Charles Tenot

CEO @lemlist & lempire. I share what I learn as the CEO of a profitable SaaS growing to $40M to $100M+. Follow me to learn from the journey.

I'm a business generalist who loves tech & running high-performing businesses.

Happy to meet Sales professionals
If you're:
- An SDR or Sales Rep
- A Sales Manager, Head of Sales, or Head of Sales Development
- A VP Sales or CRO

And you work at a B2B company between 50 and 1000 employees,

I’d love to connect for 30 minutes to chat about outbound strategy, share ideas, and learn from each other.

Don’t hesitate to drop an email on charles@lempire.co

COO / General Manager

Growing lempire from 20M$ to 100M$ while generating 35%+ EBITDA

lempire products: lemlist, lemwarm, Taplio, Tweet Hunter, lemcal - more to come

Outbound is about to change forever.

Today we’re launching the most important feature we’ve ever built.

It’s called Signals.

And I believe it’s going to become a new industry standard.

Because here’s the truth: 

People don’t hate sales reps.

They hate being interrupted for the wrong reason.

But when timing and targeting are perfect...

Sales doesn’t feel like spam. It feels like help.

It feels like:
→ An expert spotting a problem you missed
→ A guide bringing a solution you didn’t know existed

That’s what we’re making possible with Signals.

It tracks buying intent across your accounts.
Or it finds the right ones for you, automatically.

Right now we detect 3 key intents:
→ Website visits
→ Hiring activity
→ LinkedIn engagement

And we’re adding 4 more in the next few weeks.

This is just the beginning.

Our long-term vision is simple:

Make intent-based outreach insanely simple
And partner with the best data providers for every signal

So now in lemlist you get:
→ 450M lead database
→ Email & phone enrichment (80% / 60% find rate)
→ LinkedIn, email, phone, WhatsApp, soon SMS
→ Deliverability tools built-in
→ AI outbound coach
→ And now... real-time signal tracking

We’re building the most complete outbound platform for small & mid-size teams.

Sign in & security

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Talks about #tech, #sales, #growth, #startup, and #revenueoperations

CEO @lemlist | Building the sales operating system teams actually want to use

Really excited to share that from today, lemlist is SOC 2 Type II certified 🔥

Until 2024, we had never lost a deal because we weren’t

Then in Feb 2025, we lost our first 50+ seats deal

Just because we weren’t certified

Then another one; then a third

That’s when we said ok, let’s do it

It took us around 4 months

In the meantime, we signed a few deals with an exit clause if we didn’t provide the report by a given date.
That gave us just enough time to complete it

We already sent the report to 10+ prospects who had been waiting for it

Excited to see what it brings

One more step on our way to becoming the go-to sales engagement tool for 5-100 sales teams

Big congrats to the team for pulling this off 👏

Here’s a real outbound email that helped an SDR book a meeting with the CPO of a $40M ARR business (us) 👇

Every line was about us.
→ It referenced a product we just acquired.
→ It made a strong connection between that move... and their product.
Overall, it didn’t feel like outreach. It felt like someone already in the loop.

Here’s why it worked:
→ The SDR shows deep industry expertise.
→ They understood our product roadmap and what matters to US
→ The email is sharp, clear, remaining short but with the right level of details.
→ They wrote the email like a real person, not a bot

No fluff, no gimmicks.

Just sharp thinking and human writing.

Most teams do the opposite:
They automate what should feel handcrafted.
That’s why reply rates are so low.

You can of course have templated micro-campaigns (50-150 leads size) for lower tier leads, but for top tier, you should go 100% human.

This is what the best teams do, they go smaller and deeper:
Fewer prospects.
More relevance.
Higher conversion.

Because ultimately it's better to achieve 10% reply rate on 20 leads (2 meetings) than 0.05% on 2000 (1 meeting)

Spammy cold emails are dead. But outbound is still the #1 growth lever when done right.

Here’s how it evolved over the past 7 years, and what it takes to win in 2025:

2018: Let’s automate follow-ups and send cold emails to as many people as we can

2019: You can personalize emails a lot more and even add videos to increase your reply rate!

2020: Limit cold emails to 30-50/day or you will land in spam. 
Warmup tools become a thing (👋 lemwarm)

2021: LinkedIn + Email gives 3x better reply rates

2022: Buy as many domains as you can to send 100K+ emails/month for $500/month

2023: Multi-channel is the new king. 
World-class Sales team combine LinkedIn + Email + Calls to maximise reply rates.

2024: AI SDRs & "email infrastructures" start flooding inboxes. 
Spam filters get tougher. Reply rate decreases.

2025: High-quality data becomes essential, high-volume senders spend their lives in the spam folder.

2026: Spray and pray is officially dead.

So what works now?

→ Reach the right person, at the right time, with the right message
→ Use the most effective channel
→ Rely on signals, not luck
→ Send fewer messages, but make them sharp
→ Sales teams act like experts — helping solve real problems
→ And they make serious money doing it

And no matter the year... two rules never change:
#1: You must stand out. That’s true in sales. It’s true in marketing. It’s just true.
#2: If you bring real value, results always follow. Always.


What’s your take, where do you see outbound going next?

4 good reasons why we 𝘀𝗵𝗼𝘂𝗹𝗱𝗻'𝘁 have bought Claap. And why we still 𝗱𝗶𝗱 👇



1 - We could have built it
Today, it's easy to build something that records meetings and gets transcripts. There are even APIs to do it in minutes.

But, software always looks simple at first.
That's why you see new tools coded overnight every day.

But the devil is in the details.
You can build a feature.
But building a product takes years.
Even with AI.
We could have built something that checks the box.
But we would have built 5% of Claap.

Claap is not about recording meetings.
It's about capturing conversations & interactions and turning them into value for Sales:
→ Reps coaching 
→ CRM filling
→ Get insights across all conversations

That's not a feature. That’s a product.


2 - Founders might just wait for the earn-out
Classic M&A risk. Founders join, stay 2 years, don’t push, then leave.

With Robin Bonduelle, Pierre Touzeau & Thomas Hernandez, we share the same ambition: build a global leader.
I’ve rarely seen a team more committed post-deal.

Robin even joined our SteerCo retreat last week... last minute.
That tells you everything.


