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

Performance creative infrastructure that helps paid acquisition teams produce, test, and scale ads.⚡️

👋 Hi, I’m Luis Camacho, Founder @ GetAds (getads.co)

We help brands and agencies scale paid acquisition by building creative infrastructure that supports ongoing iteration, testing, and throughput. GetAds is a structured creative production system designed for teams where creative output directly impacts performance.

Our team works exclusively on ad creative. Static, video, UGC, and AI-assisted formats, all built for paid media workflows. The focus is not one-off assets, but consistent creative velocity without the friction of hiring, freelancers, or traditional agencies.

We support brands and agencies across a wide range of industries and business models, from DTC and CPG to B2B services, fintech, biotech, and mental health. If you are running paid ads seriously and creative has become a bottleneck, that is where we tend to be the best fit.

A few words from teams we work with:

“After spending a lot of time and money trying to solve our agency’s creative output problem, GetAds stood out. The quality is consistently high and the system makes it easy to keep creative moving.” - Mike W. ⭐️⭐️⭐️⭐️⭐️

“As an agency owner, having a reliable creative production system matters more than anything. GetAds has become a core part of how we support clients.” - Carlos C. ⭐️⭐️⭐️⭐️⭐️

“GetAds feels deeply integrated into our workflow. The Slack collaboration and consistency over time has made a big difference.” - Jake S. ⭐️⭐️⭐️⭐️⭐️

“We rely on GetAds for B2B creative graphics and video that fit real paid media use cases.” - Josh L. ⭐️⭐️⭐️⭐️⭐️

Side note. Our newest product helps media buyers and creative teams organize, collaborate, and save ad inspiration in one place. If you want to streamline your ad creative workflow, you can sign up for free at getads.co/app.

Want to chat? Shoot me a DM 🙂

Luis Camacho

We ran an experiment: AI spit out 2,300 ad variations in 48 hours. CPAs fell. Repeat purchases dropped 17% in 90 days.

AI can crank volume faster than any human team. It cannot, by itself, protect what makes a brand worth coming back to.

Here’s the ugly truth most agencies won’t say out loud:
AI optimizes for short-term attention patterns. It converges toward platform-safe tropes. Over time that flattens your distinctiveness and erodes brand equity. You win a lot of clicks and lose a little of your future customers every day.

If you care about longevity, humans still must close the loop. Three irreplaceable roles designers play:

1️⃣ The Curator  
↳ Pick the unusual, not the average. Keep distinct signals that humans remember.

2️⃣ The Goldsmith  
↳ Polish AI output into craft. Typography, pacing, tone, compositional decisions matter more than ever.

3️⃣ The Brand Steward  
↳ Protect long-term metrics - repurchase, referral, perception - not just CPA.

How to make this practical:
• Use AI for scale and hypothesis generation  
• Route top candidates to designers for refinement and distinctiveness testing  
• Measure beyond CPA - track retention, NPS, creative uniqueness over time

If you let a stack own your identity, you’ll get efficient and forgettable. Treat AI like a factory - fast, cheap, noisy. Let humans turn the noisy stuff into something people remember.

Found this useful? Like, follow, and repost ♻️

ps. Need a system that pairs AI volume with designer stewardship? We help brands do exactly that.

Unpopular take: Templates are the single biggest thing quietly tanking your ROAS right now.

Yes, they save time. No, they do not scale performance.

Here’s why templated ads are actively hurting your brand and ad results:

1️⃣ They train the wrong algorithmic signal  
↳ When 80% of your creatives look the same, the platform learns “this brand = low novelty.” Delivery drops. You’re competing on sameness, not relevance.

2️⃣ They attract cheap, low-LTV buyers  
↳ Templates optimize for clicks and familiarity. That brings deal-seekers, not loyal customers. Same CPA, wildly different day-90 LTV.

3️⃣ They create false learning  
↳ Templates limit directional insights. When everything looks similar, you can’t tell which hook, story, or persona actually moves the needle.

