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.

This is the exact stack we're relying on to get us to $6M ARR. 
After working with 70+ GTM teams, testing 125+ tools, here is what stayed.

To get from $0 to $3M we ran a much bigger stack.
It worked, but the tools got better and we got smarter about what we actually needed.

So we simplified our stack.

This is what stayed, organized by job to be done:

0. The Engine

→ Clay: data orchestration. Every source plugs in, every workflow runs through it
→ n8n: where our agents live and automations run 
→ Claude: research, intelligence, copy

1. Finding the right accounts 

→ Apollo: targeted lists 
→ LinkedIn Sales Navigator: full stakeholder mapping 
→ Ocean.io: lookalike companies once you've nailed an ICP

2. Capturing buying intent

→ RB2B: identifies warm website visitors
→ Trigify.io: catches LinkedIn engagement signals before your competitors do 
→ Common Room: monitors your CRM accounts and flags when it's time to reach out

3. Getting clean contact data

→ FullEnrich: phone + email waterfall 
→ Prospeo: fills the gaps for specific cases 
→ ZeroBounce: validate before you hit send

4. Personalizing at scale

→ Claygent: account research on autopilot 
→ Twain / Octave: purpose-built copy tools for teams that want alternatives

5. Reaching out
 
→ lemlist: best multichannel 
→ HeyReach.io: LinkedIn DMs at scale, zero bans 
→ Instantly.ai: cold email with warmup + rotation built in 
→ Salesfinity: cold calling that actually books meetings

6. Closing and tracking
 
→ HubSpot: still the best CRM if you use it right 
→ Attio: our recommendation for teams under 50 
→ Qwilr: proposals that move deals forward async 
→ Sybill/ Claap so reps spend time selling, not taking notes

That's 23 tools across 6 layers.

The catch is: you don't need all of them.

We run this many because we work across 70+ clients, different industries, different ICPs, different motions that are built for their specific case.
(What works for a PLG SaaS won't work for an enterprise services firm.)

But the logic behind every tool is the same:
Signal → Enrich → Personalize → Reach out → Close → Learn
Each tool has one main job, each job feeds the next.

What's the one tool you'd never cut? 👀

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

We're building toward $6M ARR, 
Signal-led outbound is the bet... Here's every signal worth tracking in 2026 👇
 
🟢 1st Party (The signals you have, nobody else has access to this)

- Website Visitors:
RB2B
Midbound
Warmly,

- Product Usage
Common Room
Pocus

- LinkedIn Signals
Trigify.io
Clay
Expandi

- CRM Data
HubSpot
Close
Attio

- Call Transcripts
Fathom.ai
Attention
Claap
 
🔵 2nd Party (these are shared by your ecosystem: from partners, platforms, and communities your buyers are already part of)

- Champion Tracking
Clay
UserGems 💎
Unify

- Ad Engagement
ZenABM
Fibbler

- Affinity Signals
Crossbeam
The Swarm

- Review Sites
G2
Capterra
 
🟡 3rd Party (These are inferred from public data, it's everything happening in the market.)

- Job Openings
Clay
PredictLeads
LoneScale

Funding
Crunchbase
PitchBook
Clay

Technographic
BuiltWith
HG Insights
Clay

Custom Scraping
Apify
Claygent
Firecrawl

Firmographic Data
BetterContact 
Apollo
Clearbit
Clay
 
P.S. We turned everything we learned into "The Intent Signals Playbook".
26 pages, every signal type, every tool, and every workflow.

Comment SIGNALS and I'll send it over.

search-magic

salescaptainio

scicord-llc

pixofix

madbold

$45+ Billion in GTM software valuations, from just 9 tools on this map!!
There are 80+ on here!

(And most weren't built in Silicon Valley.)
 
V2 of the 🌍 Global GTM Map is here.

After dropping the first GTM map last week,
the comments became a map of their own.
Founders and GTM operators tagging tools, adding countries, calling out what I missed.

So I updated it.
 
+20 New tools, +3 new countries, same mission:
Showing that GTM is now a global movement.
 