3 - M&A = defocus
To succeed, you need focus. We learned that last year.
By focusing 100% on building the best engagement tool for sales teams, we’ve grown like never before.

But now the team is more mature.
And sometimes, creating a bit of chaos is what drives long-term growth.


4 - Integrations take forever

You pause your roadmap. You lose speed. You lose your edge.

We don’t want that. We’re not rushing integrations. 

We’re focusing on growing both products while creating integrations on selected use cases that makes sense, like
→ auto-create tasks from meetings
→ re-engage prospects at the right moment

Small, high-value use cases first.

---

You can always find good reasons not to do something.

No one ever got fired for not buying a company.

But if you still feel it’s right, even after listing all the cons...maybe you should do it.

"Clay might be the most impressive company of the last 5 years".
I said that to Bill over dinner last week. He asked me why.

There are a few reasons:

1️⃣ Resilience
They struggled for years before the so-called overnight success.
Just like Notion.
This is incredible to see Founders fight for their vision for years to ultimately being proven right.

2️⃣ Customer obsession
From day one, they knew they had something.
But they spent years meeting hundreds of growth people before cracking it.
They ended up with one of the deepest market understandings I’ve seen.
And made the most advanced growth techniques accessible to anyone.

3️⃣ GTM playbook
They turned partners into a growth engine.
Thousands of them, at scale. And they grew with them.
Their GTM model will be studied in business schools.

4️⃣ Category creation
When Gainsight created CX tools...
Clay created GTM Engineers.

5️⃣ Corporate decisions
They already gave a $20M secondary option to employees.
Very cool signal to reward people who committed early.

6️⃣ Brand
This one is more subjective, but I really think they nailed it.
The name, the visual identity.
It all feels fresh, clean, and modern, and it sticks.


---
Really excited to welcome Varun Anand, one of Clay’s co-founder, at our office tomorrow.

He is clearly one of the leading minds on where GTM is heading.

With the amazing Bill Stathopoulos from SalesCaptain, we will be talking GTM trends for 2026.

Join us (link in comments), limited spots

I once hired someone despite average references. He turned out to be a top performer with us.

That’s when it clicked for me: performance is often more about context than talent.

I’m a big believer in reference checks. 

I think they’re critical.

Some CEOs even say they care more about references than interviews.

But here’s the nuance:

Strong performers are situational.

The same person can be mediocre in one team... and absolutely shine in another.

Why? Because people aren’t good or bad by nature.

They’re good or bad depending on:
→ the culture
→ the manager
→ the mission
→ the stage of the company
→ the role itself

I’ve lived it myself. 
I was an average performer at Allianz.
I did the job, nothing more.
But, in my next roles, I went 10X.

Not because I changed overnight but because the context did.

So, how can you spot someone who might shine in your setup?

Here’s what I look for:

→ Deep curiosity: not just job titles, but someone who nerds out on stuff—even in their free time

→ Frustration patterns: people who stopped trying because no one listened

→ Short tenures in the wrong places: some people leave bad fits early. That’s not a red flag—it’s a green one

→ Obvious skills alignment: their strengths match your current needs and team dynamics

--
References matter. 
But they don’t tell the whole story.

Just landed in Paris from Tekpon AI Summit and in 1 hour, I’m going live with Taplio.

I’ll break down everything I’ve learned growing to 34K followers.

→ How I come up with ideas
→ How I organize my content
→ What drives the most engagement
→ What I’d do differently if I had to start from 0
→ How Taplio actually helps me
→ Even the stuff I don’t do (but probably should)

Already 1000+ signed up.

Why not you?

No alternative text description for this image

The real reason we bought Claap is 𝐍𝐎𝐓 because it's an invisible note-taker that fills your CRM automatically... It's much more evil 😈

Context is to AI what fuel is to a car.
Or what records are to a CRM.

No context = useless AI.

When you ask for public info like Einstein's birthday, ChatGPT nails it.

But when you ask:
→ When is this prospect planning to buy?
→ Who's the decision-maker in this account?
→ What competitor am I facing in this deal?

ChatGPT doesn’t know.

Because it wasn’t trained on that kind of private context.

That context lives in:
→ Sales calls and meetings (captured by Claap)
→ Emails and LinkedIn messages (soon captured by Claap)
→ CRM notes and fields (captured via Integrations)

Sure, you could connect all these sources yourself.
But good luck building a data architecture that scales across your entire GTM stack.

That’s not plug-and-play. That’s enterprise-level messy.

And even if you do it, there’s another problem:

Generic AI isn’t built for Sales.

It works by looking at "semantic proximity", fancy way to say: finding similar words.

So when you ask for "Competitors", it might surface "Rivals" or even "Enemies"
...instead of your actual competitor in that deal.

That’s why vertical AI beats general-purpose tools.

To make AI work in GTM, the entire chain needs to be built for GTM, not just the prompting layer.

That’s where we’re heading. 

Claap will become the AI context center for lemlist products.

What do you think of this plan? 😈

I was shared over 50 AI use cases by world-class GTM teams.
Only 10% are actually driving positive ROI.


Every team wants to add AI to their GTM stack.

But the "why" and "how" should come before the "what" ; and that part is often forgotten.

AI looks amazing in demos. It creates that "wow" effect.

But when it comes to turning prospects into customers... it often falls flat.

That said, a few use cases are actually working. 
And they all have one thing in common:

They help teams handle large volumes of unstructured data.

Here are use cases I’ve seen deliver results across top GTM orgs:

→ Data cleaning & smart filters
Use Clay, lemlist tables, or even a Gsheet linked to LLMs to streamline data cleansing or enrich your records.

→ Research automation
Clay (Claygents), Firecrawl, and similar tools can automate prep work and save hours.

→ CRM hygiene
Auto-fill CRM fields with tools like Claap to save reps time—and finally get data quality you can trust.

→ Prospect scoring
When you're handling high volumes, AI can score leads by combining structured and unstructured data.

→ Deal & account scoring
Top GTM teams do regular deal and account scoring using all touchpoints—calls, emails, signals—and AI helps scale that.

→ Lookalike identification
If you're still mapping your ICP, AI can help find similar customers so you focus on who’s likely to close next.
Some more advanced use cases are also showing serious ROI:

→ ElevenLabs (cc Jonathan Chemouny) built a voice agent using their own tech to guide inbound leads through their buying journey.

