs: convert pipeline, leverage infra, feed insights back

We learned this the hard way:
One person can’t own both strategy and execution.
This is too much switching between contexts, which leads to too many dropped balls.

So we tested different structures till we got it right.

→ We launched campaigns twice as fast
→ Our messaging started resonating better
→ It became easier to see what was actually driving revenue

We’ve helped clients implement the same structure, and the numbers keep proving it right.

So let me ask you this 👇 
How’s your GTM team structured?
How is it working for you?

From my conversation with Milan Savov, on Leaders of Growth podcast (I will add the link in the comments).

When it comes to GTM data, which pill are you taking? 💊

Every GTM team wants the same thing:
A growing pipeline that makes the best use out of your reps' time.

But there are two very different ways to get there.

1. 🟦 Blue Pill GTM:
Buy more lists → Get more leads.

In this path you:
- Buy a CSV from Apollo, ZoomInfo, Cognism,... take your pick.
- Filter by title
- Send 1,000 cold emails.
- Wait for someone to book.
- If replies drop… buy a bigger list.

This path feels productive (more rows, more potential.)
But practically, you get bloated CRMs, irrelevant messaging, and reps spending their time chasing leads.

2. 🟥 Red Pill GTM:
Build a signal-driven pipeline: ICP first → Signals second → Messaging last.

In this path, you:

- Define ICP beyond job titles (think tech stack, hiring motion, headcount trends).
- Layer real-time signals like funding, exec changes, tool adoption, website shifts.
- Enrich with context: How does this company make decisions? What’s likely top of mind this quarter?
- Write emails that answer: Why me? Why now?

When you do this, your first touch feels like a warm intro,
because it is the right message, to the right person, at the right moment.

I don’t know which pill you’ll choose.

What I know is the best GTM operators in 2026 are building living, breathing pipelines.
Ones that update daily, prioritize based on intent, and let you engage buyers before your competitors even realize they’re in-market.

The tools exist.
The data exists.
The process is teachable.
The only question is:

🟦 Keep buying lists?
🟥 Or build a modern GTM system that prioritizes relevance over volume?

#GTM #Outbound #SalesCaptain

GTM Engineering job postings went up 205% in 2025 vs 2024.
Why?

Because revenue teams have reached a breaking point.

They’re not short on tools, AI pilots, or headcount.
They’re short on people who own the system end to end.
That’s what GTM Engineers solve.

They build the infrastructure that makes revenue repeatable, in ways like:

* Turning messy signals into structured actions
* Making outbound workflows scalable across reps
* Connecting tools and data so AI can actually drive outcomes
* Designing systems where pipeline grows instead of resets

How do you know if your team needs a GTME? 🤔 

Here’s what it looks like when the GTM system has no clear owner:

- Each rep runs a different version of the playbook
- “Integrated” tools constantly break handoffs
- CRM updates happen manually (if at all)
- AI experiments never make it into live workflows
- Weekly pipeline reviews feel more like firefighting instead of optimization

If 2 or more of these sound familiar, you need a GTME.

And if you’re thinking,
"That sounds like the kind of impact I want to have..."

GTM Engineering is one of the few roles growing fast, even in a tough market.
This role sits at the center of AI, systems, and revenue.
And it will only become more and more foundational.

We put everything into the visual below:
The 2026 GTM Engineer Playbook
What the role is, what skills it needs, expected salary and how to prepare for it.

Save it.
Share it with someone who wants to grow into this role.
Tag them below, this could be their next move.👇

Not all GTM partnerships are built the same.
Many get announced, logos get swapped, and nothing changes in how pipeline is built.

The successful ones have one thing in common:
Both sides are building real GTM, not just pitching it.

We’ve worked with lemlist for years, since the early partner program.
What made it work was a shared worldview: 
Outbound isn’t a sales play anymore.
It’s part of the GTM infrastructure, just like your CRM or analytics stack.

Then last year I sat down with Charles Tenot, CEO of lemlist (now a $35M ARR company). 
We shared a deep alignment on where outbound is breaking, and how real operators are rebuilding it.
You can feel that when a team runs their own GTM at the same pressure and pace their customers do.