A few things that you can see from the map:

→ There is a concentration of tools in France, UK and Estonia
→ France is leading enrichment
→ Estonia coming strong in email outreach
→ The US still leads on signals and intent
→ The UK is dominating AI video & voice
→ Bulgaria, Canada, and Ireland just joined the map
 
The tools that got the most love in the comments:

🇺🇸 Clay
🇫🇷 FullEnrich 
🇫🇷 lemlist
🇪🇪 Instantly.ai
🇲🇰 HeyReach.io
🇺🇸 RB2B 
🇬🇧 Synthesia
🇬🇧 Attio
🇺🇸 Zapier 
🇩🇪 n8n

New additions include:
🇺🇸 Lovable 
🇫🇷 Claap 
🇧🇬 clearcue.ai
🇨🇦 EmailBison
🇮🇪 Trigger.dev
🇺🇸 Chili Piper
🇺🇸 Artisan
🇺🇸 Calendly
🇳🇱 Signalbase
 
What's the best GTM tool from your country that didn't make the map?

Claude Code went from $0 to $2.5B in under a year!
We spent 3 months figuring out how a GTM team should use it. Here's everything we found..
 
LinkedIn is giving you FOMO about Claude Code,
but nobody is explaining how it actually fits into GTM.
 
We built the playbook that answers that.
 
Whether you're an AI expert or this is the first time you hear about Claude,
this resource has everything you need to get started, like:
 
1️⃣ Setup in 10 minutes, no dev background needed
2️⃣ Your first win in 60 minutes, copy paste prompts included
3️⃣ 12 playbooks every GTM team should build first
4️⃣ The full 8-step outbound campaign pipeline
5️⃣ CLAUDE.md templates by GTM motion
6️⃣ 25 workflows by GTM role, SDR, AE, Marketing, RevOps, CS
7️⃣ What NOT to automate, and the readiness checklist
 
Every workflow in it is running in production today.
 
We gave early access to our newsletter subscribers, the response was overwhelming.
Now we're making it public, for free.
 
Comment CLAUDE and I'll send it over.

100+ hours tracking LinkedIn feeds.
These are the 50 GTM voices worth your attention in 2026.
 
These are the people moving the needle in GTM right now.
Sharing frameworks you can steal on a Monday morning.
Building and leading the companies defining how B2B revenue is won in 2026.
 
A few highlights 👇

Kyle Coleman: redefining how AI should actually plug into your sales motion, not just your copy.

Chris Walker: the person who was right about the dark funnel before the rest of the market caught up.

Kyle Poyar: if you touch pricing or PLG, his Growth Unhinged newsletter is the closest thing to a cheat code that exists.

Adam Robinson: bootstrapped RB2B to $7.5M ARR by turning building in public into a real distribution engine.

Andrei Zinkevich and Emilia Korczynska: the most consistently rigorous ABM thinkers posting on LinkedIn.

Plus top voices from Clay, lemlist, Salesforge.ai 🔥and others.
 
I'm on the list too 😎 I share what we're learning at SalesCaptain in real time: the workflows we run, the outbound playbooks that actually convert, what's working in GTM right now and what isn't.
If any of this is useful → hit Follow, I post 4-5 times every week.
 
Full list in the creative,
Everyone else tagged in the comments 👇

Clay hit $100M+ ARR without a traditional sales army.
Because Clay's best customer is Clay.
 
They use their own product to run their entire GTM, and it helped them scale to $100M ARR and a $5B valuation, serving 15,000+ customers including OpenAI, Canva, and Google.
 
This Thursday, at 🇬🇧 Clay Club London, Clay's Co-Founder Varun Anand is breaking down the actual operating model.

You’ll see:
- How Clay uses Clay internally
- How website intent becomes outbound action
- How workflows replace manual prospecting
- What stays human, and what doesn’t
 
Plus:
Yash Tekriwal 🤔 is walking through Clay’s internal education and enablement engine.
lemlist and Dealfront are joining the operator roundtable.

And I’ll be doing a live breakdown of how we build signal-driven GTM systems for clients right now.

Real workflows + open Q&A.

If you're in London, you don't want to miss the insights (and the people) in this room.

Registration link is in the first comment.

See you there 🔥 😎

undefined undefined

"Should I just use Claude Code instead of Clay?"
"What about n8n or Make?" ,"Do I even need Zapier anymore?"

We get these questions every week across 70+ clients. 
The confusion is understandable. 
Here's the answer nobody's giving you.

