Let AI do the heavy lifting for your Revenue.

Most sales teams still operate like it's 2019: manual prospecting, messy CRMs, and reps spending 80% of their time on tasks that don't make deals.Meanwhile, winning companies have built something different.They've built GTM engines. Systems where AI handles the research, the enrichment, the cleaning, the scoring, and the routing, so their team focuses on what actually builds pipeline: conversations.That's what I do.I'm the founder of TC9, where we design and build AI-powered GTM engines for B2B companies. We connect the dots between your data, your CRM, and automate the 80% that shouldn't need a human.But my work doesn't stop at execution.In my content, you'll find: → How AI is reshaping the way companies sell→ Which strategies are working right now (and which are already obsolete)→ The systems, tools, and frameworks behind modern revenue teamsIf you're a founder, VP of Sales, or revenue leader trying to figure out what the next era of GTM looks like: you're in the right place.

Jérémy Grandillon

OpenClaw hit 100,000 GitHub stars in 3 weeks.
OpenAI just hired its creator to lead their AI agent division.

Here's why every GTM team should be paying attention.

OpenClaw is an open-source AI agent that runs 24/7 on your machine. 

It connects to WhatsApp, Slack, your CRM, your email. 
Anything.

It doesn't just answer questions. It executes tasks autonomously while you sleep.

It has persistent memory, a built-in scheduler, and anything to use your entire tool stack.

ChatGPT waits for you to open a tab. 
OpenClaw checks what needs doing, and does it.

Now think about what an SDR actually does all day.

→ Research a prospect: 10 min
→ Log info into HubSpot: 5 min
→ Write a personalized email: 10 min
→ Follow up on stale deals: 15 min
→ Repeat 30x

For every hour of selling, nearly two hours go to admin, research, and data entry.

OpenClaw can already scrape a company's website, pull LinkedIn data, summarize recent news, draft personalized outreach, update your CRM, and schedule follow-ups. 

All from a single message.

This isn't replacing SDRs. It's removing the 60% of the job that never required a human.

The reps who adopt this will outperform entire teams. 
The ones who ignore it will spend their days doing work a $20/month agent handles better and faster.

Honest caveat though: it's early. 

Security researchers flagged real concerns. 
Exposed instances, prompt injection risks, etc. 

Not enterprise-ready (yet).
But the trajectory is obvious.

We're 6 to 12 months from sending one message to an AI agent: "Build me a campaign targeting Series B fintech companies in Europe." 

And it researches the companies, finds the contacts, writes the sequences, schedules the sends, monitors replies, and books meetings.

The full SDR workflow. Automated. End to end.

Sam Altman said it himself: "The future is going to be extremely multi-agent."

I'm considering installing OpenClaw, connecting it to a real GTM stack, and putting it to the test. 

Would you be interested in such an experiment? 
Let me know in the comments! 🦞

Can OpenClaw replace Sales Teams

Claude Code is becoming inevitable.

But 90% of sales and marketing teams haven't touched it yet.

I spent weeks testing resources, courses, and repos to find what actually matters for revenue teams.

Here's the full list:

(Save this post. You'll come back to it!)

📖 Official Anthropic Resources

→ Claude Code Docs & Installation (the starting point)
🔗 https://lnkd.in/erW_rUrD

→ Claude Code GitHub (open-source repo, plugins, community contributions)
🔗 https://lnkd.in/eNS_huU6

→ Claude Code Best Practices (CLAUDE.md setup, custom commands, multi-instance workflows)
🔗 https://lnkd.in/e2w8tCAe

→ Context Engineering for AI Agents (why context structure matters more than the model)
🔗 https://lnkd.in/es5HWkH7

→ MCP (Model Context Protocol) (connect Claude Code to your CRM, enrichment tools, and data sources)
🔗 https://lnkd.in/eWaxd7PQ

→ Claude Code in Action (Free, official Anthropic course). Context management, custom commands, MCP servers, planning modes.
🔗 https://lnkd.in/ejb4sn2n

→ Claude Use Cases for Marketing & Sales
🔗 https://lnkd.in/e_ZebcAc

🎧 Watch & Listen

→ AI Engineer: Barry Zhang and Mahesh Murag from Anthropic
🔗 https://lnkd.in/eZN9uuGi

→ Greg Isenberg + Ras Mic: "The Most CLEAR Explanation of Claude Code"
🔗 https://lnkd.in/eqGgVT9c

🛠️ Repos, Skills & Tools

→ Anthropic Official Skills (69K+ stars). Docx, pptx, xlsx, PDF creation, and more.
🔗 https://lnkd.in/eCpuP6HJ

→ Superpowers by obra (9K+ stars). Brainstorming, spec writing, TDD, subagent-driven development. Turns Claude Code into an autonomous engineering teammate.
🔗 https://lnkd.in/eZib-p7F

→ Claude Code Guide by Cranot (2,360+ stars). Most complete community reference. Auto-updates every 2 days.
🔗 https://lnkd.in/eQYiAVKu

→ Awesome Claude Code. The definitive community list. Slash commands, CLAUDE.md files, agents, skills, hooks, plugins.
🔗 https://lnkd.in/eXzWUxgw

→ Skills.sh. 55,000+ installable skills. Search marketing-relevant ones like copywriting (12K+ installs), SEO audit (17K+), social content (7K+).
🔗 https://skills.sh/

→ AI Templates (aitmpl.com). 30+ pre-built Claude Code agents, skills, commands, hooks, and MCP configs.
🔗 https://lnkd.in/eRgRPK_s

→ OneWave-AI Skills Collection. 100 production-ready skills for sales, business automation, content creation.
🔗 https://lnkd.in/eam8FR9k

I'm already using Claude Code to build custom tools and workflows for GTM.

The GTM teams that learn this now will have a 12-month head start.

What's the first GTM workflow you'd build with Claude Code?

Most salespeople send one email and move on.

Lemlist analyzed hundreds of thousands of outbound emails on their platform.

The pattern is clear: multi-touch sequences consistently outperform single sends.

Not by a little. By a lot.

Here's what's actually happening when you follow up:

→ Your prospect gets 100+ emails a day. 
One email is invisible. Three emails make you exist.

→ Timing is random. 
Your first email lands during a board prep. Your third lands when they're actively looking for a solution.

→ Following up isn't "being pushy." 
It's removing friction. Most people don't ignore you because they're not interested. They ignore you because they forgot.

The reps I see booking the most meetings all have one thing in common.

They follow up more than their competitors.

Not with "just checking in" emails. With new angles, new value, new reasons to reply.

The fear of being annoying costs more pipeline than persistence ever will.

What's your follow-up sequence look like right now? 2 emails? 5? More?

4 Reasons Why You Need Follow-Up Emails

Most sales teams are chasing the latest AI feature.
Meanwhile, fundamentals are broken.

No tool will save you if you can't answer three questions:

→ How am I relevant to my targets?
→ How do I reach out at the right time?
→ Is my technical setup delivering my messages?