The note and small award we received recently were a byproduct of that kind of partnership, one where feedback loops, shared pain, and long-term bets matter more than metrics.

Big thanks to Julia Guenier, and the whole lemlist team for operating with that mindset.

Excited for what's coming!
Let’s keep building 🔥

Do you ever stop and ask "Why do people actually buy from us?"
That's the key to finding the best signals.
 
Instead, I get these questions a lot 👇 
"Is hiring a good signal?"
"What intent data should we buy?"
"Which tool has the best triggers?"

Wrong questions.
 
The real insight doesn't come from external signals. It comes from your own closing history.
 
So, before you add another tool, do this:

→ Pull your last 10–20 closed deals and ask one question:
What changed inside the company before they bought?
 
For example, at SalesCaptain, we analyzed our closed deals over the past 4 years.
The pattern that kept appearing: companies who changed their CRO in the last 6 months.
(Within 1–6 months of a CRO change, that's when they're ready to rebuild GTM infrastructure.)
 
What we see across mature GTM teams:

- New CRO/CMO hired → mandate to "fix pipeline"
- Ownership of revenue changes hands
- Shift from founder-led sales to systems
- Pressure to scale without hiring more reps
 
These moments create forced action.
And forced action beats generic "interest" every single time.
 
Here's something GTM teams need to remember:
Signals are hypotheses, not truths.
 
A signal only becomes valuable when you:
1️⃣ Tie it back to why people actually buy from you
2️⃣ Test it across months, not days
3️⃣ See it repeat consistently, not once
 
This is why signal-led GTM isn't about finding the signal.
It's about building a system that:

-> Tests signals continuously
-> Scores them against real revenue outcomes
-> Routes action based on impact, not noise
 
This is how pipeline becomes predictable.
 
This is from the amazing conversation I had yesterday with Ilija Stojkovski (CRO, HeyReach.io) Kaustubh Wadhwa (Product & Growth, Zapmail.ai) and Bojana Petkovic (Ecosystem Lead, HeyReach.io).
 
Here's the link to the full webinar: ﻿https://lnkd.in/dyTbkVyT

P.S. if you want the slides I shared in the webinar, DM me.

What if you treated outbound like a marketing channel?

That’s how we run it at SalesCaptain.
And for GTM teams with a finite TAM, it’s literally a cheat code.

Here’s how you can operationalize it:

✅ Quarterly touchpoints

If your ICP is 5,000 companies, your goal isn't just to "get replies", it’s to stay top-of-mind.
We run outbound like marketing campaigns: built around themes, refreshed quarterly, and optimized for relevance.

Orchestrated with: Clay, and delivered via lemlist and HeyReach.io.

What you can track:
- % of accounts touched this quarter
- Re-engagement from dormant accounts
- Reply trends by persona/topic

✅ Email signals are real-time intent

Opens, clicks, site visits... these are all triggers.
If someone engages, you need to follow up fast.
Sub-60 second replies consistently lead to 2-3X more meetings booked.

Tools: Instantly.ai, Midbound, Clay, n8n, plus Lemlist and Heyreach for outreach.

What you can track:
- Speed-to-lead (How fast you respond after a lead shows intent)
- Signal-to-meeting conversion (% of intent signals that actually turn into booked meetings)
- Channel effectiveness

✅ Outbound needs distribution of insight

We’re not here to “check in.”
Our highest-performing messages offer something useful like frameworks, benchmarks, or patterns the buyer hasn’t seen before.

Research & Personalization via: Claygent, Twain and/or Octave.

What you can track:
- Response rate to insight-led messages
- “This was helpful” kind of replies

Video below from my conversation with Stefan Conic 🙌

Outbound trying to be smart -> Stupid.
Outbound trying to be relevant -> Smart.

Part 2/5 of mistakes you can’t afford in 2026

Your outbound messages fail because you're trying to impress.
Instead of trying to help.
When in reality, winning campaigns are useful, not clever!