You don't need all 5 of these tools. 
You need to know what each one does, pick the ones that match your stage, your team, and your budget.

1. Claude Code

✅ Calls any API, writes and runs its own scripts 
✅ Replaces tasks that used to need a developer 
✅ Cheapest of the five ($20/mo base)

❌ Your code and prompts go to Anthropic's servers (data privacy concern) 
❌ No visual interface (non-technical will have a steep learning curve) 
❌ Needs deployment setup to run autonomously 
❌ Cost spikes with heavy API usage

Best for: Scale stage teams ready to automate custom workflows

2. Clay

✅ Best B2B enrichment on the market (waterfall 15+ providers) 
✅ Visual, non-technical friendly
✅ Native AI built in (Claude, GPT, Gemini)

❌ Won't run on its own  
❌ Credits stack up fast at high volume

Best for: Any stage, the GTM tool most teams start with

3. n8n

✅ Runs 24/7 autonomously 
✅ Self-hosted = zero per-op cost
✅ Full logic control, AI agent nodes built in

❌ Steep learning curve 
❌ Every API update = manual fix on your end 
❌ Managing 20+ client instances needs a dedicated person

Best for: Scale stage (only with a dedicated GTM engineer)

4. Make 
✅ Visual drag-and-drop, no code needed 
✅ Affordable entry point ($9/mo) 
✅ Runs 24/7

❌ Hits its ceiling fast on complex logic 
❌ Not built for serious GTM engineering at scale

Best for: Growth stage teams who need automation without hiring a developer

5. Zapier 

✅ Easiest to set up 
✅ 6,000+ integrations 
✅ every team already knows it

❌ Most expensive at scale 
❌ Not built for complex GTM logic (you'll outgrow it fast)

Best for: Early stage, or simple triggers at any stage

The clients who get this right early save 3-6 months of rebuilding. 
The ones who don't always come back saying they wish they'd started smaller.


Which of these are you currently running?

40% of our outbound now runs on Claude Code.
Here are the 25 workflows making it happen, broken down by role.
 
👨‍💼 SDR / Business Development

1. Signal-triggered outbound
2. LinkedIn engagement scraping
3. Job-change tracking
4. Competitor evaluation targeting
5. Influencer outreach automation
 
💼 Account Executive

6. Meeting prep brief
7. BANT call analysis
8. Recovery email after tough calls
9. Buying committee mapping
10. Deal intelligence from transcripts
 
🤳 Marketing

11. LinkedIn ads via API
12. Content-to-pipeline workflow
13. SEO content pipeline
14. Win-loss messaging analysis
15. Sales calls to content
16. Event attendee outreach
 
💰 RevOps

17. Pipeline forecast check
18. Custom signal enrichment
19. Positive reply routing
20. Weekly pipeline digest
21. Lead magnet follow-up automation
 
🤝 Customer Success

22. Champion departure response
23. Renewal intelligence
24. QBR preparation
25. Account health scoring
 
These workflows are built on:

Claude Code 
Clay
Apollo
HubSpot
HeyReach
lemlist
Instantly.ai
RB2B 
Fathom.ai
Slack
n8n
 
We documented all 25 in detail in the Claude Code GTM Playbook, exact prompts, setup steps, tools and 30-day plan for using Claude Code in GTM included.

Comment CLAUDE and I'll send it over. 👇

25 Claude code Workflows for GTM teams

Here's the full ABM stack we're using to hit $6M ARR
200+ ABM campaigns taught us which tools actually matter. 

P.S. The top 1% GTM teams in 2026 are running seven layers, the rest 99% run only three.

1. Intent Signals
Unify
Bombora
Common Room
 
2. LinkedIn Ads & Tracking
ZenABM
Fibbler
LinkedIn Campaign Manager
 
3. Website Visitors
RB2B
Midbound
Warmly,

4. Data Orchestration
Clay
Apollo
Sales Navigator

5. Outreach
Instantly.ai
lemlist
Salesforge.ai 🔥
HeyReach.io
 
6. AI Layer
Claude
Claygent

7. CRM & Ops
HubSpot
n8n
Zapier
 
💡 One tip we learned after 200+ campaigns:
The main reason ABM fails is because you're reaching one person at a company, not the buying committee. 
Fix your contact coverage first.
(Match rates went from 40% to 80%+ for our clients when we did 🔥)
 
What's the one layer missing from your current ABM stack?