Everything in outbound reduces to these three variables.

The rest is execution.

And execution goes wrong when you stack 5-6 tools and lose yourself in complexity.

Or, you can focus on one good tool that covers it all.

I’ve been using lemlist for almost 10 years, and I consider it one of the best tools in the outbound stack.

Here's what makes it work:

→ Built-in lead database. 
When I define my ICP, I build the list directly inside the tool. No exporting CSVs. No enrichment subscriptions. Just one workflow.

→ Signal detection. 
Job changes, website visitors, LinkedIn activity. You know when the timing is right before you hit send.

→ AI features that make sense.
Automatically cleaning names, classifying leads in relevant buckets, company latest news. No AI for the sake of it, only what you’d have done anyway. 

→ Multi-channel sequences. 
Email, LinkedIn, WhatsApp. Deliverability monitoring, warm-up included, all channels in one workflow.

Get the strategy right first. 
Then pick the tool that matches your resources.

After that, you'll have plenty of time to evaluate the next shiny feature the lead gen bubble is selling you.

What does your current outbound stack look like?

Stop overcomplicating outbound - Fix the basics

8 years of cold email. Many things changed.

But 3 principles never moved.

I've sent millions of cold emails since 2018.

Open rates went from easy to earn to nearly impossible if you skip the fundamentals.

Here's what still works, no matter what Gmail or Outlook throw at you:

→ Targeting
If you're emailing anyone outside your ICP, you're burning domains for nothing. Tight lists convert. Broad lists destroy your sender reputation.

→ Infrastructure 
SPF, DKIM, DMARC, domain rotation, inbox warming. In 2018, I set this up manually. Today, it's too complex and too costly to DIY. 

I use Mailpool for all my email infrastructure. Domains, inboxes, spam checks, Google Workspace, Microsoft 365, and SFTP. All handled. No going back.

→ Messaging 
Landing in the primary inbox is step one. Getting a reply is what keeps you there. Low volume. No spammy words. Relevant copy only. Replies signal to Gmail that you're a legit sender.

Most teams fail at cold email because they skip straight to copywriting.

Copy doesn't matter if your emails land in spam.
Deliverability doesn't matter if you're emailing the wrong people.

The order matters: targeting → infrastructure → message.

Get these 3 right, and cold email still outperforms every other outbound channel in cost per meeting.

And I highly recommend using a trustworthy provider like Mailpool to handle your infrastructure!

Which of these 3 is the hardest to get right for your team?

3 key principles after 8 years of cold email

I used to be "the cold email guy."

For years, that was my identity. Automating prospecting. Optimizing deliverability. Building sequences that actually get replies.

I was good at it. But at some point, I started feeling stuck.

I was solving the same problems over and over. Open rates. Reply rates. Infrastructure fixes. The tactics kept evolving, but the scope stayed small.

I wasn't thinking about revenue. I was thinking about replies.

And I kept asking myself: is this it?

The companies I admired were doing more. They had marketing, RevOps, sales, and data teams all working toward the same goal. Every piece of the revenue engine was in place.

But here's what I noticed: those pieces weren't connected. They were running in parallel, not as a system.

Then 2023 happened.

AI. Clay. 

AI-powered enrichment. Intelligent automation. Suddenly the tools existed to do something new.

Not just automate prospecting. But connect everything.

Signals feeding scoring. Scoring feeding routing. Routing feeding outbound, ads, and nurture. One system. One data layer. Every motion working together.

That's when it clicked.

The winning companies had all the pieces. What they didn't have yet was the glue.

AI + automation wasn't just the next chapter of outbound. It was the way to connect what the best companies were already doing separately.

So I made a choice.

I stopped positioning myself as an outbound specialist and started thinking like an engineer.

Not just "how do I send better emails?"
But "how do I build a revenue system where every piece compounds?"

→ I started mapping 100+ buying signals
→ I connected outbound, marekting, and CRM
→ I built scoring models that route leads automatically

Most importantly, I stopped thinking in campaigns and started thinking in systems.

Cold email is still in the playbook. But it's one play in a system of 75.

The real game is GTM Engineering. Building the glue that makes revenue engines work.

If you're feeling stuck in one skill, one channel, one identity, maybe it's time to zoom out.

The best version of your work might be bigger than what you're known for today.

What skill are you evolving beyond right now?

The SDR role isn't dying. 
It's being redesigned.

Humans doing robot work was never the play.

Sales is hard. I've lived it for years. 
But hard doesn't have to mean miserable.

And your growth doesn't have to suffer either.

The GTM Engine changes everything. 
I've seen it firsthand.

Here's what a day in the life of an SDR should look like in 2026:

𝟵:𝟬𝟬 𝗔𝗠 
❌ 12 open tabs. Manual scraping. Copy-paste chaos. 
✅ You log in. Warm leads are already waiting.

𝟭𝟬:𝟯𝟬 𝗔𝗠 
❌ LinkedIn + Google detective work. 
✅ Intent data is enriched, scored, and sorted for you.

𝟭:𝟬𝟬 𝗣𝗠 
❌ Staring at a blank screen, writing cold emails from zero. 
✅ Smart outreach is drafted. You refine. You don't rebuild.

𝟯:𝟬𝟬 𝗣𝗠 
❌ Manual follow-ups falling through the cracks. 
✅ Behavior-based triggers handle it. CRM stays clean.

𝟱:𝟯𝟬 𝗣𝗠 
❌ 40 touchpoints. 1 decent conversation. Soul-crushing. 
✅ Fewer hours. Better conversations. Real momentum.

Same title on the business card. 
Completely different reality behind it.

AI isn't here to replace SDRs. 
It's here to cut through the noise that was burning them out.

♻️ Reshare if this resonates. 
➕ Follow Jérémy Grandillon for more!

SDR Life Before VS After Automation

SDRs don't fail because of effort.
They fail because of infrastructure.

Most SDR teams spend 80% of their time on research, CRM updates, and admin.

The top-performing ones spend 80% on conversations and strategy.

Here's what separates them:

→ Lead research: 
Manual tab-switching vs. automated enrichment through Clay or Builtwith.

→ Personalization: 
Writing every email from scratch vs. AI-generated messaging based on intent signals.

→ CRM hygiene: 
Repetitive manual updates vs. auto-synced workflows in HubSpot or Salesforce.

→ Targeting: 
Static lists with zero context vs. signal-qualified prospects scored by job changes, funding rounds, tech installs.

→ Onboarding: 
Weeks of shadowing vs. prebuilt sequences and playbooks ready on day one.

The SDR role isn't dying.

But the SDR operating system is being completely rebuilt.

What's the one manual task your SDRs still waste the most time on?

I just made our entire GTM Engineering Playbook free. 20+ pages. 300+ operational assets. 

Everything we use to build signal-based revenue engines for B2B companies.

After 8+ years in Sales, Marketing, and RevOps, every framework, scoring model, database, and workflow we run lives inside this playbook.