Here are some examples of useful messages:

- Lead magnets that are genuinely valuable 
- Insights specific to the buyer’s market, role, or stack 
- Strong offers (often free implementation or teardown) 
- FOMO through hyper-relevance “We’re already working with your top 2 competitors” 

But none of that works if your data’s trash.
You can’t fake context, nor can’t prompt your way to get trust.

When the data’s real, the message writes itself.
Short, relevant, to the point.
And that’s what wins.

Why US companies are winning the GTM execution race, 
and everyone else is playing catch-up

Over the past couple of years, while working with GTM teams across the US and Europe, I kept noticing the same pattern:

Same conferences.
Same tools.
Same markets.
But very different questions.

US teams asked:
“How do we optimize our 30+ Clay workflows?”

Most European teams asked:
“How do we get more leads?”

Clay calls this GTM Alpha; the velocity at which a company can execute go-to-market.
And GTM Alpha is quietly splitting B2B into two camps.

Here’s where people get confused:
→ US leads global AI investment with $109.1B, nearly 12× China and 24× the UK.
→ 95% of businesses globally already use or plan to adopt AI by 2025.

On paper, it seems like everyone’s on equal footing, but they’re not.

Europe often reports higher AI usage:
→ 13.5% of EU enterprises in 2024 vs. ~8.7% of US firms in 2025.

So why is the US still pulling ahead?

Because adoption is not depth!

It’s not whether companies use AI, but how deeply it’s embedded in their GTM system.

-> In the US, organizational AI adoption is ~82%, with 99% of Fortune 500 already onboard.

Most teams start the same way:
AI for writing emails and summarizing calls.

The best teams go further. 
They run GTM with AI:
– Data enrichment
– Intent-based segmentation
– Multi-channel orchestration
– Real-time routing to reps
(Same tools, different outcomes.)

So how do you catch up? ⚠️ 

Start with the foundation.
You don’t need 30 workflows. Just the right ones, in the right order.

Phase 1️⃣: Clean your data
CRM enrichment
Lead routing
Basic scoring
(Most teams skip this, and fail later.)

Phase 2️⃣: Broad ICP outreach
List building from LinkedIn, Google Maps, etc.
AI-powered personalization
Email + LinkedIn sequencing

Phase 3️⃣: Add intent signals
Job changes
Hiring spikes
Competitor followers
Event attendees

Phase 4️⃣: Activate inbound
Visitor ID
Form enrichment
LinkedIn engagement
Pricing page workflows

Phase 5️⃣: Build your ABM stack
Account tracking
Committee mapping
Tool change detection
Expansion workflows

Here's something you need to keep in mind:
-> Despite 78% of orgs using AI in some function,
70–85% of AI projects still fail.

Why?
Because teams jump to Phase 5, without fixing Phase 1.

AI-led GTM drives:
– 3× more site visits
– ~50% larger deals
– 30% faster launches and ~25% workflow gains

Some teams are still debating tools.
Others are optimizing conversion by segment, time-to-MQL, and cost per account.

Stop asking:
“How do we get more leads?”
Start asking:
“How do we orchestrate GTM?”

Thoughts? 👇

You tracked the signal.
You did what you were supposed to do.

Website visit.
Job change.
Engagement spike.
...
So you reached out.
And nothing happened.
No reply, no pipeline!
 
This is where most GTM teams get confused.
Because the problem isn’t that you missed the signal.
It’s that the signal didn’t answer the most important question:

👉 Why now?
 
Your GTM team already has the signals:
Website visits, job changes, social engagement, product usage, and hiring signals.
 
The issue isn’t lack of data.
It’s that signals don’t tell a story on their own.

- A website visit doesn’t mean interest.
- A job change doesn’t mean intent.
- Engagement doesn’t mean readiness.

On their own, these are contextless events.
And what usually happens next is predictable:

- Signals get pushed into Slack.
- Logged in the CRM.
- Tagged inside GTM tools.
But no one defines:
1. what changes because the signal happened
2. who should act
3. how the message should adapt
4. or when not to act at all
So teams react instead of orchestrate.