We analysed 6,000+ signals across 200+ B2B campaigns.
These 9 generated $2M+ in pipeline.
The rest were just noise.

Last month we ran a webinar with lemlist about signals, 1,200 people showed up.
Most of them had the tools, Clay, RB2B, Bombora... you name it.

They all had signals,
But almost none had a system for what to do with the signals.

They had the tools, not the playbook.
So we wrote it for you.

A comprehensive resource (9 chapters) on:

→How to find the signals UNIQUE to your business (that your competitors don't have)

→ How to prioritize the accounts they surface (the exact scoring matrix) 

→ What to do at every stage: TOFU, MOFU, BOFU 

→ What to say when a signal fires (the AI personalization framework) 

→ 17 signal types + the full GTM tech stack to run it all

Everything we use at SalesCaptain and across 70+ clients
Nothing held back.

Comment SIGNALS and I'll send it over.

We used these 7 signals to generate 20+ meetings/month and $1M+ in pipeline, ONLY from LinkedIn.
Here are the signals, the steps and the tools we used:
 
1. LinkedIn Ad Engagers → They engaged with your ad but never clicked. Capture, enrich, reach out.

2. LinkedIn Harvesting → 3+ engagements from the same person. 
Auto-DM + follow-up email.

3. Event Attendees → New events in your space every Monday. 
Find who's attending first.

4. Keyword Engagers → Someone posts about the exact problem you solve. 
You show up.

5. Followers Outreach → They followed your page. Enrich, classify, personalize, reach out.

6. Competitor Followers → Already in the market. 
The warmest outreach you'll ever run.

7. Decision Maker Connect → Meeting booked → full buying committee found → connected before the call. (This one alone changed how we close deals)
 
Most reps are waiting for prospects to raise their hand.
These workflows find them the moment they show intent, before they even know they need you.
 
Tools used across all 7:

LinkedIn
Clay
HeyReach.io
lemlist
Trigify.io
Common Room
PhantomBuster
HubSpot
ZenABM
Instantly.ai
Calendly
 
Workflow 06 is the one most people skip because it feels too aggressive. It's also the one I'd start with.

Which one are you running? 👀

7 LinkedIn workflows that generated $1M in pipeline

HeyReach just got banned by LinkedIn ❌ 
We've run 200+ campaigns with them. Here's my opinion 👇

Of all the LinkedIn tools out there, HeyReach was one of the most careful.

They respected rate limits.
They built for safety.
They did everything right
... and they still got banned.

Which means no one is safe.
Because this isn't about compliance.
 
LinkedIn is playing a different game entirely.
Every tool that monetizes their data better than they do is a target.

Automation tools first.
Then enrichment.
Then analytics.
 
LinkedIn is closing the loop, slowly, then all at once.
Worth noting, existing campaigns are still running, users are not affected.
 
The right question to ask isn't "which tool do I switch to?"
It's: 
"How much of my GTM is built on a platform that can pull the plug overnight?"
 
Curious what others are thinking here.

Clay just dropped a major pricing update (March 2026)🆘
Here's who benefits, who should pay attention, and what most people missed.
 
🟢 BIG WINNERS

→ Teams doing heavy enrichment with Clay's marketplace 
Data costs just dropped 50–90%.
Your budget goes a lot further from day one.
 
→ Teams that wanted CRM + Web Intent but couldn't justify $800/mo
Those features now unlock at $495/mo on the Growth plan.
That's the biggest access shift in this update.
 
→ Heavy Claygent users Clay says 85% of AI users will pay less.
Frontier models now pass through at cost, zero markup.
 
🟡 WATCH OUT

→ Pro plan users running workflows on your own API keys 
Three things to know:
 
1️⃣ You may see a price increase, Clay admitted the old Pro plan was mispriced

2️⃣ Using your own API keys DOES consume Actions, this is the detail most posts are missing.

3️⃣ Even a single HTTP API call to your own database now requires the $495 Growth plan

→ Heavy credit users (70K–100K credits/month)

One user publicly shared their math:
Currently paying ~$1,500/mo.
To maintain the same volume on new plans → $3,500–5,000.
If you're in that range, model this out before you switch.
 
