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.

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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 🔥

Head of GTM Engineering at Clay

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. 😉

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"As an ad agency owner, I need unlimited creative that’s affordable, easy to use, and delivers high-quality results for my clients. GetAds is that. Their web portal is super easy to use, the price is the best in the business, and their team of designers are the best there is, bar none. I’m even impressed with their turnaround time. That’s all I need. Thanks, GetAds!" - Carlos C. ⭐️⭐️⭐️⭐️⭐️

"We are very very satisfied and will continue to use Get Ads for our business. They are almost fully integrated into our business via slack which is amazing and learn over time what we like and dislike." - Jake S. ⭐️⭐️⭐️⭐️⭐️

"GetAds has been a fantastic addition to our design suite. We are able to get strong B2B creative graphics/videos quickly with the GetAds team." - Josh L. ⭐️⭐️⭐️⭐️⭐️

Side note, our newest product helps media buyers & creative teams organize, collaborate, and save ad inspiration in one place. If you want to supercharge your ad creative workflow, sign up, it's free (forever) → getads.co/app

Want to chat? Shoot me a DM :)

Luis Camacho

AI is decimating my company and it’s probably doing the same to yours without you even realizing it…

Here’s the crazy thing I learned…

12:07 pm. I ask ChatGPT  “best UGC ad agency..”

It lists my competitors. We are not there. My coffee goes cold.

And the scary part?

This wasn’t a “research” query.

This was a buyer query.

Someone with intent. Someone deciding who to trust.

And AI confidently sent them elsewhere.

My first reaction was anger.

Then it turned into something worse.

How many people are doing this every day?

How many CMOs, founders, brand managers are asking AI who to hire and then seeing our competitors?

So I did what most founders do when they’re scared and pissed at the same time.

I went down the rabbit hole.

I wanted to understand how the h*ll you get seen by AI when AI is the one making the decision.

And that’s when I found a platform called Meridian.

It doesn’t try to get you traffic.

It shows you whether AI even knows you exist then gets you ranked higher. 

I don’t want other founders or CMOs to have that same moment:

Sitting there.

Watching AI confidently recommend your competitors.

Realizing deals are happening without you ever being in the room.

That feeling sucks.

So I’m sharing this to hopefully help one of you. 


Meridian lets you see things you literally cannot see anywhere else:

↳ Which brands AI recommends instead of you
↳ What sources AI is actually reading
↳ How often you show up across ChatGPT, Gemini, Perplexity, Google AI

One more thing.

I'm giving away the world's first AI visibility tracker that shows you exactly how you're ranking right now. Be aware, it may scare you.

Comment on Meridian, and I'll send it to you.

And yes, I am a Meridian partner because I believe in what they're doing.

Conversion-Driven Creatives On-Demand for agencies & brands with our streamlined process & platform. ⚡️

Stop writing briefs. Start publishing hypotheses.

Most briefs are mood boards dressed up as strategy. That’s why design teams make beautiful guesses and your ad account pays for them.

Here’s the brief that actually drives performance:

1️⃣ 3-Second Belief  
↳ One sentence the viewer must believe in 3 seconds. Example: "This snack keeps my toddler full until lunch."

2️⃣ Fail-Fast Conditions  
↳ Define what counts as failure in 48-72 hours. Example: "If Reels CTR < 0.4% and CPA > $45, kill creative."

3️⃣ Audience Micro-Story  
↳ Persona + context + motivation. Example: "Urban runner, 28-40, hurt by joint pain, wants quick recovery."

4️⃣ One Measurable Outcome  
↳ Pick one metric and timeline. Not 'brand awareness' — pick CPA, ATC rate, or ROAS in 7 days.

5️⃣ Next Experiment Ask  
↳ Give the team the exact variable to try next (hook, shot type, offer). Don’t leave them guessing.

Bonus: include the primary objection verbatim from customer research. If you can’t say the objection, you don’t understand the buyer.

Controversial truth: a brief that treats creative like a lab yields more winners than throwing money at "vibes." Briefs are your cheapest scaling tool.

Found this useful? Like, follow, and repost ♻️ so others can too!

ps. Want the one-page brief template we use to halve revision cycles? DM me.

Here’s an unpopular truth: swapping creative partners every time an ad set dips is the most expensive growth strategy in marketing.

If you want speed, scale, and compounding returns, stick with a good outsourced creative partner—especially one that owns part of the creative strategy. Here’s why:

1️⃣ Creative memory wins  
↳ Teams that stay together build institutional memory of audiences, hooks, and sequencing. Tests become data, not noise.

2️⃣ Strategy alignment reduces churn  
↳ When a partner helps set strategy, they optimize for LTV and journey, not just the next cheap conversion. That shifts every creative decision from short term to compounding value.