4️⃣ They erode your brand muscle  
↳ Designers stop experimenting. Strategists stop testing bold ideas. Over time your creative IQ atrophies and you can’t recover quickly.

What to do instead (fast wins):

• Write the headline before the mockup. Copy forces clarity.  
• Build 5 persona-specific variants, not 1 universal template.  
• Vary signal-level elements: hook, framing, lighting, CTA — small tweaks compound.  
• Measure cohorts, not just CPAs. Track LTV and retention by creative.

If you want cheaper clicks or prettier templates, keep templating. If you want a brand that scales profitably, stop being addicted to one-size-fits-all creative.

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

ps. struggling with creative bottlenecks? We can help.

Stop putting shiny 5-star blurbs in your ads. They’re killing resonance.

Here’s the real secret most brands ignore: the reviews that convert are not the ones that praise you perfectly. They are the ones that argue with you.

Why the messy reviews win in paid acquisition:


1️⃣ Contain built-in objections

↳ 3 and 4-star reviews surface doubts in the customer’s own words. Use those words to pre-handle objections in creative and watch CTR + quality increase.


2️⃣ Reveal true hooks, not marketing speak

↳ Customers describe outcomes in ways you would never write. Copy those exact phrases into headlines and captions for instant resonance.


3️⃣ Power sequence-based journeys

↳ Run a skeptical review as your first touch, an explainer as your second, and a 5-star as the close. The algorithm learns a believable path, not a single “hero” ad.


4️⃣ Scale micro-personas fast

↳ Tag reviews by theme - convenience, durability, results - then build 5-7 quick variants per theme and map to audiences. Small library. Big variety.


How to implement in 72 hours:


• Export reviews and cluster by theme

• Pull 6-8 verbatim lines per theme for hooks

• Build 5–7 creatives per theme (skeptic → product → proof)

• Feed into dynamic creative + run in controlled batches


Controversial but true: polished praise sells to people who already trust you. The noisy, imperfect reviews sell to the rest.

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

ps. struggling with creative bottlenecks? We can help.

AI will make ads cheaper. It won’t make brands cheaper.

Here’s the uncomfortable truth: the algorithm rewards predictability. It loves patterns. It learns your ad language and then amplifies what’s easiest to classify. That’s great for scale. Terrible for brand resilience.

If you want a brand that survives AI-era advertising, stop optimizing solely for what the model likes. Build for what the human remembers.

Introducing the Brand Immunity Stack — a playbook for resilient brands:

1️⃣ Identity Anchors  
↳ Pick 3 repeatable brand motifs (toneline, visual tag, confession script). Remix them across formats so people remember you even when the algorithm forgets.

2️⃣ Controlled Unpredictability (Shock Loops)  
↳ Run small, low-budget tests that intentionally break your pattern. Different voice, weird visual, unexpected CTA. These force the model to learn new user-brand matches and prevent creative overfitting.

3️⃣ Journey Signals, Not Single Ads  
↳ Design sequences people can follow. Teach the algorithm through paths: tease → teach → prove → convert. The system will stitch the journey only if you supply varied touchpoints.

4️⃣ Owned Narrative Data  
↳ Capture micro-conversions (video watches, micro-form fills, DMs). Build first-party signals the AI can’t borrow from competitors.

Controversial take: scaling only your “winner” creative is the fastest way to make your brand irrelevant long-term.

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

ps. struggling with creative bottlenecks? We can help.

Killing an ad after 48 hours is not decisive. It’s careless.

Too many teams axe creative before they’ve run the proper diagnostics. Before you bury a “loser,” run this pre-execution checklist to avoid throwing away a potential winner.

1️⃣ Is it past the learning slope?
↳ If the ad hasn't moved through the algorithm's 72-96 hour adjustment window with stable budget signals, it’s still learning.

2️⃣ Placement parachute test
↳ Run the creative across 3 placements (Reels, Feed, Stories). If it flops everywhere, it’s offer or audience. If it wins on one, scale that placement.

3️⃣ Creative correlation heatcheck
↳ If multiple creatives fail simultaneously across the same audience, the problem is audience or timing, not the visual.