What the best GTM systems do differently is simple (but not easy):

1️⃣ They combine signals, they don’t chase them
One signal rarely means anything.
Multiple signals, across time, start to explain intent.

2️⃣ They score accounts, not activities
Fit × Engagement × Potential Value.
Not “someone clicked,” but “this account is worth time now.”

3️⃣ They design actions before automation
Signals are inputs, not instructions.
The action depends on where the account actually is.

4️⃣ They protect human effort
Sales and marketing only engage when the system says timing is right.

Everything else gets deprioritized automatically.
That’s when outreach stops feeling random.
and pipeline flows.

I’ll be breaking this down live with Erwan Gauthier VP of Growth at lemlist, including how the team at Lemlist are building signal-led GTM motions going into 2026.

Link to register: https://luma.com/zn8wfvy6

This session will change how you think about signals.

Your next 50 best customers will look a lot like your last 5.
 
We had a client burning $5K/month on cold outbound trying to "expand TAM."
1% reply rate, zero pipeline, team demoralized.
 
I asked them one question: 
"Who are your 10 favorite customers? The ones who get it, move fast, and actually implement?"
 
They sent me the list, we spent 2 days analyzing them.
Then we killed every other campaign they were running.
 
What we did instead:
- Pulled their best 15 customers from Salesforce
- Imported them into Clay
- Used Ocean.io to find 200 companies with the same industry, size, tech stack, and buying triggers
- Built automated outreach mentioning the customers they mirror via lemlist
- Let it run
 
The results:
- 15% reply rate (vs. 1% before)
- $400K pipeline in 90 days
- 4 deals closed in the first 90 days

Same team, same budget.
 
So what changed?
When you target lookalikes, you have an advantage:
- You already know the exact problem they have
- You already know what messaging lands
- You already have proof in their language
- You already know who makes the buying decision
- You already know how long the sales cycle is
 
The mistake most teams make is that they chase "new markets" way too early.

They see their core ICP starting to saturate (or think they do) and immediately pivot to adjacent segments, new verticals, or "enterprise" just because the board asked about it.

Meanwhile, there are 50+ companies exactly like your best customers who haven't heard from you yet.
 
The fastest pipeline growth comes from doubling down on what already works.
 
Here's the exact workflow we run:
Step 1: Export your best 10-15 customers (the ones you'd clone if you could)
Step 2: Import them into Clay
Step 3: Use Ocean.io, Apollo, or Findymail to find lookalikes based on:
Industry
Company size
Tech stack
Growth signals
Location (if relevant)
Step 4: Enrich with decision-makers using Clay's waterfall (Datagma → Apollo → Findymail)
Step 5: Build sequences in lemlist/HeyReach.io mentioning the customer they mirror:
"We recently helped [similar company] in [their industry] solve [specific problem]. Saw you're in a similar space and thought this might be relevant."
Step 6: Let it run, measure, and scale what converts
 
Average result: 3x more pipeline in 60 days, targeting companies they already know how to close.

If you haven't exhausted your core ICP, don't go chasing new markets.
 
If you know your top 10 accounts and want help applying this playbook, DM and I will be happy to help you.

We scraped Google Maps photos of 2,000 bakeries
and used AI to detect bread-making machines 🥖 
Sounds insane, right?
 
But this is exactly the kind of custom signal that’s replacing generic intent data in 2026.
 
Everyone’s buying the same intent data.
Which means everyone’s reaching out to the same prospects,
at the same time,
with the same “personalized” message.
 
Which means you are always standing in the same line with your competition.
 
Here’s what changed our entire GTM approach at SalesCaptain:

We stopped relying on off-the-shelf signals.
and started building our own.
 
Not:
– Hiring intent from ZoomInfo
– Funding announcements from Crunchbase
– Sales Navigator filters everyone else is using
 
Instead, we built signals only we had access to.