3️⃣ You get an R&D engine, not a vendor  
↳ A partner who tests, documents, and standardizes learns faster. You get libraries, templates, and playbooks that scale, cutting production cost per variation dramatically.

4️⃣ Faster algorithm adaptation  
↳ Partners who see patterns across brands adapt to platform shifts before your in-house team catches up. That’s the difference between reactive fixes and proactive wins.

Controversial bit: if you treat them like a transactional vendor you will get transactional results. Pay them to act like a partner—retainers, outcome bonuses, or equity align incentives and multiply focus.

Your creative partner should feel like an extension of your company, not an external checkbox. When they do, creative becomes an asset, not a cost.

Found this useful? Like, follow, and repost ♻️ so others can too!

ps. struggling with creative bottlenecks? We can help.

If you want Andromeda to love your account, confuse it on purpose.

Yeah, seriously.

Meta’s new algo rewards novelty. Feed it the same hero ad for months and it learns a narrow map of who will convert. That sounds good until the map runs out of roads.

Here’s a different way to think about creative testing: treat it like maintenance, not discovery.

1️⃣ Recalibration pulses  
↳ Every 7–14 days, launch 2 net new concepts that are intentionally different from your current winners. Different hook, different creative grammar, different CTA.

2️⃣ Temperature reset - allocate 10% of spend to exploration  
↳ Small budget. Big informational return. Let the system explore without risking your main CPA.

3️⃣ Shock and feed sequence  
↳ Shock with 2 radical concepts. Identify signals fast. Feed winners with 3-5 micro-variants to compound learning.

Why this works (and most brands miss it): Andromeda builds user embeddings over time. New concepts expand those embeddings. That lets the model personalize better, which improves match quality and reduces wasted reach. You are not just finding a single winner. You are expanding the pool of people who can become winners.

Stop treating testing like an afterthought. Make novelty part of your cadence.

Found this useful? Like, follow, and repost ♻️ so others can too!

ps. struggling with creative throughput? We can help.

Most teams don’t have a scaling problem.

They have a decision problem.

Every week, the same questions come up:

Which ads should we scale?
Which ones are lying to us?
Where are we wasting budget?

The answers are usually scattered across dashboards, channels, and gut instinct.

That’s why most creative testing slows down as spend grows.

Not because teams stop testing, but because decisions start lagging behind performance.

GoMarble built a set of AI agents to solve that exact gap.

Each agent is designed to look at your data the way a senior strategist would, but without the bottlenecks. They analyze patterns across accounts, creatives, and performance signals to surface what actually matters.

The agents show how this works in practice.

It breaks down how GoMarble’s agents:

• Identify which ads are safe to scale and which ones are about to break
• Spot creative patterns that are working across campaigns, not just one
• Flag false positives before teams over-allocate budget
• Turn raw performance data into actionable creative direction

It’s about compressing weeks of analysis into minutes, so creative and media teams can move with confidence instead of hesitation.

That’s the difference between reacting to performance 
…and staying ahead of it.

Comment ‘'GOMARBLE’’ to get access to the agents.

Your 50 variations aren’t creative diversity. They’re just the same idea with different lipstick.

Here’s the real difference most teams miss:

Variation = tiny tweaks inside one concept family
↳ Color, thumbnail, wording, timing. Useful. Fast.

Diversity = net new ad concepts
↳ New hooks, new stories, new formats, new entry points. Feeds the algo real novelty.

Why Andromeda prefers diversity (and why you should too)
↳ The model doesn’t just reward better thumbnails. It rewards new signals it can stitch into journeys. Give it small tweaks and it learns one story. Give it new concepts and it builds new journeys.

A simple operating system to win the Andromeda era:
1️⃣ 3:1 Rule
↳ For every 3 micro-variations you launch, create 1 net new concept. Stop bloating the same idea.

2️⃣ Batch net new concepts
↳ Launch 5–7 executions of each new concept (UGC, discrediting angle, authority piece, demo). Let the model recognize the pattern.

3️⃣ Measure signal, not just CPA
↳ Track reach lift, sequence engagement, and cohort conversion paths. Novelty shows up in upstream signals before CPC beats appear.

Controversial take: obsessing over micro-optimizations trains your account to be narrow. If you want algorithmic distribution, feed it variety, not redundancy.

Found this useful? Like, follow, and repost ♻️ so others can too!

ps. struggling with creative bottlenecks? We can help.

Controversial take: Outsourced creative strategy should run your ad tests for the first 90 days. Not just execute. Lead.

Here’s why most brands hire agencies for production and then wonder why nothing changes:

1️⃣ Outsiders force hypotheses  
↳ External strategists question sacred assumptions. That friction exposes which ideas are actual opportunities and which are brand myths.

2️⃣ They turn variety into learning velocity  
↳ Good outsourced teams deliver 30 to 60 micro-experiments in a quarter, not 3 "polished" concepts. Volume + structure = compounding wins.