4️⃣ Micro-conversion signal
↳ Low purchases but rising add-to-carts, link clicks, or view-throughs? The ad is qualifying traffic. Fix the offer or landing experience, don’t kill the creative.

5️⃣ Frequency vs fatigue
↳ Frequency >3 with falling CTR is fatigue. But low frequency with low CTR is an attention problem. Fix cadence first.

6️⃣ Audience overlap audit
↳ High overlap causes internal cannibalization. Segment your audiences before scrapping assets.

7️⃣ Quick resurrection test
↳ Move the creative into a fresh audience for 48 hours. If performance improves, you just found a new angle, not a dud.

Killing creatives is easy. Deciding strategically takes discipline.

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

ps. struggling with creative bottlenecks? We can help.

Stop hiding unhappy customers. Start running ads with them.

Real customer moments — the raw unfiltered videos, angry comments, confused DMs — are your most efficient performance creative. Positive moments convert. Negative moments qualify.

Here’s how to use them, bluntly and systematically:

1️⃣ Capture the moment
↳ UGC, customer service clips, voice notes. Capture sentiment, platform, persona. Store with metadata.

2️⃣ Reframe, don’t fake
↳ Edit to add context, then pair with your solution. Example: “It leaked once. Here’s why it won’t again.” Honesty + fix = trust.

3️⃣ Run polarity tests
↳ Same story, two endings: positive outcome vs tough truth. Measure CPA, CTR, and 30-day LTV. Negative-first ads often reduce returns and increase LTV.

4️⃣ Use complaints to pre-qualify
↳ Put limitations in creative. “Not for heavy daily runners” filters deal-seekers and attracts ideal buyers.

5️⃣ Build permission loops
↳ Reply publicly, then turn the exchange into a testimonial ad. Shows you listen and iteratively improve.

Why this works
→ Raw moments prove you’re real. Algorithms love authenticity. Customers prefer vetted expectations over polished promises.

Controversial take: polished perfection sells once. Imperfect truth builds a sustainable business.

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

ps. Want a system that captures and tests customer moments at scale? We build those.

Stop A/B testing your brand into extinction.

Performance teams often chop up brand cues to chase clicks. That makes your ads easy to ignore and impossible for the algorithm to stitch into a coherent journey.

Here’s why maintaining brand integrity in performance creatives is not optional — it’s strategic:

1️⃣ Brand fingerprints give the algo anchors  
↳ Consistent micro-elements - color, logo lockup, VO cadence - let Meta sequence your ads into a narrative, not random shots.

2️⃣ Cohesiveness pre-qualifies better customers  
↳ On-brand creative attracts buyers who resonate with your values. Same CPA, higher LTV. Your first ad is the filter, not just the traffic driver.

3️⃣ Generic creative creates noise, not signal  
↳ When every ad looks like every other ad, the system struggles to learn who your real audience is. Volume without identity = waste.

4️⃣ A practical allocation that actually scales  
↳ Keep 60% of your creative library on-brand templates. Use the remaining 40% to test hooks, formats, and placement-specific variants. That balance trains both humans and machines.

5️⃣ Quick micro-checklist to protect your brand  
↳ Primary color, logo position, tone of voice, opening beat, end frame offer. Lock these for on-brand assets.

Controversial take: chasing short-term clicks by making everything anonymous is the fastest route to long-term decline.

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

ps. struggling with creative bottlenecks? We can help.

Stop outsourcing creative. Start plugging it in like infrastructure.

Here’s the mindset shift most brands miss: a creative partner shouldn’t be a vendor you brief. They should be a plug-and-play microservice you wire into your ad stack.

Do this and your ad performance improves not because of one hero ad, but because your account finally gets consistent, testable inputs.

How to set it up:

1️⃣ Reserve capacity, not a project  
↳ Buy a weekly output SLA: X hooks, Y cuts, Z native formats. Predictable volume beats sporadic perfection.

2️⃣ Ship templates, not one-offs  
↳ Build 6 modular layouts (hook, pre-story, intro, close). Remix faster than you pause.