We use it to:
→ Define TAMs and qualify accounts at scale 
→ Detect 1st, 2nd, and 3rd party buying signals
→ Score and route leads to the right channel
→ Launch outbound plays triggered by real-time signals
→ Build entire GTM motions from audit to full speed

102 signals. 75 plays. 9 workflows. 300+ ready-to-use assets.

Here’s what’s inside:

1️⃣ Signal Detection

102 intent signals mapped to source, strength, and response window
82 scraper triggers for automated signal capture via Apify and Phantombuster
3-layer signal taxonomy: 1st party, 2nd party, 3rd party

2️⃣ Lead Scoring & Routing

Dual-axis scoring framework: Account Score + Lead Score on a 1-10 scale
Lead Treatment Matrix that routes leads to 6 outreach channels automatically
6 AI qualification prompts with JSON scoring rubrics ready for Clay

3️⃣ Outbound Execution

75 ready-to-execute outbound plays organized by funnel stage and effort level
6 day-by-day cadence templates with message frameworks and benchmarks
Complete cold email infrastructure guide: domains, DNS, warm-up, deliverability

4️⃣ Automation & Implementation

9 end-to-end automation workflows with trigger logic and routing rules
90-day implementation roadmap: from discovery to fully operational in 12 weeks
ROI calculator with formulas, benchmarks, and leadership-ready reporting

I know, that's a lot. 

Every piece compounds. 
Your signals feed your scoring. 
Your scoring feeds your routing. 
Your routing feeds your outbound. 
Your analytics extract what converts and feed it all back.

And the good news is that we'll keep updating it as we experiment new plays.

(Claude Code is coming). 

This is the exact methodology we deliver to clients. Now it’s free.

→ Connect with me
→ Comment “GTM”

I’ll send it straight to your DMs.

The SDR role isn't disappearing. It's splitting in two.

One path leads to GTM Engineering.
The other leads to burnout.

Most SDR teams still run the old playbook.
Manual lead research. Static sequences. Activity metrics.
Hours spent on data entry instead of selling.

That model is collapsing.

The teams winning right now look completely different.

→ They use Clay to enrich leads from 10+ sources automatically.

→ CRM updates itself through HubSpot workflows and system triggers.

→ Outreach adapts in real time based on intent signals, not arbitrary cadences.

→ Follow-ups run on autopilot until human judgment is actually needed.

One GTM Engineer replaces the chaos of 7 disconnected tools with a single orchestrated system.

The shift isn't AI replacing SDRs.

It's AI removing everything that was never selling in the first place.

Lead research. Data entry. Sequence management. Activity logging.

That was 70% of an SDR's week. Now it's zero.

What's left is the work that actually moves pipeline.
Strategic conversations. Pattern recognition. Creative problem-solving.

The SDRs who adapt become the most valuable people on the revenue team.

The ones who don't get outpaced by a Clay table and 3 Zapier automations.

What's the first part of your outbound workflow you'd hand off to automation tomorrow?

Clay just launched Ads. 
And most people will miss why this matters.

Here's the short version: 

You can now build ad audiences directly from your CRM data and buying signals, then sync them to LinkedIn, Meta, and Google ads.

Same enrichment engine that powers your outbound. Now powering your paid media.

Let me break down the workflow:

→ Pull a high-intent list from your CRM
Not a generic audience. Your actual pipeline. Your actual target accounts.

→ Layer Clay's enrichment on top
Job changes, funding rounds, tech stack signals, website visits. The same data you already use for outbound.

→ Clay enriches contacts 
Emails and identifiers to maximize match rates. They're claiming up to 95% on LinkedIn and 65% on Meta. Way above standard CRM-to-ads sync.

→ Push those audiences directly to LinkedIn, Meta, or Google. One sync. No CSV exports. No manual uploads.

But here's where it gets interesting.

You can target the exact accounts your sales team is working. Not lookalikes. The actual people.

You can exclude customers, employees, and out-of-ICP contacts dynamically.

You can shift budget based on live intent signals. 
Tier 1 accounts on your pricing page: they see your ads first.

This is CRM-powered precision advertising built on the same engine that runs your outbound.

And this is exactly why I keep saying GTM Engineering is not just about sales automation.

The same data layer that powers your lead scoring, your sequences, your CRM hygiene now also powers your ad targeting. 

Same signals. Same enrichment. Same logic. Applied across channels.

When your sales team works 200 high-intent accounts and your marketing team runs ads to a completely different audience, you're burning money. 
Clay Ads makes those two motions run on the same data for the first time.

For teams that already have GTM automation in place, this is an immediate multiplier. You're extending your existing system into a new channel with zero additional data work.

For teams that don't... the gap just got wider.

Clay keeps shipping features that prove the same thesis: GTM is a system, not a set of disconnected tools.

What channel would you connect to your CRM data first if match rates were actually reliable?

If you're still sending cold emails from 2-3 inboxes in 2026, you're landing in spam.

Spam filters got brutal last year.

Blasting hundreds of emails from a single domain gets you flagged in days.

The fix is to scale horizontally.
More domains. More inboxes. Lower volume per inbox.

But setting this up manually through Gmail or Outlook is expensive, slow, and a technical mess.

You don't want to deal with SPF, DKIM, DMARC, and all the funky letters on your own.

That's why I use Mailpool for my clients and my own outbound.

Here's the setup in 3 steps:

→ Connect your domains (or buy them directly). 
DNS setup is guided. No more guessing which TXT record goes where.

→ Spin up inboxes across Gmail, Outlook, and SMTP. 
Mix providers for better deliverability and keep volume low per inbox. 
This is what actually keeps you out of spam.

→ Plug into your favorite outreach tool. 
Mailpool connects with most cold email platforms, so you don't rebuild your workflow from scratch.

The whole thing takes minutes, not days.

The difference between a clean infrastructure and a messy one is the difference between 40% open rates and landing in junk.

I've been in the cold email game for years, and I'm glad I found a provider I can trust. 

I definitely recommend checking out Mailpool for the best infrastructure!

Your CRM is quietly draining your pipeline.

Not because the tool is broken.
Because nobody owns what's inside it.

I've audited dozens of CRMs. The pattern is always the same.

→ 30-40 of contacts have no valid email.
Enrichment ran once, 18 months ago. Never again.

→ Lead routing is based on fields nobody updates.
Reps get assigned accounts they've never touched. Territories overlap. Deals fall through the cracks.

→ Duplicates everywhere.
Same company, 4 records, 3 owners, zero accountability.
The "source of truth" is a source of confusion.

→ Pipeline reviews built on stale data.
Forecasts are fiction. Leadership makes decisions based on numbers that were wrong weeks ago.

The real cost isn't inefficiency.
It's the deals your team never even sees.

A dirty CRM doesn't just slow you down. It makes automation impossible.

You can't build AI workflows, lead scoring, or signal-based outreach on top of garbage data.

The companies shipping real GTM automation right now all started the same way.

They fixed the foundation first.

What's the first thing you'd clean up in your CRM if you had a full week to dedicate to it?