Here are some real-life examples from our client work:
 
1. Wellness and self-care software company 💇‍♀️ 

- Scraped Google Maps + websites for salons/spas
- Detected multiple locations or recent expansions
- Identified operators outgrowing spreadsheets/manual tools
- Triggered outreach during operational scaling

Result: 400+ positive replies in 5 months

2. Cybersecurity company 🥷 

– Monitored public breach reports in real time
– Identified relevant security teams
– Reached out while the problem was active

Result: $200K+ ACV meetings in a single quarter

3. Recruitment platform 💼

– Scraped job listings across multiple sources
– Identified companies actively hiring
– Matched HR decision-makers to real demand

Result: 710+ demo calls in 10 months

These aren’t signals you can buy from a vendor.
They’re competitive advantages built from:

– Custom data sources
– AI enrichment of unstructured data
– Community, ecosystem, and event signals

The pattern I see across every high-performing GTM team:
They don’t ask,
“Which intent tool should we buy?”
They ask,
“What data would give us an unfair advantage competitors can’t access?”

Then they build it!

If you want to design custom signals for your market and orchestrate them across sales, marketing, and ops, you know where to find me. 😎

Clay just unlocked super-multichannel with ads.

Not just email + LinkedIn.
The same audience can now be targeted across email, LinkedIn, and ads (LinkedIn, Meta, Google) in a unified way.

Why you should care:

1️⃣  One audience, one system, not separate targeting logic per channel
2️⃣ Prospects see you programmatically across channels, not randomly
3️⃣ You can increase spend and message frequency as signals increase
4️⃣ Website visits, product views, demo signups → more spend
5️⃣ ICP-fit accounts with weaker signals → lighter spend
6️⃣ Outreach and ads are sequenced based on warmth

Instead of managing multiple audiences across multiple platforms,
you control exposure, intensity, and timing from one place.

The warmer the prospect, the more they see you.
The colder the prospect, the less you spend.

This is huge 🔥

ADS IN CLAY. The most exciting new feature of everything Clay has been working on in my opinion is Ads.

We are seeing customers get ~much~ higher match rates than they have today against their audiences on LinkedIn, Meta and Google which is a massive win for performance marketing teams.

Ads platforms as a new export destination in Clay also enables very interesting campaigns. For example now you can:

1. Setup website intent in Clay to deanonymize web traffic
2. Search in Find People for your ICP contacts
3 Enrich them to find their hashed advertising IDs using our ads ID waterfall
4. Create audiences in Ads to run ABM campaigns
5. Convert them deeper into the funnel where you can message them via the various messaging tools in Clay

This is in open beta today for enterprise customers and we are looking for lots of feedback from performance marketers to make this best in class. 

DM me or comment for more.

Founders ask me all the time:
“Which channel should we double down on?”
 
SEO?
Google Ads?
LinkedIn Ads?
Social?
Cold Email?
 
After working with 60+ B2B teams at SalesCaptain, here’s the reality:
👉 Most channels work.
👉 Not all channels work for your stage, deal size, and urgency.
 
So instead of opinions, let’s benchmark 👇
Cost • Targeting Precision • Scalability • ROI • Time to Results
 
📬 Cold Email / Outbound
• Very low cost (tools + time)
• Extremely precise targeting
• Highly scalable
• Very high ROI when done right
• Fast results (1–2 weeks, if you have warmed up inboxes)
 
💰 Google Ads (Search)
• High CPCs
• Great for bottom-funnel intent
• Moderate scalability
• Fast if demand already exists
 
📈 SEO / Content
• High upfront investment
• Long-term scalability
• Massive ROI over time
• Slow to impact (3–6+ months)
 
🎯 LinkedIn Ads
• Surgical B2B targeting
• Expensive
• Moderate scalability
• Strong for awareness + nurture
 
🎥 Social Ads (Meta / TikTok)
• Scalable
• Interest-based targeting
• Better for DTC than niche B2B
 
🤝 Referrals / Partnerships
• Highest conversion rates
• Hard to scale
• Not predictable on their own
 
Cold Outreach wins when:
✅ You know your ICP
✅ Your offer is clear
✅ You want speed and control
✅ You’re building a repeatable engine, not betting on algorithms
 
📊 Save this. Share it with your Marketing Lead.
 