→ HubSpot and Pipedrive are testing AI sales agents to answer product questions.
 It sits between website and sales and from internal feedbacks I could get, it gives pretty interesting results.

I’m sharing more about this today at the Tekpon AI Summit.

I'll walk through what I learned from 20+ GTM leaders at Ramp, Revolut, Paddle, Alan, Pennylane, and more.

And over the next few weeks, I’ll keep posting examples here.

Please help 👇
What AI use cases have you seen deliver ROI ; or fall short?

DM me if you're working in a 5+ people sales team and want to chat use cases.

---
PS: this pic is from the event: great session with Bill Stathopoulos from SalesCaptain and Frank Sondors 🥓 from Salesforge 🔥

We did 40% off for Black Friday last year. But, we won't be doing it again this year for a few reasons.

Every year, PLG SaaS tools rush into Black Friday (or Cyber Monday) like it's a must.

We did it for 2 years. It worked "on paper".

But now we're done with it.

There are a few reasons:

1- Time-shift revenue vs. actual revenue

Yes, we got a spike in conversions.

But it just pushed people to convert earlier. 
After the deal... conversion dropped for a while.

This means we just time-shifted revenue.

2- It kills focus.

The team spent days prepping offers, landing pages, emails.

We'd rather have:
• Product & Tech improving the tool
• Marketing working on stuff that brings actual value to Sales teams

3- It impacts Brand perception

It sends the wrong brand message.

We're not a random tool you can find for cheap, and don't want to be.

We're a team of 50+ engineers based in Europe, building something great.

We want to build trust, not urgency.

4- It doesn't really help customers make better buying decisions

Buying software is not a 24h impulsive decision.

It's a choice that should help you for months, ideally years.

But a Black Friday offer puts pressure.

People buy because of the price, not because of the fit.

And that leads to the wrong kind of customers.

Most of the discounted users churned within a year.

---
We're not here to be the cheapest.

We're here to be the most helpful.

To deliver recurring value, over the long term, with an unparalleled product.

---

So this year, no Black Friday. 
No FOMO.
Just focus.

🙌

You don't need to send 1,000+ emails a month to close $1M in outbound sales.

Actually... the best reps I know send very few messages.

But each one is tailored with care.

Let’s do the math:
→ $1M target with a $40K ACV = 25 deals
→ Let’s say you close 1 in 4 = 100 qualified meetings
→ A good personalized outbound can get 5% reply rate
→ That means you need 2,000 leads
→ That’s just 9 accounts per day

Don’t tell me you can’t do that.

Every day:
→ Pick 9 accounts
→ Do your research
→ Write quality messages
→ Book one meeting every 2 days

Sales is not a spam game. It’s a discipline game.

The lazy shortcut is blasting 10,000 emails.

The smart way is caring enough to make 9 count.

Last minute plans are always the best.

Paris was not even supposed to be part of Varun Anand's Europe tour for Clay.

Thanks to SalesCaptain and TC9, it was added at the last minute.
And it turned out to be an amazing event, my favorite of 2025.

The energy was 🔥

A room filled with insanely talented GTM engineers building best in class systems to make outbound always more precise and targeted.

Varun said that he believes France has some of the top talents in Growth in the world.

He gave the example of our Growth Twins, Edouard and Louis, who are, he said, building GTM engines for Pigment comparable to what exists at Stripe or OpenAI.

My vision for 2026 is unchanged:

We need to keep improving GTM systems to make Sales more targeted and more valuable for buyers.

Spam is the enemy.

GTM Engineers should focus on building small and very targeted lead lists.

Or even better, focus on scoring and helping sales teams prioritize by giving them tools that make all the context available quickly so they can make better decisions on what to do next.

This is why Clay and lemlist work so well together and why so many customers use both.
→ Clay helps source, score and prioritize leads
 → lemlist helps engage across all channels including email, LinkedIn, phone, WhatsApp and SMS, which maximizes the chances to get buyer attention

Thanks to everyone involved yesterday and to everyone who joined.

--

cc Julia Guenier, Bill Stathopoulos, Jérémy Grandillon, Theo Kanellopoulos, Frank Sondors 🥓 Valentin W., Pierre-Baptiste Landoin

Most CEOs spend too much time with investors, but that's not how you create value for your business. 
Here’s what I believe a "perfect" CEO week looks like in a 100-300 people company 👇

I’ve been thinking a lot about how to use my time better.

What creates real value? What’s just noise?

Here’s what I’ve learned the hard way:

What doesn’t work:

→ Spending hours with investors. It’s mostly about optics. A 3-month doc + reaching out when needed is often enough.

→ Jumping into shiny new topics already owned by the team. You’ll probably slow them down more than help.

→ Sharing new ideas and articles every day. I’ve been guilty of this. It’s distracting. Focus beats stimulation.

What works:

→ 5 customer calls per week. Mix of long-term users, new wins, and churned ones. Especially those who fit your ICP.

→ 5 employee 1:1s per week. Not just your execs. Anyone. Just listen and understand what’s working and what’s not.

→ 5–10 hours of deep work on big bets. Future products. Strategic questions. The stuff no one else can do.

→ Use your own product or go through the full buying journey. Spot the frictions.

→ Work with your managers like a coach. 
Not status updates. Real problem-solving. Building trust.

 → Talk with other CEOs and advisors. 
Helps you zoom out and see things differently.

 → Take care of yourself. 
Walk. Exercise. Most good ideas won’t come from checking Slack.

→ Stay in touch with the market. A few newsletters. A few creators. Just enough to stay sharp. Not too much to lose focus.

One of our most successful 2025 features is a pure trojan horse. 
And most companies can steal this GTM strategy to accelerate growth.


When it comes to outbound, companies have 3 options:

1/ Work with a spreadsheet and forget 90% of follow ups

2/ Use their CRM, e.g. an "all-in-one" approach (Hubspot, Salesforce Engage)

3/  Go for the "best-of-breed" and use a tool like lemlist or Outreach

All-in-one tools are convenient but not really best-in-class in terms of features.

On the other hand, best-of-breed tools are the most powerful and give better results. 