Pushy selling is the fastest way to kill pipeline.

I've seen outbound teams burn through hundreds leads a month with zero results.

Not because the leads were bad.
Because every touchpoint screamed "BUY NOW."

Buyers don't respond to pressure. They respond to psychology.

Here's what actually moves deals forward:

→ Reciprocity 
Give before you ask. Share a relevant benchmark, a teardown, a custom insight. Our best-converting sequences all start with value, never a pitch.

→ Social proof 
"We helped 40+ B2B SaaS companies cut cost-per-meeting by 60%" hits harder than "we're the best at outbound." Peer wins beat promises every time.

→ Loss aversion 
Quantify the cost of doing nothing. "You're spending €18K/month on SDRs generating 12 meetings" is more powerful than any feature list.

→ Micro-commitments 
Don't ask for a 30-min call on the first touch. Ask for a reaction. A reply. A small yes that opens the door to a bigger one.

→ Authority
Credentials and case studies close more than objection-handling scripts. Be the advisor buyers trust, not the seller they avoid.

→ Emotional anchoring 
Start with their goal, not your product. Tie the solution to where they want to be before you address what's broken.

Most outbound fails because it leads with pressure instead of trust.

Trust, logic, and emotion close deals. 

Sequences built on psychology outperform brute-force volume every single time.

What's the one psychological trigger that works best in your outbound sequences?

Most sales teams are still hiring their way out of problems.

More SDRs. More seats. More fixed costs.
Then wondering why margins shrink and turnover spikes.

Here's what the shift actually looks like:

The legacy playbook:
→ 12-month contracts on tools nobody fully uses.
→ 15 SDRs grinding 200 calls/day against outdated lists.
→ 40% annual turnover. Constant ramp cycles.

The modern playbook:
→ 1-2 GTM Engineers replacing entire outbound teams.
→ Pay-as-you-go stack: Clay, enrichment APIs.
→ Automated lead scoring, routing, and sequencing.
→ Pipeline grows. Headcount doesn't.

The difference isn't "working smarter."
It's architectural.

One model scales with people.
The other scales with systems.

I've seen teams cut outbound costs by 60% while tripling qualified meetings. Not by optimizing scripts. By rebuilding the engine underneath.

The companies pulling ahead right now aren't the ones with the biggest sales floors.
They're the ones where a single GTM engineer runs what used to take a team of 10.

What's the first thing you'd replace with automation in your outbound stack?

The best automation in the world is worthless if your CRM is dirty.

You can have the best Clay workflow.
The best HubSpot scoring model.
The best outbound sequence.

If the data feeding it is wrong, the whole system loses its impact.

Same thing with AI.

A perfect prompt with garbage context gives you garbage output.
An agent connected to an unenriched CRM is an agent spinning its wheels.

The real lever isn't the tool.
It's the quality of what feeds it.

→ Data enriched in near real-time
→ Standardized fields
→ Duplicates eliminated
→ Routing built on reliable information

When all of that is clean, every layer you add (workflow, agent, scoring) runs at full power.

Otherwise, you're stacking tools on broken foundations.

What's the first field in your CRM you'd clean up?

Michel Lieben 🧠

Founder / CEO @ ColdIQ | Scale Outbound with AI & Tech 👉 coldiq.com

I’m (Michel) the Founder & CEO at ColdIQ, a sales prospecting agency (+ we compare the latest sales tech, too!).

We worked with 100+ B2B organizations (including SaaS & Agencies!) and are using Clay, Prospeo, FullEnrich, Instantly, Lemlist, Ocean.io - alongside other great sales tools - to run outbound campaigns that flood 🌊 our (and our clients’) inboxes with interested prospects.


We can help you:

• If you’re a B2B business leader who doesn’t have the time to handle your prospecting engine or to hire and manage salespeople… You can outsource your lead gen to us, and we’ll transparently show you the exact way we run your campaigns. (We’ll provide SOPs, too… if it works so well that you want to build your in-house team).


• If you’re a sales leader or an outbound agency owner: We’ll help you set up the exact systems & tools we use to run automated ‘trigger-based’ campaigns that convert like crazy. 


• And… if you simply want to improve your B2B sales automation skills or learn to run these campaigns yourself, we’ll teach you by building a campaign from scratch together with you —from ‘idea’ to ‘running campaign’ (we’ve done it more than 50 times already, and the rumour says people ❤️ed it).


We've launched hundreds of campaigns, so you don't have to.


Thus - if you: 
- are a B2B service/solution provider making > $50k/month
- provide solutions with Lifetime Value > $10k
- want to shortcut your outbound success


We can help.

Send a DM, and I'll share more details.

Alternatively, reach out to michel[at]coldiq.com 
or via the website 👉 coldiq.com 


__________



And if you're looking to build your top-of-funnel tool stack... 
Check our curated lists of the best outbound tools here 👇

👉 coldiq.com/tools 👈
👉 coldiq.com/ai-sales-tools 👈

Performance-based B2B lead generation 💥 | coldiq.com
→ We help you scale your prospecting activities by implementing outbound sales systems in your business. We take care of sourcing leads, researching your ICP, crafting the sales messages, automating sending and ensuring the high deliverability of messages. We let you focus on what brings money into the business: closing deals.

Can you run your entire GTM with Claude Code?

We're answering that tomorrow.

We use Claude Code for:

Paid media.
Outbound.
Reporting.
CRM ops.

All through AI agents we built in-house and deployed across 70+ B2B clients inside our $7M ARR agency.

On February 26th, we're opening our terminals and showing everything. 
Live.

What we'll cover:

Outbound
→ ICP scoring & signal-based lead prioritization on autopilot
→ cold email sequences built from real performance data
→ AI reply handling in under 2 minutes

ABM/Ads
→ automated campaign creation, reporting & optimization
→ AI agents managing LinkedIn, Meta & Google ads
→ paid media run entirely from the terminal

RevOps
→ campaign diagnostics that took hours, done in 60 seconds
→ live dashboards pulling every data source into one view
→ bidirectional CRM sync: Attio, Lemlist & Instantly

What you'll leave with:

→ how to build your first Claude Code GTM agent from scratch
→ the architecture behind 32 skills, 12 agents & 2,108 files
→ which GTM use cases actually deliver ROI today

We'll demo the agents live.
Then break down the architecture so you can build your own.

Hosted by Ivan Falco (Head of Growth) & Kenny Damian (Head of GTM) at ColdIQ.

February 26th - 1:30 PM EST

In case you missed the event....

Here's the link to the webinar recording - https://lnkd.in/eqNfrT7b

Founder & CEO at ColdIQ | Tomorrow’s GTM Systems, Built for you 👉 coldiq.com

Yesterday, > 1400 people watched Kenny Damian build an entire outbound campaign using Claude code.

He wrote a few prompts in the terminal, fed it a list of companies, and then...