Use it to decide where your next $$$ actually goes.
 
And if you want help designing an Outbound system
that scales without burning cash,
you know where to find me.
 
#coldemail #outbound #b2bsales #gtm #demandgeneration #saasgrowth #revenuegrowth

Closed-lost isn’t a graveyard,
It’s a dataset.

Most teams lose a deal and move on.
We do the opposite:

We turn every closed-lost deal into a future meeting… using the exact reason they said “no”.

Here’s the 8-step workflow we built (we used this with a fintech client last week, and reactivated 3 deals in 8 days).

1) Pull closed-lost from HubSpot
Deal name, close date, close-lost reason, notes, decision maker.

2) Pull the actual buyer context from Gong
First + last call transcript.
Not “AI personalization”… the real objections, timelines, and blockers.

3) Enrich with real signals
Funding, acquisitions, new hires, restructuring, product launches.

4) Generate a reactivation recommendation
Why they said no
What changed
When to re-engage
What angle will land now
What to avoid

5) Turn that into a short email (4-part structure)
Intro → original blocker → why now (signal) → 15-min CTA.

The point is to send the one email that makes the buyer think:
“Yeah… this is actually relevant now.”

Imagine if you’re sitting on 200+ closed-lost deals, how much pipeline you could be generating with this workflow.
If you want a workflow like this built for your team, you know where to find me. 😉

Founder @Blue Water Marketing | eCommerce & Digital Marketing Nerd

Hey, I’m Chris Marrano.

I’ve spent the last 15 years in the trenches of digital marketing, starting at Mullen (Boston) working with brands like Match.com and LendingTree, then going client-side at Harvard Business School before launching Blue Water Marketing from the ground up.

Today, I run an eCommerce growth agency that helps Shopify brands scale from 7 to 8 figures—without bleeding budget.

We do this by combining Meta Ads, Google Ads, Klaviyo, and content at scale with deep financial visibility (think MER, aMER, CAC, and contribution margin). We don't just run ads, we integrate into your brand’s systems and decision-making so growth is profitable.

I'm also building ADIQ.AI, an AI-powered SaaS platform that helps brands analyze creative performance in real time—because in this market, "creative testing" without data is guesswork.

Outside of business, I live in South Florida with my wife Taylor and our two boys. I’m a family-first operator. Weekends usually involve beach days, t-ball games, and building something in the garage (usually with a goldendoodle supervising).

If you're a DTC founder looking to:
✅ Turn creative chaos into profitable customer acquisition
✅ Build predictable growth systems backed by numbers
✅ Actually understand what's driving your MER

Let’s connect.

Chris Marrano

I have been auditing eight figure ecommerce ad accounts with the same Claude skill.

No dashboards.
No new tools.
No custom reporting.

Just a simple export from Facebook Ads Manager dropped into Claude.

Every time I do this, the reaction is the same.

“Wait… how did it see that?”

Patterns jump out that are almost impossible to spot when you are clicking around Ads Manager. Things that feel obvious once you see them, but are completely invisible before.

It does not tell you what to do.
It shows you what you cannot unsee after.

If you are running a seven or eight figure Shopify brand and want the exact audit skill I use, comment SKILL and I will send you the MD file.

Scaling 7 & 8 Figure DTC Brands Profitably | Building AI-enhanced systems | Founder@BlueWaterMarketing | Founder@ADIQ.AI

Most brands are tracking 47 different creative metrics.

And they still can't tell you which ads are actually working.

I've audited hundreds of Meta accounts. The ones drowning in data almost always have the same problem: they're measuring everything and understanding nothing.

Here's where we start every diagnosis:
- Hook rate. Are people stopping? If less than 25% watch past 3 seconds, nothing else matters. Your ad isn't even getting a chance.
- Hold rate. Are they staying? ThruPlays divided by 3-second views. This tells you if your message lands after the hook.
- Creative diversity. How much spend is concentrated on your top 3 ads? Above 60%? Andromeda is starving for fresh concepts.