3️⃣ Version control your creative  
↳ Give every asset an ID + experiment tag. Measurement stops being guesswork and becomes repeatable.

4️⃣ Force mini-release cycles  
↳ 5–7 variations every week. Launch, learn, iterate. Stop waiting for the perfect hero.

5️⃣ Contract the learning loop  
↳ Partner owns documentation: what worked, why, next hypotheses. If they don’t deliver insights, fire them.

Real result: when we switched a DTC client to this model they moved from 4 creatives/month to 20/week and saw predictable CPA gains within 6 weeks.

If your creative partner still treats work like a one-off deliverable, you’re paying for chaos.

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

ps. struggling with creative bottlenecks? We help brands build plug-and-play creative systems.

If your ad library is 80% AI-perfect assets, you’re not scalable. You’re fragile.

Here’s the unpopular truth:
AI makes pretty things. Authentic content makes repeatable winners.

Why real UGC beats synthetic every time:
1️⃣ Human signals matter more than polish  
↳ Micro-expressions, background noise, and awkward cuts signal "real" to both humans and algorithms. Those cues improve attention and retention.

2️⃣ Trust compounds LTV, not clicks  
↳ AI assets get clicks. Real stories get repeat buyers and referrals.

3️⃣ Algorithms prefer messy context, not flawless photos  
↳ Modern models reward diverse, native-feeling journeys. Synthetic sameness gets deprioritized.

No UGC from customers? Steal it legally. Here’s how to source authenticity from unexpected places:

1️⃣ Map the emotional trigger you need - fear, relief, pride.  
2️⃣ Search subreddits, product forums, TikTok comments with that emotion + situation. Example search: "sleep deprived" + "newborn" in Reddit.  
3️⃣ Pull posts that match. Look for timestamps, real names, unedited photos. Those are authenticity signals.  
4️⃣ License with a simple DM: "Love your post. Can we feature it in an ad? We pay $250 and credit you." Use sliding scale for creators.  
5️⃣ Edit lightly - keep audio breaths, shaky cam, text overlays. Preserve the native feel.  
6️⃣ If no posts exist, manufacture authenticity: seed 10 micro creators with samples, ask for unscripted day-in-life clips, run a one-question survey and turn answers into short reels.

Controversial take: AI is not the enemy. It is the excuse marketers use to avoid sourcing humans. Stop automating humanity out of your funnel.

Want a quick playbook for scraping authentic signals from Reddit and TikTok comments? Like, follow, and repost ♻️ so others can too!

ps. struggling to scale genuine UGC? We help.

As a creative partner for DTC brands, we see brands underinvest in catalog creative all the time.

This is a big step toward making catalog ads actually look and perform like real ads.

Gen AI works for one-off ads, but is unusable for product catalogs / DPA.

Ecom brands:
- Have hundreds of SKUs
- Are spending 50%+ ad spend on DPA
- Have no time

They’re being left behind. Until now.

Introducing, Generative Catalogs: redesign your entire product catalog and DPA in minutes.

Re-shooting all your SKUs is nearly impossible.

Optimizing your catalog ads is tough.

Now, do it all with the best AI.

- Pick your favorite AI model
- Write a prompt (put it on a model, on the beach, etc)
- Apply to every SKU

We’re pairing this with an irresponsible offer..

For the next week, any accounts that test this feature will receive UNLIMITED PREVIEWS for FREE.

➡️ Pick any prompts you like from our expansive prompt library (or write your own)
➡️ Apply to preview it on your catalog
➡️ Share the magic with your team

For FREE.

> Easily try out new designs.
> QA them to filter out slop.
> Launch and test as DPA on every platform.

Oh, and we have free built-in feed management (meaning you can ditch Feedonomics for free).

The world's best ecom brands and retailers are already using Marpipe to design and scale their catalog creative. 

Comfrt, Ridge, Kate Spade, True Classic, Mejuri - over 7,000 have already signed up.

Free to try, only pay if you like it.

What are you waiting for?

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