→ Solo GTM engineers and individuals

Clay essentially coined the GTM Engineer role.
But higher fixed costs raise the barrier for people just getting started.
Worth flagging honestly.
 
→ Anyone assuming Actions = Credits
They're not.
Actions measure platform work, 1 action per task, regardless of data spend.

The good news: 90% of customers will never hit their limit.
 
What does NOT consume Actions: Lookups, CRM imports, webhook imports, CSV exports.
 
🔵 THE BIGGER PICTURE
 
Clay is separating what the platform does from what the data costs.

For GTM teams, that clarity matters, and it sets them up to charge properly for the orchestration features coming next.
 
Across the 70+ clients we run GTM for, 
the teams that will feel this most are the ones doing serious enrichment work inside Clay, and for them, this is a genuine win 🏆 
 
Clay also publicly said this will cost them 10% in revenue short term.
That's not a company optimizing for quarterly numbers, that's a bet on the right model winning.
 
If you've been sitting on the fence because the credit model felt unclear, this changes that.
 
On a legacy plan?
You have until April 10 to decide.
You can stay exactly where you are. No forced migration.
 
Where are you right now with Clay? 👀

- Heavy user evaluating the change
- Considering Clay for the first time
- Confused about Actions specifically

Drop it in the comments, happy to help if I can.


*image via Everett Berry.

We went from $0 to $3M ARR using cold email.
The tools that got us there? Half of them don't exist in our stack anymore.

It's not because they're bad tools, but because the market moved.
 
Cold email in 2026 looks nothing like 2022, here are 10 differences:
 
1️⃣ Sending moved from basic sequencers to multichannel-first tools Instantly.ai lemlist

2️⃣ Data moved from static databases to waterfall enrichment 
Clay

3️⃣ Validation moved from manual to automated 
ZeroBounce

4️⃣ Personalization moved from Mail Merge to AI at 1:1 scale 
Clay Claude

5️⃣ LinkedIn moved from manual outreach to 30 profiles running simultaneously HeyReach.io

6️⃣ Email only outreach is replaced by Multichannel Email + LinkedIn + WhatsApp + Calls 
lemlist

7️⃣ Automation moved from Zapier clicks to plain English workflows 
n8n Claude Code

8️⃣ Deliverability moved from guessing to knowing before you send 
GlockApps Folderly Inc.

9️⃣ AI research moved from hours to minutes 
Claude Claygent

🔟 Infra moved from 1 domain to 10+ minimum 
Mailforge - Cold Email Infrastructure 📈
 
We're building toward $6M ARR.
The modern stack in this image is part of what we're betting on.
Share it with your network 🔁 
 
P.S. We put together SalesCaptain's full "Cold Email Playbook" (infrastructure, sequencer setup, drafting emails, stack...etc the whole thing) 
Comment COLD and I'll send it over.

Bad email infra costs the average GTM team $2,000+/month in wasted tools.
Here's what you actually need at every budget level.
 
💰 $500 Stack 
For solo founders and new GTM teams testing cold email. 
Goal: Test messaging fast + keep reputation intact.

Inbox Provider: 
Gmail
Outlook 

Sending:
Instantly.ai
Smartlead 

Warm-up:
Built-in (both) 

Verification:
ZeroBounce
Bouncer 

Health Monitoring: 
GlockApps
Instantly.ai reports 

AI Personalization:
Claude 

Automation:
Zapier 

Domain Setup:
Namecheap + Cloudflare

⚙️ $1K Stack 
For growing teams running consistent outbound and early multichannel. 
Goal: Stable inboxing + visibility into what's working.

Inbox Provider:
Mailforge - Cold Email Infrastructure 📈
Zapmail.ai 

Sending:
lemlist 
Salesforge.ai 🔥

Warm-up:
Mailforge Warm
Clay Signals 

Verification:
NeverBounce by ZoomInfo
ZeroBounce 

Health Monitoring:
MailReach
Mailsuite 

AI Personalization :
Claude
Claygent 

Automation:
n8n

🚀 $5K Stack 
For GTM teams sending 100K+ emails/month or agencies running multi-client. 
Goal: Predictable deliverability at volume, automated, monitored, CRM-connected.