Those three numbers tell you if an account is healthy or dying.

But knowing the problem isn't the same as fixing it.

To actually improve, you need to track performance at the concept level — not the ad level. You need to see trends over 7, 14, 30 days. You need to know which hooks are working, which CTAs are converting, and which concepts deserve more iterations.

That's why we built a Creative Performance Scorecard.

One sheet that tracks concept-level performance over time — built around the metrics that actually predict winners under Andromeda.

It's how we answer "which concepts should we make more of" across every client account.

Comment "SCORECARD" and I'll send it over.

Most brands still check performance by logging into Ads Manager. (Free Resource)

We just ask our AI.

Over the last nine months, we rebuilt how we operate internally by plugging AI agents directly into our Meta ad accounts.

Now our team can ask questions in Slack or through voice and get instant answers like:
- What are our top performing ads by CTR this week
- Which creatives are creeping above our CAC threshold
- What trends are actually moving performance across ASC

The system pulls live data, compares it to historical benchmarks, and responds in plain English. If needed, it generates a visual report automatically.

This is not a dashboard. This is not automation for the sake of automation.
It is an operating system for performance marketing.

When creative is the only real edge, speed of decision making matters more than ever.

You cannot move fast if your data lives behind clicks, exports, and lag.

We are not replacing humans. We are replacing delay.

If you want to see how we built this and how you could adapt it for your team, comment AI OPS and I will send the walkthrough.

I had the chance to sit down with Dave Ten on his latest podcast, and we went deeper than surface level AI talk.

We unpacked the AI infrastructure we’re building, how Meta’s Andromeda update quietly changes how ads are selected and scaled, and where I believe AI is actually headed in marketing.

My core belief hasn’t changed.

The advantage is no longer clever account structure.
It’s signal quality, creative volume, and fast feedback loops.

AI is not here to replace teams.
It’s here to collapse learning cycles and make systems more resilient as platforms evolve faster than operators can react manually

If you’re building for the next version of ecommerce and paid media, this conversation is worth your time.

Check out the episode in the comments below.

We’re rolling out our AI Agent and AI Media Buyer Chatbot to beta users next week.

The internal team has been testing it for the past few weeks.

The feedback is insane.

The Agent monitors all your Meta accounts 24/7 like a junior buyer who never sleeps. Generates pause, scale, and alert recommendations and actually learns from every decision you make. 

Approve a rec that crushes? Confidence goes up. Reject one as too aggressive? Thresholds adjust.
It gets smarter the more you use it.

The Chatbot is like having a senior media buyer on call at 2am.
- “CPM spiked 40%—what do I check first?”
- “Should I kill this ad set or give it more runway?”
- “Client wants to know why ROAS dropped. Help me diagnose.”

Real answers. Based on your actual data. No waiting.

One works while you sleep.

One answers when you’re stuck.

We’re only letting in a handful of beta users. Drop “AGENT” in the comments if you want early access.

Summer 2025 broke a lot of Meta ad accounts for Shopify brands

We had clients hitting their best months ever in August. By September, some dropped from 3.2x ROAS to 1.6x.

Same creative. Same offer. Same budgets. Just... didn't work anymore.

The culprit: Andromeda's final rollout.

Here's what changed: → Interest targeting? Basically useless now → Lookalike audiences? Severely diminished → ABOs with 3-5 ads? Fatigue in days, not weeks

The algorithm is now 10,000x faster at processing creative variations. It doesn't care about your targeting anymore—it cares about what you're showing people.
So we rebuilt everything.

New testing structure: 15-30 ads per test instead of 3-5.

Creative diversity isn't optional anymore. It's the entire strategy.

And we leaned hard into AI. 3,200+ automations running weekly. What used to take 8 hours now takes 20 minutes.

Just gave a talk breaking all of this down—what happened, why it happened, and the exact systems we're using now.

Full video is live. Link in comments.

What did you see this summer? Drop your experience below.

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