3️⃣ They trade perfection for signal  
↳ Agencies can afford to push ugly, native-feeling hooks that reveal real user intent faster than an in-house team obsessed with pixel perfection.

4️⃣ They scale operationally  
↳ Fractional teams specialize in repeatable testing frameworks. You get a creative multiplexer that feeds the algorithm diverse inputs without blowing your budget.

How to make it work

1. Pay for learning, not assets. Fees tied to insights and validated winners.  
2. Give access, not approvals. 48-hour feedback windows. No endless iterations.  
3. Demand a public learning log. Weekly takeaways, winner templates, failed hypotheses.  
4. Treat them as a partner, not a vendor. Data access beats design notes every time.

If your agency refuses a learning-based contract, they want to stay comfortable. You want results.

Found this useful? Like, follow, and repost ♻️

Offers are lazy.

They ask customers to transact. Angles get customers to care.

Here’s why scaling with angles, not offers, wins long term:

1️⃣ Offers compress intent, they attract deal hunters
↳ 50% OFF gets clicks, not loyal customers. Cheap offers scale CPA but tank LTV.

2️⃣ Angles scale perception, they pre-qualify buyers
↳ Angles speak to identity, context, and urgency. They filter for buyers who stick around.

3️⃣ One offer, many angles is exponential leverage
↳ Keep the same pricing or promo. Test 12 angles across the same audience. Winners compound when you multiply creative formats.

How to operationalize it (practical playbook):

1. Map 3 core personas
2. For each persona, create 4 context angles (fear, aspiration, scarcity, social proof)
3. For each angle, craft 3 intensity levels (tease, proof, close)

Result: 3 x 4 x 3 = 36 distinct angles to feed the algorithm

Metric that matters: Angle Velocity
→ How fast you can validate an angle and create 3 creative variants for it. Faster velocity = faster scale.

Controversial take: If you’re rotating offers every week to chase volume, you are masking bad angle work. Fix the message first, then scale the spend.

Found this useful? Like, follow, and repost ♻️ so others can too!

ps. struggling with creative bottlenecks? We can help.

Faster creative is a productivity problem. No, wait. It’s a decision problem.

You can crank out 100 ads a month and learn nothing if each one is opinion dressed up as art. What actually wins is high decision density — more meaningful learnings per dollar spent.

Decision density = insights gained / ad spend

Here’s how to crank that number up fast:

1️⃣ Start with a single hypothesis  
↳ Know exactly what you want to prove. Hook, offer, or audience. Not all three.

2️⃣ One change per variant  
↳ Swap only the headline, or the thumbnail, or the CTA. If it wins, you know why.

3️⃣ Run 48-hour sprints, not month-long marathons  
↳ Fast early signals beat polished stagnation. Iterate daily, not weekly.

4️⃣ Use modular templates and pre-approved palettes  
↳ Swap copy and product shots in seconds. Cut feedback rounds to near zero.

5️⃣ Always log the takeaway, not just the winner  
↳ “This hook beat control by 18% — because it framed X.” Record it. Reuse it.

Controversial take: perfect creative is a marketing hobby. Testing is a business function. If your process worships polish over proof, you are funding your competitors’ experiments.

Want a ready-made 48-hour creative sprint template? Like, follow, and repost ♻️ — I’ll share the playbook.

Controversial take: hiring more creatives is not the fastest path to better ad performance.

What wins is importing the right creative playbooks from outside your category.

Here’s how top agencies actually scale performance by stealing ideas, not headcount:

1️⃣ Hunt outside your lane  
→ Political micro-targeting, mobile game UA, retail window design. Each has one repeatable superpower you can steal.

2️⃣ Translate playbooks into hooks, not assets  
→ Don’t copy visuals. Convert the tactic into a 3-word hook + pre-story + testable angle. Hooks drive the algorithm. Design amplifies them.

3️⃣ Run cultural experiments in controlled batches  
→ 5–7 variations per playbook. Learn fast, document the rule, then scale what changes user quality, not just CPA.

4️⃣ Price the import, measure the lift  
→ Charge a Creative Import Fee: scouting + translation + sequencing. Benchmarks should be LTV uplift, retention, and funnel quality, not just day-1 CPA.

Why this works: outside playbooks change who clicks. That changes who stays. Changing audience quality compounds revenue more than shaving a few cents off CPA.

If your agency growth plan is "hire 5 more creatives," you are scaling costs. If it is "import 3 new attention systems this quarter," you are scaling advantage.

Found this useful? Like, follow, and repost ♻️ so others can too!

ps. Need help importing a playbook? We help agencies do exactly this.

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Bill Stathopoulos

Luis Camacho

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The Battle

Bill Stathopoulos

Luis Camacho

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

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