Inbox Provider:
Mailreef
Inframail 
Mailscale 

Sending:
Lemlist
Outreach
Salesloft 

Warm-up:
Folderly Inc. 
Warmbox 

Verification:
ZeroBounce
MillionVerifier 

Health Monitoring:
Mailreach Premium 

AI Personalization:
Claude
Claygent
Twain 

Automation:
n8n
Clay
HubSpot CRM sync 

Reputation AI:
Mailscale active recovery
 
We mapped all three stacks into the slides above.
Swipe to see if you're overpaying for your current setup

P.S. If you want the FULL "Cold Email Playbook" Let me know in the comments below 👇

Cold email infra by budget 2026

The worst thing that can happen to your business : being INVISIBLE to your best buyers.
 
They're ready to buy,
You have no clue!
Because you don't know it's the right moment to reach out.

That's what signals fix.
 
Signals tell you who is in buying mode, right now.

Most teams use 1 or 2.
The best teams stack signals from all 3 layers simultaneously
and that's what separates 1% reply rates from 5%+.
 
Here's every signal type worth tracking in 2026 👇
 
🟢 1st Party (The signals you have, nobody else has access to this)

Website Visitors → RB2B · Midbound · Warmly,
Product Usage → Common Room · Pocus
LinkedIn Signals → Trigify.io · Clay · Expandi
CRM Data → HubSpot · Close · Attio
Call Transcripts → Fathom.ai · Attention · Claap
 
🔵 2nd Party (these are shared by your ecosystem: from partners, platforms, and communities your buyers are already part of)

Champion Tracking → Clay · UserGems 💎 · Unify
Ad Engagement → ZenABM · Fibbler
Affinity Signals → Crossbeam · The Swarm 🔆
Review Sites → G2 · Capterra
 
🟡 3rd Party (These are inferred from public data. Everything happening in the market.)

Job Openings → Clay · PredictLeads · LoneScale
Funding → Crunchbase · PitchBook · Clay
Technographic → BuiltWith · HG Insights · Clay
Custom Scraping → Apify · Claygent · Firecrawl
 
P.S. We turned everything we learned about signals into "The Intent Signals Playbook".
26 pages, every signal type, every tool, and every workflow.

Comment SIGNALS if you want to get it.

The only Signals playbook you will ever need.

https://lnkd.in/d7J3_JRR

Helping E-Commerce Brands Scale on Facebook with creative & conversion-driven strategies.

Founder of the Nomad Project, a performance marketing agency, emphasizing in paid media performance through Facebook and Google ads. My journey includes years of deep-rooted experience in e-commerce, notably leading the growth trajectory of Loop Club, culminating in its successful acquisition.

Ben Radack

How I run FB ads for an 8 figure pet device company
Full account structure breakdown:

CBO scaling campaigns (one per product line):

→ Cost cap on each CBO 
→ Ad set 1: Historical winners that have been performing long term 
→ New ad set added every month for that month's proven winners with a min spend limit 
→ As older ad sets lose steam I turn them off 
→ This keeps the campaign from getting top heavy and spending everything on 1-2 ads

ABO creative testing campaign:

→ Highest volume optimization 
→ One concept/angle per ad set 
→ 4 ads max per ad set 
→ This is where everything gets tested before it earns a spot in scaling

Whitelisting CBO campaign:

→ One ad set per page 
→ Partnership ads turned on so Meta dynamically shows the creator page, the brand page, or both together depending on what it thinks will convert 
→ Keeps creator performance separated so I know exactly which pages are working

Zombie campaign:

→ Low cost cap CBO 
→ Every failed test gets dumped in here 
→ Meta only spends when it finds a cheap conversion → You'd be surprised how many "dead" ads come back to life at a low cost cap

Primary text testing campaign:

→ Same creative, same headline, different primary text per ad set 
→ Run through Meta's A/B test tool for zero audience overlap 
→ Properly tests which copy variations actually win before I add them to my core rotation

This works because the account spends over $500k/mo.  For smaller budgets I would consolidate down to only a couple campaigns.