Claude Code took over:

1. It scored and prioritised the entire company list against our ICP

2. It found verified email addresses through Apollo’s API

3. When Apollo didn’t have coverage, it automatically pulled in additional enrichment providers to fill the gaps

4. It wrote personalised copy templates on its own (based on our best-performing outreach)

5. Then it uploaded the entire campaign: leads, sequences, and copy... straight into Instantly.ai

It took fewer than 20 minutes.

This was just one of three demos we ran.

Right before that, Ivan Falco showed us how to automate ad campaign creation & 'warm' social prospecting.

Unfortunately, I can't upload the entire video here due to LinkedIn's file size limits.

If you couldn't attend: 

Here is the recording and the full playbook bundle (frameworks, SOPs, templates) so you can try this yourself -

https://lnkd.in/eD-WAHyU

Imagine only cold emailing leads who WANT to buy from you…

The closest way to do so? Leveraging buying signals:

The idea is that these signals help you:
- find relevant reasons to initiate contact
- re-activate existing prospects at the perfect moment
- surface new challenges to address in your messaging

… and much more.

There are several categories of signals:

1️⃣ First-Party Signals

↳ = Intent data gathered from your own business ecosystem.

These are prospects who already know you, actively taking steps like:

- utilizing your product
- browsing your website
- subscribing to your email list
- interacting with your brand on social platforms

Platforms that help you capture these signals include:

1. LinkedIn Signals: Clay, Expandi.io, Trigify.io, Jungler

2. Website Visitors: Instantly.ai, Clay, Midbound, Vector 👻

3. Product Usage: Common Room, Mixpanel, Pocus, PostHog

4. Call Transcripts: Attention, Fireflies, Claap

5. Gated Content: Distribute, Gamma


2️⃣ Second-Party Signals

↳ = Intent data sourced from your ecosystem, shared by partners.

Generally, prospects who have engaged with:

- your brand on a partner platform (e.g: checking out your listing on G2)
- your company, while employed at a different organization
- a partner of yours with an overlapping customer base

Examples include:

6. Champion Tracking: Clay, Common Room, Unify, UserGems 

7. Affinity Signals: Crossbeam, Reveal, The Swarm 🔆, PartnerStack

8. Ad Engagement: Fibbler, ZenABM, Factors AI

9. Software Marketplaces: G2, Capterra, ColdIQ


3️⃣ Third-Party Signals

↳ = Intent data sourced from external providers.

Thus, public signals indicating companies might benefit from your solution.

Examples include:

10. Technographic Data: Clay, PredictLeads, HG Insights, BuiltWith, Similarweb

11. Funding Announcements: PredictLeads, lemlist, Clay, Crunchbase, Owler, PitchBook, 

12. Web Data Agent: Claygent, Parallel Web Systems, Tavily, Common Room, Unify, Linkup, Perplexity, Manus AI

13. Job Openings: Common Room, PredictLeads, Clay, LoneScale, Mantiks, TheirStack, Lemlist

14. Custom Scraping: Apify, Firecrawl, Claygent, Instant Data Scraper

15. News Monitoring: PredictLeads, Google News, Exa

16. Ads Activity: Apify, Adyntel, Ahrefs

17. Firmographic Data: Prospeo, Wiza, Exa, DiscoLike

18. Lookalike Search: PredictLeads, DiscoLike


P.S: What’s your preferred tool for monitoring buying signals?

We recently crossed $7M ARR.

Here’s every tool we use to run our business:

1️⃣ Content Engine

LinkedIn generates 100+ leads for us every month.

This includes my account: Michel Lieben [67,000+ followers] 
+ other team members [300,000+ followers combined]. 

I use:

- Taplio for content inspiration & ideation.
- Notion for content planning & calendar.
- Scripe to draw inspiration from specific creators.

I crossed 2,200 YouTube subscribers from 15 videos. 

I use:

- Tella for async video production.
- vidIQ for content discovery & ideation.

We ship 2 articles/week and attract 100,000+ visitors quarterly.

30% now comes from SEO, thanks to free mini-tools we built for lead gen, & programmatic pages we created at scale. 

We use:

- Claude Code to build these out.
- AirOps for programmatic SEO.
- Ahrefs for keyword research.

We have ~10,000 active newsletter subscribers with 40%+ open rates. 

We use beehiiv to send our weekly issues.


2️⃣ Outbound System

We deliver Outbound & GTM services to 80+ B2B clients.

Our entire outbound engine runs on Clay for:

→ Enrichment
→ Personalization
→ Prospect research
→ Workflow automation
→ Signal-based targeting

We also use Claude Code for list building, email copywriting, and automating campaign creation.

Plus specialised tools for:

- AI Agents: Relevance AI, n8n.
- Outreach: Instantly.ai, lemlist, Expandi.
- Lead Sources: Prospeo, Apify, Exa, Openmart.
- Contact Data: Wiza, FullEnrich, Prospeo, LeadMagic.
- Intent + Retargeting: PredictLeads, Common Room, Vector 👻, Fibbler, Midbound


3️⃣ Operations Stack

Our team includes 35 FTEs & ~12 Fractional Freelancers.

We use:

- For internal automations: n8n, Claude Code

- For internal database & documentation: Airtable, Notion, Supabase

- For team communication: Slack, Google Meet, Norrsken Barcelona (office by the sea 🌊)


4️⃣ Inbound Funnel

We book ~100 qualified B2B meetings monthly. 

We use:

- Default (lead routing)
- GA4 + Wistia (analytics + VSL)
- Usermaven (analytics & attribution)
- Webflow & Vercel (website hosting)

For re-engagement:

- Customer.io (email marketing)
- Kondo: Superhuman for LinkedIn DMs (LinkedIn inbox management)


5️⃣ Sales Stack

We closed +$1,000,000 in new ARR last month. We use:

- Attio (CRM)
- Qwilr (proposals)
- Attention (AI meeting notes)


6️⃣ Billing & Finance

We’re integrating Hyperline for billing our productized offerings. It handles quoting, invoicing, and payment collection in one.

On top of that, we use:

- Ramp (expense & treasury management)
- Stripe, Revolut, Mercury (billing + banking)


P.S: What’s one tool we should absolutely try?

I tried way too many AI Sales tools in 2025

Here are the categories I’m closely monitoring in 2026:

1/ Workflow Builders

Why?

↳ They allow you to create advanced, multi-step, automated prospecting workflows.

Example use-case: Running a signal-based Clay campaign that ranks leads, segments them into several tiers, adds an AI-personalized first line… and then pushes contacts to your preferred sequencer. 

Examples include:

→ n8n
→ Clay
→ Outbond
→ Relevance AI
→ Enginy (formerly Genesy)


2/ MCPs

Why?

↳ They allow AI agents to execute actions by connecting to your tools. Without you needing to manually open them.

Example use-case: Connecting Claude MCP to Google Calendar so that it…

1. Checks how many sales calls you have today
2. Researches each prospect
3. Provides relevant talking points for the qualified ones…
4. Cancels meetings with unqualified leads.

All that, without opening your calendar app.