But they have one big flaw, they require the team to adopt another tool.

And in 2025, teams want less tools, not more.

So what we did is simple: we decided not to position "against" the CRM.

We embraced it.

We embedded lemlist inside Hubspot and Salesforce.

All key jobs to be done... 100% available in the CRM:
→ Enroll leads in a sequence
→ Pause or remove from campaigns
→ Edit the campaign
→ Find phone, email, LinkedIn
→ Engage via email, phone, LinkedIn, WhatsApp
→ (soon) Find new prospects in target companies

No tab switching. No training needed. No resistance from reps.

We have still people using lemlist in lemlist.

Because our overall strategy is simple:
1️⃣ Build lemlist to be the reference for people who do outbound most of their days (SDRs)
2️⃣ Build lemlist "from CRM" for those who want to only use 1 tool
3️⃣ Build lemlist "for builders", via API, for those who want to build more custom use cases

---
It’s not the first time this strategy worked.

At Botify, we launched in the US selling SEO software.

We positioned it as complementary to the suite people already used.

That’s how we grew from $0 to $10M ARR in under 2 years.

---

If your market is crowded, don't fight for space.

Find the cracks.

Last week, I saved 2+ days as a CEO by using a vibe coding tool.

I’m convinced these tools will change how teams collaborate long before they ever replace Software Engineers.

Here are 2 moments where it made a real difference in my CEO role:

1. Pricing Iterations

Normally I’d open Notion or FigmaJam. 
Build a doc no one reads.
Instead, I used Lovable.
I built 5 versions of our pricing page. Using our real UI. In minutes.
Then shared with the team. Got async feedback. Clear and fast.

2. BI Dashboards

I needed specs for 2026 performance dashboards.
The usual way is a long doc, a meeting. 
People misunderstand half of it.

This time, I made a working prototype.
With fake data. Real filters. Actual charts.

The exec team played with it. Commented inside. I updated the prototype.

We had the final version 24h later.

Another example: when we shipped the Calling feature at lemlist, Maël Ezzabdi skipped the doc too.

He used a vibe coding tool to build a live prototype.
The team instantly got the vision. Built v1 in weeks.

So no, I don’t think AI tools will replace engineers anytime soon.
Actually, hiring Software Engineers has never been harder.

But I’m convinced they’ll change how we work together.

One visual beats 100 words.

Curious if others are seeing the same shift?

CPO @lemlist - On a mission to help ambitious businesses become big names!

Me in 2020: "Sh** the candidate rejected us, what did we do wrong?"

Also me, in 2025: "Good news, they understood our culture and said no."

And that's actually a win

Because a good culture is not about pleasing everyone.

It's not a one-size-fits-all.  It's a filter.

If you're trying to be for everyone, you end up being for no one.

I’m not saying losing candidates is good.

But losing the wrong candidates can be.

There are bad reasons to lose someone:
→ You were too slow
→ You failed to explain the role properly
→ Hiring manager didn't inspire
→ You didn’t show what’s exciting
→ You lowballed the offer

But here’s a good reason:
→ They felt it wasn’t the right culture or role for them

That’s alignment.
And that’s exactly what you want.

You’re not just hiring skill. You’re building a team that wants to be there.

Really happy to share that we hit a 9.1 eNPS score (+72)

This is another +0.2 improvement from 8.9 earlier this year.

It might not look like much... but to me, it means a lot.

I’m a competitive person. I love chasing growth.

But I’ve learned you don’t fully control success.

You do control the environment you build.
The people you hire.
The ones you keep.
The ones you promote.

So for me, this is the biggest win.
Seeing the team happy and thriving.

Now let’s make sure we keep that level of engagement as we scale.

We're still hiring:
→ Product designer with strong convictions
→ Experienced Software Engineers (🇫🇷 speaker)
→ Sales reps (anywhere 🌍)
→ Product / Content Marketers (sales mindset is a must)

Reach out if that sounds like you.

Everyone is excited about AI for sales, but very few are getting positive ROI.
And it’s not just my opinion. 

Kyle Poyar and Maja Voje surveyed 195 software leaders.

One of their key findings is scary but not surprising: 

→ AI in GTM is underwhelming.

Ahead of my talk at the Tekpon AI Summit, I spoke with 20+ leaders of top global companies (Ramp, ElevenLabs, Agicap, Pennylane, Paddle, Gorgias, Revolut and more.)

I had the exact same feedback:

→ Everyone has use cases with AI
→ But very few are convinced by the total net impact vs. costs (time spent, tools, etc.)
→ AI is great at some tasks, but disappointing at others
→ Adoption remains the #1 problem to make AI use cases ROI-positive


Ahead of the conference, here’s where it actually delivers value in sales:

→ Processing a lot of info, fast
Example: doing account research before meetings

→ Spotting buying signals in messy data
Example: detecting office openings in news articles

→ Auto-filling CRMs
Example: turning call transcripts into structured data with Claap

→ Turning chaos into clarity
Example: classifying companies as B2B or B2C from descriptions

→ Catching what humans miss
Example: flagging churn risk in emails and meetings

I’ve built a simple framework to figure out when AI helps, and when it fails to deliver.

I’ll also share 9 real-world use cases that are already driving ROI.

All of this is part of my session at the Tekpon AI Summit.

👋 I’ve got 3 free passes to give away.
➡️ Drop a comment and connect with me if you want one.

PS: you can read the full article from Kyle's newsletter
https://lnkd.in/evrRtxpV

Founder & Creator | Growth Unhinged

Bestselling Author | Empowering 9,500+ Companies with My GTM Method | B2B AI-GTM Consultant | Building AI Agents & Agentic Workflows | 73K LinkedIn | 25K Newsletter

Tekpon

Scale revenue with AI & tech

I decided to skip the traditional corporate path & start building in the AI x Sales space at 27. 
Here's the journey so far:

Age 18-21: Business school in Brussels, realized I needed practical experience
Age 22: Coding bootcamp + lucky Bitcoin exit gave me 50K to fund a world trip
Age 23: 12-country world tour learning new skills every month in a new country.
Age 24-26: Growth hacker roles at German startups, learned systems but felt unfulfilled 
Age 27: Co-founded ColdIQ with Mich
Age 28: Hit our first major milestones learning everything the hard way 
Age 29: Scaled to $6M ARR and became Clay's #1 global partner. Running a business that does $477K/month with 30+ team members across 4 continents.