Media buyer & creative strategist - I help brands lower their CPA with Facebook ads

I took over an account and dropped their CPA by 74% in 2 days.​​​​​​​​​​​​​​​​

All with a SUPER simple account structure & testing strategy

Creative Testing - ABO

→ Went through their ad library (hundreds of ads)
→ Batch tested a ton of them across 5 different ad sets
→ Yes, Meta skipped a bunch, but it helped me find winners fast

Scaling Campaign - Cost Cap CBO

→ Ad set 1: All historical winners from the account
→ Ad set 2: All proven winners from December testing - min spend limit

That's it.

What was broken:

Their past team was hardly testing anything.

All the spend was going to 1 ad that was extremely fatigued.

The account had zero velocity.

The fix:

Simplify the account structure + increase testing velocity significantly.

Sometimes the best strategy is just testing more and organizing better.

You don't need 10 campaigns and complex structures.

You need clean separation between testing and scaling, and you need to actually test.

2 days in, CPA dropped 74%.

Your best performing ad might be your worst ad.

Meta is really good at finding people who are already ready to buy. These people will convert on a mid ad. It doesn't need to be great. They were already going to buy.

So you look at the data and think the ad is crushing it. But it's not the ad. It's the audience.

Try scaling it. CPA spikes. It falls apart. Because it was never a good ad. It was just shown to easy buyers.

I've seen so many accounts get stuck here. Ads that perform well but only to warm audiences. Can't scale. Can't grow.

The fix:

→ Make ads for people who don't know you yet
→ Test against cold audiences
→ If someone who has never heard of you stops scrolling, that's a scalable ad

An ad that converts warm traffic is easy. An ad that creates new demand is where the real money is.

I have a client that only runs ads through non-brand Facebook pages. And it's crushing.

No ads from the brand page at all. Everything comes from pages we created.

Here's how to set this up:

→ Create Facebook pages for your content creators (with their permission)
→ You can also create tastemaker pages based on your niche (think "Pro Sleep Tips" or "Daily Wellness Hacks")
→ Warm them up for a month. Post content etc
→ Run them in a warmup campaign at under $100/day just to build some history
→ After a month, graduate them to your testing campaign and run your top performing creative from these pages

People trust a person or a niche page way more than a brand they've never heard of.

Same ad, different page, different results.

Try it.

Batch testing 50 ads works like carving a marble block.

Here's how.

You launch 50 ads in one ad set. Meta immediately picks 1-2 to spend on. The other 48 get barely anything.

Most people stop here. They judge the 48 as losers and move on.

I don't.

→ Take the 48 ads that didn't get spend
→ Put them in a new ad set
→ Let Meta pick its favorites again
→ Pull the winners
→ Repeat with whatever's left

Each round you're chipping away at the block. Finding winners that Meta missed the first time.

Here's why this works.

I'm somewhere in the middle on trusting Meta. It's good at finding winners. When it picks 1-2 ads out of 50, those are usually solid. So the first round works in your favor.

But Meta also misses things. It makes a quick decision early on and ignores the rest. Doesn't mean those ads are bad. It means they never got a shot.

By retesting the leftovers in a fresh ad set, you're forcing Meta to look again with fresh eyes. And every round you find 1-2 more winners it would have never discovered.

→ Round 1: 50 ads, find 2 winners
→ Round 2: 48 ads, find 2 more
→ Round 3: 46 ads, find 1-2 more

You keep carving until there's nothing left worth testing.

This isn't for everyday testing. It's for when you need to find winners fast and you've got a big batch of creative to get through.

Your scaling campaign should never depend on one ad set.

I see this all the time. One ad set eating 80% of the budget. Everything looks great until those ads fatigue. Then the whole account crashes overnight because there's nothing behind it.

Here's how I prevent this:

→ Every month I launch a new ad set in my scaling CBO with that month's proven winners
→ Each ad set gets a min spend limit so Meta is forced to distribute budget across all of them
→ No single ad set is ever responsible for the majority of total spend

So when an ad set starts losing steam:

→ It's only 20-30% of your budget, not everything
→ The other ad sets are already scaled and pick up the slack
→ Performance dips instead of crashes

As older ad sets fatigue I turn them off. New ones are already running behind them.

Think of it like a rotation. You're always building the next wave of winners while the current ones are still performing. By the time they die, the replacements are already warmed up and spending.

Your account should be able to lose its top ad set tomorrow and keep moving. If it can't, you've got a structure problem.

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