You can prompt via tools such as:
→ Cursor
→ Claude Code

And connect to your apps using:
→ Docker, Inc
→ Pipedream
→ Composio


3/ AI Coding Tools

Why?

↳ They enable you to write code in plain English. These can be leveraged to build complex workflows.

Example use-case: Build a phone number finder to collect email addresses.

My personal favourites include:
→ Cursor
→ Claude Code
→ OpenAI Codex

Other platforms include:
→ Warp
→ Cline
→ Replit
→ Lovable
→ Windsurf


4/ All-in-One Sales Platforms

Why?

↳ They consolidate all essential cold outreach capabilities into one software.

Example use-case: Warming up domains, assembling a lead list, monitoring relevant signals, enriching contact data & automating outreach within a single platform. 

Examples include:

→ Instantly.ai
→ Expandi
→ Artisan
→ lemlist


5/ Sourcing Agents

Why?

↳ They gather data autonomously, given a set of prompts.

Example use-case: Sourcing a list of Sales Leaders, based in SF, in VC-based startups that have > 5X’d revenue 2 years in a row within the last 3 years… by simply telling Exa, in plain English, that this is the list you’re looking to build.

Examples:

→ Parallel Web Systems
→ Relevance AI
→ Claygent
→ Linkup
→ Tavily
→ Apify
→ Exa


6/ Conversation Intelligence

Why?

↳ They record meetings & surface relevant insights from your business conversations.

Example use-case: Reviewing your latest 100 sales calls via Attention’s agent to identify the most frequent objections your sales team receives from prospects.

Examples:

→ Momentum.io
→ Fireflies.ai
→ Attention
→ Claap


7/ Signal Platforms

Why?

↳ They track intent signals to help you uncover prospects in buying mode.

Example use-case: Monitoring previous product buyers (champions) in Common Room, to pitch your solution when they move to a new company (that doesn’t use your product yet!)

Examples:

→ Common Room
→ PredictLeads
→ TheirStack
→ Clay

P.S: What AI Sales software category are you betting on in 2026?

AI Sales Categories (2026)

Most companies bet their LinkedIn strategy on the Founder.

We turned 24 employees into LinkedIn influencers:

In the span of 90 days, it led to:

581 LinkedIn publications,

adding up to:
> 43,000 reactions (likes, supports, loves)
> 28,000 post comments
> 34,000 new followers

Craziest part about all this is that I'm convinced most B2B teams can replicate this playbook 'pretty' easily.

👉 Here's how: youtu.be/d-gqMuvDQFQ

I asked 62 GTM leaders running $1M+ orgs what tools they use.

One tool showed up in 71% of stacks:

MOST MENTIONED:

- Clay (71%)
- n8n (48%)
- HubSpot (39%)
- Instantly.ai(35%)
- HeyReach.io (35%)
- Apollo (35%)
- LinkedIn (32%)
- Attio (32%)
- Prospeo (29%)
- Lovable (29%)


FEATURED STACKS:

Nikola Sokolov (CEO, influencers.club) - 54 tools
↳ Clay, Instantly, HeyReach, n8n, HubSpot +49

Charles Tenot (CEO, lemlist) - 40 tools
↳ Clay, n8n, Apollo, Ahrefs, HubSpot +35

Jaspar Carmichael-Jack (CEO, Artisan) - 25 tools
↳ HubSpot, Gong, Lovable, Ahrefs, Artisan +20

Benjamin Douablin (CEO, FullEnrich) - 19 tools
↳ HubSpot, Instantly, HeyReach, n8n, FullEnrich +14

Eoin Clancy (Head of Growth, AirOps) - 17 tools
↳ AirOps, Lemlist, Clay, Common Room, Attention +12

Kai Brandt (CEO, Enginy (formerly Genesy)) - 17 tools
↳ HubSpot, Claude, Ahrefs, Lovable, Loom +12

Pierre Herubel (Co-Founder, Content Path) - 15 tools
↳ Clay, Claude, Attio, Lemlist, Webflow +10

Roq Xever (Founder, PredictLeads) - 15 tools
↳ HubSpot, Clay, Claude, Cursor, Lusha +10

+49 more stacks broken down on our "tech stacks" page.
(Link in the comments)

P.S: Any tools surprise you?

27 APIs to turn Claude Code into a lead generation machine:

1. PredictLeads

Example use case: use PredictLeads' API within Claude Code to monitor signals on target accounts such as hiring surges, funding rounds & tech installs.

2. LeadsFactory

Use case: find people by job title by providing a LinkedIn company URL as an input.

3. Exa

Use case: Describe your ICP in plain English and let Claude Code search the web semantically to find matching companies.

4. Jina AI

Use case: feed Claude Code any URL via Jina's API to convert the page into clean readable text (so that you can then extract prospect info, pricing data or company intel & mor)e.

5. Wiza

Use case: feed Claude a list of leads and Wiza's API finds verified emails and phone numbers.

6. Prospeo

Use case: build lead lists, find emails & find phone numbers via Prospeo's API

7. FullEnrich

Use case: run Claude Code's enrichment step through 15+ data providers in a waterfall to find verified emails and phones that single-source tools miss

8. Apify

Use case: let Claude Code run pre-built scrapers for social media profiles, company pages, Google Maps & other platforms.

9. Trigger.dev

Use case: let Claude Code kick off long-running GTM workflows (batch enrichment, multi-step sequences, CSV processing) that run reliably

10. lemlist

Use case: connect Claude Code to your multichannel outreach tool to automate outbound campaign creation.

11. Instantly.ai

Use case: let Claude Code push enriched leads into cold email campaigns.

12. Google Analytics

Use case: ask Claude Code to pull your website traffic, conversions and channel data to gather insights on your GTM activities.

13. DataForSEO

Use case: let Claude Code pull SERP rankings, keyword volumes and competitor data to fuel your SEO content strategy without touching a dashboard

14. Logo.dev

Use case: let Claude Code fetch any company's logo by domain to fill your sales decks or branded visuals.

15. fal

Use case: ask Claude Code to generate ad creatives, social visuals or video assets on demand using 600+ AI models through a single API call


...ran out of space here, but there are 12 more in the slides 👇


P.S: What's your favourite GTM API for Claude Code?

Top 27 GTM APIs for Claude Code

44 data sources to find prospects in any niche...

...and 7 different ways to source this data:


1. Leverage sourcing agents

Use platforms like Airtop, Clay, Exa, Perplexity, Manus AI or Relevance AI and describe in plain/natural language what you're looking for.

Their agents handle the rest.


2. Use 'standard' B2B databases

Use filters such as “job title”, “location”, “employee count”, “headcount growth” within standard databases like Prospeo, Wiza, Apollo, LinkedIn & DiscoLike 

…or using niche databases like Openmart, influencers.club… 

to find your target data.


3. Target by technology

Use APIs like PredictLeads, or platforms like TheirStack, BuiltWith & BuyerCaddy to find companies using a specific technology.