It's been wild. Today through ColdIQ, we help B2B companies build AI-powered sales systems that work. 

We've run outbound for 300+ organizations and generated millions in pipeline.

The best part? We built this entirely remote with people I genuinely enjoy working with. 

Turns out you can have rapid growth AND life quality - you just need the right systems.

If you want to build your own AI sales agency, I teach everything in our ColdIQ Agency Accelerator, the exact playbook we used to hit $6M ARR in 2 years. 

From Clay workflows to hiring A-players to scaling without burning out.

If you're already doing $1M+ ARR and want help scaling your existing business, let's talk about our done-for-you services.

https://coldiq.com/

If you're not there yet, I share everything for free on LinkedIn and in our 7-day email course (in the featured section).

The AI x Sales opportunity is the biggest wealth creation event of our generation. The market is so massive that there's room for everyone to win.

Ready to start your agency? Join 130+ founders in our accelerator.

https://coldiq.com/accelerator-program

Alex Vacca 🧠🛠️

We analyzed 100K+ LinkedIn DMs to figure out what works.

Here's what we found:

1️⃣ Personalization beats volume every time

Campaigns with copy tailored to the ICP got up to 54.7% more replies.

We stopped blasting generic messages and started personalizing based on specific pain points.

We're using Clay for data enrichment and personalization, LinkedIn Sales Navigator for precise targeting.

Next month target: Scale personalization without losing quality. Why? Take some time to personalize your messages; it'll go a long way.

2️⃣ Short messages crush long ones

Messages under 150 characters had 22% more replies on average. We track which message length converts from each persona.

We aim to get our point across in as few words as possible - nobody's reading novels.

Next month plan: Test extra short hooks under 100 characters.

3️⃣ Contextual outreach destroys generic

Messages referencing recent activity (LinkedIn posts, role changes) saw +18% replies. We find relevant reasons to reach out every time.

Tool stack breakdown:

Clay for finding recent activity, role changes, company updates

LinkedIn Sales Navigator for activity monitoring

Expandi for sequencing

Zapier for workflow automation

Next month: Keep refining context triggers - when something works, you optimize it.

4️⃣ Warm approach sequences that build relationships

Connection requests sent after profile visits, post likes, or follows saw +30.2% acceptance rates. We make ourselves seen before reaching out.

Sequences with 3+ steps performed 42% better than single-message flows.

Different relationship temperatures get different approaches.

5️⃣ Multi-channel orchestration across every platform

Adding email follow-up after no LinkedIn reply lifted reply rates by 13.8%. We don't rely on LinkedIn only.

This is where most agencies lose pipeline - we track everyone who doesn't respond and re-engage via other channels.

6️⃣ Conversational copy beats direct pitches

The messages that actually work:

"Noticed you're hiring [role] - what's working for you?" (+18.2% replies)

"Saw your post on [topic], curious what are you testing right now?" (+19.3% replies)

"Saw you joined [company] - how's the first month going so far?" (+21.5% replies)

"We analyzed [findings] - worth sharing what others in your space are doing?" (+27.1% replies)

The results:

54.7% higher reply rates with personalized outreach

40%+ acceptance rates consistently

18%+ reply rates across campaigns

8%+ positive reply rates

The system works because it's not just LinkedIn messaging - it's relationship building at scale with contextual touchpoints where your prospects actually engage.

Want the full outbound playbook that's generated 54.7% higher reply rates? 👉 Comment "OUTBOUND" for our 7-day email series on the exact sequences we use.

Co-Founder @ ColdIQ ($6M ARR) | Helped 300+ companies scale revenue with AI & Tech | #1 AI Sales Agency

I turned 30 earlier this month.

I had no idea what I was doing for most of my twenties.

Moved countries. Started stuff that failed. Said yes to random things just to see what would happen.

Probably looked lost from the outside.

But here's what I think now:

Focusing too early is a trap.

I see people at 22 trying to "find their thing" and lock in fast. Pick the career. Pick the country.

But how do you know what to focus on if you haven't tried enough things yet?

You don't.

So you end up focused on the wrong thing. And you don't even know it.

That's worse than being "lost" for a few years.

Some people skip the messy phase. They lock in early. Look successful at 25. Then wake up at 30 wondering why they're not happy.

They focused, but not on the right things.

I needed those years of trying random things. Not because they all worked. Most didn't. But because now I actually know what I want.

I know which friendships matter. Not trying to keep up with 50 people anymore.

I know where I want to live. Done being the eternal nomad.

I know what we're building with ColdIQ. Done chasing every shiny opportunity.

We tested a lot in 2025. New offers. New markets. Some worked. Some didn't.

But now the picture is clear. We go into 2026 knowing exactly what to double down on.

You can't focus on the right thing until you've explored enough to know what the right thing is.

To the next decade 🥂

lemlist hit $37M ARR.

Here’s the outbound engine behind it (and why it works so well)↓

Most people think lemlist grew by sending better cold emails.

They didn’t.

They built a system that turns content → intent → enriched data → personalised outreach at scale.

Here’s the exact workflow:

1️⃣ Content that attracts their ICP (not vanity content)

An influencer or internal creator publishes on LinkedIn - but not just any content.

It’s written to attract one specific persona with a problem lemlist solves.

Every comment, like, and share = a signal.
A signal that someone cares about the topic.

They use:

- Jungler to scrape all post interactions
- LinkedIn for content publishing

Because people are already familiar with their brand, reply rates are way higher than pure cold outreach.

2️⃣ Data routing & enrichment

Not every engager is worth contacting.
So they have a system to score, clean, and enrich.

They push all extracted contacts through:

- n8n for data routing
- Clay as the data hub (enrichment, scoring, workflow automation - all in one place)

Scoring includes:

→ Job title relevance
→ Engagement type
→ ICP match
→ Buying power indicators
→ Existing customer check
→ Tech stack + initiatives + recent activity

Here’s the thing nobody talks about:

If the enrichment is bad, the personalization fails.
If the personalization fails, the whole system collapses.

This is where lemlist invested the most time - and where most teams cut corners.

3️⃣ AI personalization & multi-channel outreach

Personalization isn’t “{first_name}, loved your post!”

They use:

lemlist’s AI variables → genuine first-lines for every prospect
Multi-channel sequences → email + LinkedIn for maximum reach

A typical opener:

“Hey {{first_name}}, saw you engaged with our post on {topic}. Looks like you’re focusing on {initiative} — happy to share what’s worked for us.”

Warm context + real personalization + multi-channel = consistent replies.

Teams spend hours “perfecting” cold emails.
lemlist spends hours perfecting context - and lets AI scale the rest.

4️⃣ Meeting booked

Warm, relevant outreach performs.

This is one of the most efficient ways to:

→ Warm up leads
→ Segment the highest quality ones
→ Gently ping them with context at exactly the right time

This is one of lemlist's highest performing outbound plays. It's also a play we love to run at ColdIQ.

They've spent months testing and optimizing this workflow to run on autopilot.

The compound effect takes time, but when it kicks in, it's massive.

If you want to implement something like this - we'll literally run this entire workflow for you, along with other high-converting GTM plays.

Drop me a DM👇

We just crossed $6,000,000 ARR.

Here's the tech stack that made it happen ↓

1️⃣ Content & Inbound

We generate over 100 warm leads per month via LinkedIn.

These come from my account (45,600+ followers) and the rest of the ColdIQ team (230,000+ followers).

I use:

- Scripe for post ideas + analytics
- Notion as my content calendar to keep me organised

We generated ~50M impressions on X last month, which is honestly wild. And for this we use:

- Typefully to visualize & draft threads: makes the whole process way smoother

I am getting some momentum behind my YouTube, so at the moment I use:

- Two Sony FX30 camera for filming
- Tella for screen & audio recording (super clean output)
- vidIQ to gain inspiration from successful videos, basically reverse engineering what works

We drove 102,000 visitors to our website in the last 90 days. 35,000+ come from SEO alone. We use:

- Ahrefs for keyword research (can't live without it)
- Webflow's CMS to host/publish our articles
- Surfer to optimize our copywriting for search engines

We have 7,000+ subscribers to our newsletter, and growing. We use:

- beehiiv to send our welcome sequence & weekly emails

2️⃣ Outbound Engine

- We identify website visitors with Instantly.ai & Vector 👻
- Based on their firmographics + page visit, we:

→ Email them via Instantly.ai

→ or connect + send voice notes via lemlist

- more personal touch

- For data: Prospeo.io, LeadMagic, Clay, FullEnrich
- For AI research & personalization: ChatGPT, Claude
- For deliverability: a mix of Gmail + Outlook inboxes

3️⃣ Ops & Project Management

- Everything runs in Airtable
- We automate with n8n, Make or Relevance AI, depending on what we're trying to do
- Big-picture process flows? We map those in @Puzzle
- Internal comms → Slack

4️⃣ Sales & Closing

- Calls get booked through Default
- We use Attention to record & summarize meetings
- Proposals: Qwilr (clean, professional, gets signed)
- Banking: Mercury
- Contracts: PandaDoc
- Payments: Stripe

We've spent months testing, tweaking, and optimizing this entire stack to work together seamlessly.

Tech moves fast. Really fast.

New tools drop every week, and what worked 6 months ago might not be the best option today.

I break down the complete stack + how we actually use these tools on my YouTube.

Subscribe here → https://lnkd.in/dKsZpY2D

What tools are you running? Drop them below 👇

Behind Lemlist’s $30M ARR growth engine.

... and 20,000 paying users.

Michel Lieben 🧠 sat down with Charles Tenot, CEO of Lemlist, to go behind the scenes of their growth strategy.

Let me build this out properly for you. Here's the full breakdown:

1️⃣ TRAFFIC GENERATION

lemlist gets over 200,000 website visitors every month. But they don't rely solely on one channel.

Here are the channels they use to drive that traffic:

a. SEO: 15–20% of signups come from search
→ They dominate keywords like "cold email templates" and "email outreach tools"
→ 300+ blog posts targeting bottom-funnel search intent

b. YouTube: 14.2K subscribers, and 393 videos
→ Educational content on cold email, outbound sales
→ Tutorial videos showing actual lemlist workflows

c. LinkedIn: Combined reach of 250K+ followers
→ Team members consistently post about outbound strategies
→ Share customer wins and case studies weekly

d. Paid Ads: €20K/month to Meta, Google, and LinkedIn
→ Google: Target high-intent keywords like "mailchimp alternatives"
→ Meta: Retargeting website visitors with social proof content
→ LinkedIn: ABM campaigns targeting sales leaders at 50-500 employee
companies

e. Webinars: Expert-led sessions on outbound and sales
→ Weekly live sessions with 200-500 attendees
→ Guest speakers from successful B2B companies
→ Replay content distributed across all channels

f. Affiliates: Partners and customers earn a % for referrals
→ Agency partner program with 30% recurring commissions
→ Strategic partnerships with complementary SaaS tools
→ Customer referral program with account credits

2️⃣ LEAD CAPTURE

lemlist turns traffic into signups, fast.

They convert 7–8% of 200K+ monthly visitors (that's 14,000-16,000 signups monthly).

Here's what increases those conversion rates:

Free trial strategy:

→ No credit card required
→ Full access to the platform
→ 14-day trial with onboarding sequence
→ In-app tutorials and success metrics tracking

3️⃣ ACTIVATION & ONBOARDING

This is where most SaaS companies lose people, but lemlist nailed it:

→ Day 1: Welcome email + calendar booking for optional onboarding call
→ Day 3: "Send your first campaign" tutorial with templates
→ Day 7: Case study of similar company + advanced features demo
→ Day 10: Personal video from Guillaume + upgrade incentive
→ Day 14: Trial ending soon + success metrics from their usage

4️⃣ CONVERSION TO PAID

Here's where the "reverse trial" magic happens:

→ Soft paywall: Free users hit email limits naturally through usage
→ Value demonstration: Show ROI metrics before asking for payment
→ Multiple upgrade paths: Self-serve pricing page OR book sales call
→ Usage-based triggers: "You've sent 95/100 free emails this month"

The numbers:

→ 200K monthly visitors
→ 95%+ monthly retention rate
→ €150 average monthly deal size
→ 7-8% conversion to trial (14K-16K trials/month)
→ 15-20% trial-to-paid conversion (2.1K-3.2K new customers/month)

What do you think lemlist should add to grow even faster?