Their use of this tech should suggest they’re a great lead for you.


4. Target companies showing buying intent for your offering category.

Monitor companies’ activity, including:
- Job openings
- Funding events
- Social engagement
- Tech/software changes

Via tools like Clay, PredictLeads, Common Room, and Trigify.io to infer potential buying willingness. 


5. Custom data extraction

Extract data from popular websites, specific pages, or any site using Apify actors or tools like Instant Data Scraper, Firecrawl, ZenRows & Airtop.


Once you sourced your target people & companies, you’ll want to:

→ Find their email addresses & phone numbers with point solutions (e.g: Prospeo, Wiza, LeadMagic) or…

→ Find their contact data via data waterfalls (e.g: FullEnrich, Clay, Enginy (formerly Genesy), Outbond)

More details included in the carousel below ↓

P.S: Who's your go-to to source accurate B2B data?

44 Data Sources

My cold outreach process that generated 25,000+ leads in 2026

(and got us to $7m ARR with our agency)

1. Build a few relevant audience segments

There are some ‘easy’ targeting wins when you run cold outreach for the first time.

- Companies engaging with your brand
- Companies similar to your best clients
- Companies showing buying intent in your category


2. Map your total addressable market (TAM)

That is, every single company that fits your client criteria.

You can use B2B data sources like: Clay, Wiza & Prospeo to build your account lists according to your chosen criteria (company size, geography, industry)


3. Research your target accounts & segment them into tiers.

- Tier 1 should be your dream clients or perfect fits (similar to your best clients).
- Tier 2 should be good fit clients (similar to orgs you helped).
- Tier 3 should be orgs you believe you can help.

You can prompt AI models within Clay to tier/score accounts, or do it within Claude Code by creating a .md file that includes your scoring criteria to be compared against your account list. 

APIs or tools like PredictLeads, Common Room come very handy here as well.


4. Try reaching your entire TAM every 3-6 months

- For Tier 1 leads: mix manual AE outreach + multichannel engagement = phone (use Nooks) + LinkedIn + email.

Pro tip: make sure to write the first 25-50 messages manually. 
Do the unscalable at first; this is how you’ll uncover patterns you can scale later on.

- For Tier 2 leads: automate multichannel outreach with AI (use Clay + lemlist)

Pro tip: make sure every message is valuable, relevant + personalised to each recipient. Think: “what can I send to my prospect that’ll be helpful to him, even if they ignore me”

(Here I like to think of what’s the first thing I’d do if I were to sign them as clients, and I do it already… for free).

Example: Building a free ‘niche’ lead list for target accounts, with companies/people data of their ideal clients.

- For Tier 3 leads: engage leads at scale with a proper deliverability infrastructure (use Instantly.ai).

Use tier 3 leads as an experimental playground to test out various copywriting frameworks. (Let me know if you’d like to see some high-performing ones; we collected our own list.


5. Respond to positive replies asap.

The faster your replies = the higher your meeting rate.
More meetings = more sales.


6. A few bonus tips:

- The lead list // targeting is the most important element to succeed at cold outreach. Spend most of your time on list building.
- You’re interrupting people’s day whenever you’re reaching out cold. Keep that in mind, make it a ’nice’ interruption (not always possible, but try your best!)
- Implement a proper deliverability setup. The biggest killer of email outreach is messages that land in spam.
- Warm your target accounts. If you have budget, build a target list & run LinkedIn ads to them, so that they won’t be 100% cold when they receive your outreach.


P.S: Anything you’d add?

300+ hours testing Claude Code vs. Cursor to run our GTM...

Here’s my 'final' vibe marketing stack at $7M ARR:

1. Conductor (free)
- My go-to interface to run Claude Code & Codex's latest models.
- UI is much nicer than a terminal + it lets you effortlessly toggle between Codex & Claude Code.


2. Claude Code ($100/mo)
My central hub for all API & MCP calls.

We leverage it for lots of GTM activities, beyond outbound:

→ Creating mini-tools for lead generation.
→ Data scraping + enrichment workflows.
→ Deep SEO analysis via Google Analytics MCP.
→ Entire ad campaign + outbound campaigns creation.
→ List building through Wiza, Prospeo, FullEnrich & Exa's APIs.

...

3. OpenAI Codex ($20/mo)
I barely touch it, honestly.

Mostly for the occasional build that Opus couldn’t crack.

It plugs natively into Conductor, so maintaining access at $20/mo is an easy call.


4. Cursor ($60/mo)
- I began with Cursor. Loved the UI, so I was running Claude Code inside it.
- I used it to design/build some really sharp landing pages.

...but Conductor now covers everything I need with both Claude Code & Codex baked in, with an even slicker UI so… I'm cancelling Cursor.


5. Vercel
- We host all our mini-apps & our site here.


6. GitHub


7. Lovable
- Relied on it early for prototyping & our first mini-tools.
- Solid starting point, but CC is simply stronger for what we’re doing.

--

APIs (where it gets interesting)

Claude Code is an incredibly handy way to orchestrate API calls.

No need to grasp how APIs function; you just feed it your platform’s API documentation, and it sorts out the connection by itself.

Here are some GTM APIs I wire into it:

- PredictLeads: Company intelligence data (covering hiring signals, tech stacks, and funding details).

Example use case: Calling its API from Claude to reveal target companies’ tech stacks.

- Exa: Generates lead lists in natural language.

Example use case: Call its API to “Find Series A fintech companies in Europe”.

- LeadsFactory: “Find people API”

Example use case: Leveraging it within CC to locate people by job title, given a list of domain URLs // LinkedIn company URLs.

- Google Analytics MCP: This produced one of the most insightful custom SEO reports I’ve come across. It surfaced gaps we had overlooked for months in a matter of minutes.

- Apify to tap into custom scraping actors.

- Openmart: Local B2B database.


What’s the craziest way you’ve used these “ai coding” platforms so far?


P.S: I recorded a video going through these tools & why/how I use them. It's right here: youtu.be/b9tygqQiBS8

$7M ARR Vibe Marketing Stack

This GTM workflow helped us hit $7M ARR

It consistently books us 100+ meetings per month:

1. Our team publishes 150 posts per month

- 24 people publish LinkedIn content in our team
- We incentivise w/ competition & cash prizes
- We write around our prospects' pain points
- We use Taplio + Scripe to find inspiration
- We study hooks & visuals from outliers

↳ We’re launching a new competition for Q2 2026. The goal will be to get > 300 posts/mo.

2. We promote successful posts via Thought-Leader Ads

- This generates extra views at ~$40 CPM.
- We boost posts that generated meetings.
- We check who booked from these posts.
- We boost posts in front of this ICP.

↳ We also use LinkedIn Ads to pre-warm accounts for outbound. Thus, all channels work together.

3. We re-engage leads that interacted with our ads, site or content.

- On the site: we use Midbound & Vector 👻 for website de-anonymization.
- On LinkedIn: we use tools like Trigify.io & Jungler to catch social interactions.