Content helped ColdIQ hit $6M ARR.

And this workflow turns every single post into pipeline.

We built a system that converts LinkedIn engagement into qualified meetings.

Here's the breakdown we use at ColdIQ:

STEP 1: CAPTURE ENGAGEMENT IN REAL-TIME

Every like, comment, and profile view gets tracked automatically.

When someone likes OR comments on your post they're basically telling you they actually care about what you're talking about.

We use Trigify.io and Teamfluence™ to monitor all LinkedIn engagement signals.

Most people get that engagement and then just move on to the next post - we actually do something with it.R

STEP 2: INSTANT ENRICHMENT

The moment someone engages, Clay pulls full contact and company data.

Job title, company size, tech stack, funding rounds, hiring signals - all of it happens in seconds.

STEP 3: AI QUALIFICATION

Not everyone who likes your post is actually a good fit prospect.

We use ChatGPT and Claude to score each contact against our ICP criteria.

- Low fit? Filtered out immediately
- High fit? They move to the next step

The AI looks at things like:

- B2B vs B2C
- Geographic fit
- Company size match
- Estimated customer lifetime value

STEP 4: CRM DEDUPLICATION

Before we do anything, we check: is this person already in our system?

Already a customer? Already in active conversations? Skip them completely.

New contact? Push to sequence.

The fastest way to look like an idiot is cold emailing your existing customers.

STEP 5: MULTI-SOURCE EMAIL VERIFICATION

We waterfall through Prospeo.io, FullEnrich, and LeadMagic until we get a verified email.

No single provider has 100% coverage.

But stack three of them together? You're getting close to 95% hit rate.

STEP 6: PERSONALIZED OUTREACH ON AUTOPILOT

Each prospect receives a tailored message via Instantly.ai that references the exact post they engaged with.

Not generic "Hey {firstName}" nonsense.

It's contextual: "Saw you engaged with my post about Clay workflows - we just built something similar for a client in your space that books them 2-3 meetings per week."

STEP 7: MEETING BOOKED

This system generated 144 meetings for us in a single month.

And it runs 24/7 without human intervention because:

- Every piece of content becomes a lead magnet
- Every engagement becomes a qualified opportunity
- The entire conversion happens automatically

If you're posting on LinkedIn without this system you're basically just creating content and hoping meetings happen (which they won't).

That's not how it works in 2025.

The companies winning are the ones that built actual systems to convert attention into pipeline.

Are you tracking your LinkedIn engagement right now?

(We can build this entire workflow for you, plus show you the other plays that got us to $6M ARR)

P.S: Tools don't book meetings. Systems do. And this is the system that's working right now.

OpenAI just sent us this award for passing 10 billion tokens.

Here is what I learnt: being too smart is slowing you down.

The smartest people I know are the slowest to start.

- They read about AI.
- They follow the news.
- They watch the tutorials.

But they don't build anything.

Their logic:

"Why learn this if it's outdated in 6 months?"
"Why build this if a new model does it better?"
"Why start now if everything keeps changing?"

Sounds smart.

But it's actually not.

Here's what actually happens when you use AI every day:

- You learn how it really works.
- You find what it's good at and what it sucks at.
- You build intuition you can't get from reading.

Yeah, some stuff we built 2 years ago is completely outdated and we constantly need to replace old workflows we built.

That's the price to pay but despite that we still learned more than the people who waited and never built anything. 

When a new model drops, we figure out what we can do with it.

Because we already understand the fundamentals.

The people still waiting?

Starting from zero and probably will tell themselves that they will start when GPT 8 will release.

The world moves fast.

You can watch it move.
Or move with it.

10 billion tokens later, I'm glad we moved.

Stop waiting for things to stabilize because they won't.

Just start building.

Everyone else is also just figuring it out.

4 GTM agents that save 2-5 hours per client every day.

They run:

Prospecting, content
AND market research on autopilot.

Most teams think AI is about writing faster. It's not.

It's about eliminating the 80% of GTM work that never should've been manual in the first place.

Here's the system:

AGENT 1: LEAD RESEARCH AUTOMATION

Manual prospecting is dead.

Every company profile gets captured, enriched, and scored automatically.

Pipeline:

- GhostGenius captures profiles
- We filter by credibility signals (200+ followers, real website, actual activity)
- GPT scores each profile against our ICP (in real time)
- LinkedIn IDs dedupe contacts so we never hit the same prospect twice

Clean, qualified prospects → straight into Google Sheets for outbound.

AGENT 2: LOCAL PROSPECTING ENGINE

Apify pulls local businesses from Google Maps.
Raw Google Maps data is a mess. Half the info is missing or outdated.

The fix:

- Google Search API fills missing metadata
- We scrape each website for keywords, offers, tech stack
- GPT classifies and enriches the business profile
- We extract missing emails, numbers, contact pages

Export to Airtable or Sheets → done

This turns low-quality data into sales-ready records.

AGENT 3: BRAND CONTENT GENERATOR

Drop a brand brief into a Google Form. Wake up to:

- LinkedIn posts
- Carousel copy
- Newsletters
- Hooks
- CTAs
- Variations
- TOV matched drafts

All written in your style, using your positioning.

Drafts go straight into Notion or Google Docs, ready for a 10 minute edit.

AGENT 4: REDDIT INTEL COLLECTOR

This one is my unfair advantage.

Most GTM teams ignore Reddit.
But it’s where your prospects say the things they’d never admit on a sales call.

Pipeline:

- Input a brand or website
- GPT identifies ICP signals
- Reddit API scrapes relevant threads
- GPT summarises pain points, the language prospects use, their frustrations, what they actually care about
- A daily insight report sent to your inbox

This is the closest thing to reading your market’s mind.

THE RESULT: AUTOPILOT PIPELINE

These 4 agents work together to create a system that runs 24/7:

1. High-fit leads → already in your CRM
2. Weekly content → drafted before you wake up
3. Market intelligence → delivered before your first coffee
4. Zero hours wasted on research, scraping, or repetitive admin

You’re not “doing more.”
You’re just letting the system do what humans shouldn’t.