4. We route all qualified leads to a Clay table.

5. These leads are scored/segmented & tiered.

- Claygent does ‘advanced’ inbound research.
- LLMs prompts segment leads into tiers

- Tier 1 leads = manual outreach
- Tier 2 leads = multichannel outreach
- Tier 3 leads = automated email outreach

6. We enrich valid emails & phone numbers for prospects.

- Wiza, FullEnrich, LeadMagic & Prospeo find us contact data.
- These enrichments are performed inside Clay.

7. We re-engage leads via 1 or several channels, depending on tiering.

- We use Instantly.ai, lemlist, Expandi or Nooks for sales engagement.
- We try our best to send valuable, relevant messages.

8. This workflow booked us 1,500 meetings last year.

- We’ll probably beat that in 2026.
- This allowed us to reach $7,000,000 ARR and 36+ FTEs
- Clients are closing 6-figure deals within 90 days, running the same workflow.

Want this system built for you? 
Reach out in the DMs or via our site :)

How to write cold emails like the top 1%:

(Frameworks we use at our $7M+ ARR agency)

1. "Right Person for Opportunity" by Kenny Damian

2. "Pain | Agitate | Solve" by Soheil Saeidmehr

3. "Trigger | Implication | Pain" by Aaron Reeves

4. "Content Assets" by Ethan Parker

5. "Quick Maths" by Thibaut Souyris

6. AIDA by Monika Grycz 💌

7. Similar Challenges" by Patrick Trümpi

8. Champion Play by Brian LaManna

9. AI Campaign Ideas by Dujam Dunato 
(inspired by Eric Nowoslawski)

10. Rhetorical Question by Leif Bisping

11. "Observation | Call-Out | Proof" by Nick Abraham

12. "Trigger | Process | Symptoms" by Tal Baker-Phillips


What’s your go-to cold email template?

Drop it below 👇


P.S: We compiled the best copywriting frameworks we used to book 15,000+ B2B meetings for 260+ companies into one Notion doc.

Want it? Let me know below, and I’ll send it over :)

Write like the top 1%

Snowflake hit $4,000,000 ARR with 60% of its pipeline generated by SDRs.

Here’s their strategy (and how you can reproduce it):

First, you need to ensure your departments collaborate towards the same objective.

For Snowflake: Marketing, SDRs & Sales sit under ONE SINGLE team.

They ran the experiment for specific regions.

- The ones that did it had up to 46% meeting rates.
- The ones that didn’t do this had 17% meeting rates.

1️⃣ Alignment

Marketing & Sales operate hand in hand.

Marketing collects insights to be leveraged by the sales team.
The sales team executes on them within 2 weeks.

Seems obvious, but truth is most companies have these 2 teams working in silos.


2️⃣ Intelligence

Snowflake leverage signals a lot.
Their rationale is to get in front of prospects as soon as they’re exploring their use cases.

They do that via:

- Third-party intent signals (job changes, funding rounds, web searches)

And further down the funnel via:
- First-party intent signals (product usage, email clicks, website visits).

They rely on tools such as Bombora to detect accounts showing interest in the background. I’d suggest leveraging Clay, PredictLeads or Common Room for this.

Accounts flagged as “high intent” convert 4x better than standard accounts in the CRM.


3️⃣ Activation

When accounts display enough buying intent, Snowflake’s teams deploy their “1-2 punch” play.

That is:

Weeks 1 & 2: ABM team nurtures target accounts with personalised campaigns (ads + emails + dedicated landing pages)

Week 3: SDRs jump in with outbound.

By the time an SDR cold calls a prospect… they’re already not cold anymore.

Result = 36% meeting rates on pre-warmed accounts (vs. 10% on cold)

4️⃣ Engagement

They reach prospects everywhere they are.

→ Calls
→ Cold Emails
→ LinkedIn DMs
→ Custom microsites

True multichannel orchestration.

(I’d suggest leveraging a platform like lemlist to replicate this omnichannel engagement)

5️⃣ Optimisation

They continuously iterate on what works and what doesn’t.

Performance metrics get shared between the teams in bi-weekly alignment meetings.

ABM, SDRs, & AEs are all informed of what works in terms of messaging & targeting.

But they don’t try to attribute who’s responsible for the deal precisely.

Instead, they measure impact at the account level and optimise the entire funnel together.

The outcomes speak for themselves:

→ Deal velocity multiplied by 2.
→ Tier-1 accounts convert 5x better.
→ 2-4X more meetings on ABM accounts.

… and you don’t need Snowflake’s budget or 200+ SDRs to start executing on it.

You can start by:

- Aligning marketing & sales on shared objectives.
- Tracking buying signals 
- Launch ABM campaigns 2 weeks before starting outbound.

… and measure impact at the account level.

And if it feels like too much at once, send a DM… we’ll help you implement this system.

P.S: This workflow breakdown comes from Elric's newsletter.

Snowflake $4B ARR

How to turn $233,000 in LinkedIn ad spend into > $1,500,000 in closed revenue?

We're showing the entire playbook today. Live

CONTEXT

AirOps had a great product trusted by Webflow, Ramp, Carta and LegalZoom. But their pipeline had been stuck at ~$536K/month for almost a year.

We built a full ABM motion combining outbound + LinkedIn Ads, hitting the same accounts from every angle.


WHAT WE'LL COVER:

Account-Based Outbound
→ Building and tiering target account lists with Clay using fit + intent signals
→ Syncing outbound and LinkedIn Ads to hit the same companies from both sides
→ Signal-triggered plays that changed based on account engagement stage

Thought Leader Ads
→ Why we put 80% of ad spend behind founder content, not product ads
→ Using webinars as an outbound play - 112 positive replies from input-request invites
→ Cross-channel feedback loops between outbound and paid

The Results
→ $7.8M qualified pipeline
→ $1.5M closed-won revenue
→ 164 deals created, 30 closed-won
→ 15x pipeline ROI on $233K ad spend
→ 1,058 outbound replies
→ Ad spend scaled 20x with positive ROI

We won't keep it high-level. We'll show the exact system: TAM to TAL to signal stack to coordinated touches to pipeline.

Hosted by Ivan Falco (Head of Growth at ColdIQ) and Eoin Clancy (VP of Growth at AirOps).

Today, March 12th - 1:30 PM EST

Link to register below 👇

P.S: Anything specific you'd like to learn about combining outbound with LinkedIn Ads?

taplio

The Battle

Jérémy Grandillon

Michel Lieben 🧠

Followers

Posts

Engagements

Likes

Performance ScoreJérémy Grandillon's LinkedIn Performance

Performance ScoreMichel Lieben 🧠's LinkedIn Performance

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taplio

The Battle

Jérémy Grandillon

Michel Lieben 🧠

Followers

Posts

Engagements

Likes

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);}Jérémy Grandillon's LinkedIn Performance

Performance ScoreMichel Lieben 🧠's LinkedIn Performance

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Performance ScoreJérémy Grandillon's LinkedIn Performance