And here’s the real shift:

> Companies scaling in 2025 aren’t hiring more SDRs.
> They’re eliminating the work SDRs used to do.

If you’re still manually researching prospects and writing content from scratch, you're working 10x harder than necessary.

We build these exact workflows in n8n - plus the other automation plays that save 15+ hours per week, per team member.

Which one are you building first?

4 GTM n8n Agents 

Here’s what our numbers look like today:

→ $6,000,000 ARR
→ $40k–$80k new MRR added each month
→ Predictable pipeline month after month

All powered by a GTM funnel that took us 18 months to refine.

Here’s the full breakdown, the exact one we still use internally.

1️⃣ Awareness (the volume engine)

Not every impression is equal, but volume absolutely matters.

Here is how we look at it:

Visibility → Leads
Leads → Meetings
Meetings → Proposals
Proposals → Revenue

Here's what we're generating right now:

100,000+ quarterly website visits (SEO + Paid)
2.5M–3M monthly impressions on LinkedIn
5K–20K monthly YouTube views

Tools:

→ Taplio, Scripe, Notion (content)
→ AirOps, Ahrefs, Surfer (SEO)
→ Fibbler, arcadsAI (paid)

2️⃣ Interest

Getting seen is easy. Getting buyers to take action is what separates good from great imo.

So we increase conversion rates by:

→ Running monthly webinars (warm nurturing at scale)
→ Sharing lead magnets that educate
→ Using one-step smart forms to auto-route leads instantly
→ Identifying anonymous visitors and re-engaging them (this one's a game-changer)

Tools:

→ Instantly.ai, Vector 👻, Midbound (visitor ID)
→ Default (automated routing)

3️⃣ Consideration

Attention doesn't convert unless buyers understand what you do.

So we:

→ Built multiple VSLs that explain the offer clearly
→ Share success stories with full breakdowns of how we did it

Tools:

→ Wistia (VSL hosting + video testimonials)

4️⃣ Conversion

At this stage we talk to more qualified leads, more often.
Here's how we maximize conversion:

Email nurture sequences keeping the pipeline warm
Automated outreach to high-potential accounts
More open slots for sales calls
Consultative selling on Google Meet

Tools:

→ Clay, OpenAI (lead scoring + segmentation)
→ Customer.io, lemlist, Instantly.ai (outbound + nurture)
→ Attention, Attio (meeting intelligence, pipeline analytics)
→ Qwilr, PandaDoc (proposals, contracts)

Is it perfect? No.
Does it work? Very well.

This GTM system powers our growth month after month. We're always iterating, always improving.

What would you improve? 👇

The sales flow that generated $966K ARR.

Nearly $1M in new revenue in 30 days.

Most people see the content - the LinkedIn posts, the videos, all of it. 
But content is just the front end.

Behind the scenes, there's a whole system.

The team posts across LinkedIn daily.

But none of that means anything without closers who can convert attention into pipeline.

That's where Dujam Dunato and Jan Rasmussen Mitjana  come in.

They're the ones handling inbound, qualifying leads, running calls, and closing deals at scale.

Here's the exact sales flow they used to generate $966K ARR in one month:

1/ Pre-call qualification

We only book calls with prospects we know we can help.

Qualification happens automatically through:

- Inbound routing systems
- Video testimonials that build trust before the call
- Website assets that pre-educate prospects

LinkedIn connection automation for long-term nurturing

Tools:

↳ Default - auto-qualification + routing
↳ lemlist - LinkedIn connection automation
↳ VSL - makes sure prospects understand our offer before speaking to us

This removes 90% of the time-wasters and lets the team focus on revenue-critical conversations.

2/ Discovery & research

Before any call, we prepare - but we don’t do it manually.

We use:

a. Automatic prospect intelligence via Clay + Zapier
b. Funding stage + headcount research
c. Stakeholder identification + role tenure
d. Tracking strategic hires, initiatives, and timing signals

Tools:

↳ SPICED (Winning by Design) - call structure
↳ Clay + Zapier - pre-call research + aggregation
↳ Fireflies.ai - real-time AI note-taking + CRM automation
↳ Qwilr - digital sales room + proposals

This means reps walk into every call fully briefed without lifting a finger.

3/ Follow-up & nurturing

For leads who aren’t ready to sign immediately, we run:

a. Automated follow-up sequences with real value
b. YouTube video follow-ups (no boring text-based emails)
c. Multi-threading across LinkedIn to engage all decision-makers

Tools:

↳ Customer.io & Attio - automated follow-ups
↳ LinkedIn - multi-threading workflows
↳ YouTube content from me & Michel - authority-led nurturing

This keeps prospects warm without our team writing endless manual replies.

4/ Why this closed $966K in one month

Qualification: Only the right people reach our closers
Education: Prospects arrive informed, reducing friction
Automation: Reps spend their time selling, not admin

Content: LinkedIn + YouTube turn strangers into warm, ready-to-buy leads

If you have any questions, feel free to drop any of the guys above a message!

138 meetings from 144 LinkedIn posts (that's almost 1:1).

Here's our $6M ARR workflow:

Step 1: Content volume that converts

We published 144 LinkedIn posts last month. Not random content, everything's built around ICP pain points.

We're using Taplio and Scripe for inspiration, but we're analyzing what books meetings. We look at hooks, visuals, and formats from posts that converted.

Step 2: Paid amplification with actual ROI tracking

$5,100 in LinkedIn Ad spend generated 155K extra impressions at $33 CPM. But we ONLY boost organic posts that have already booked meetings.

We track which persona converts from each post type, then push those winning posts to that exact audience.

Step 3: Intent capture across every touchpoint

This is where most agencies lose pipeline. We're tracking everyone who shows intent but doesn't book.

Tool stack breakdown:

Website visitors: Instantly.ai, Midbound Vector 👻 and Common Room for anonymous visitor identification.

LinkedIn engagement: Trigify.io and Teamfluence™ for social signal monitoring

Step 4: AI-powered lead scoring in Clay

Every lead gets routed to Clay for intelligent scoring. We use Claygent for lead research, then OpenAI to segment into 3 tiers based on fit and timing.

Different tiers get different outreach strategies. A Tier 1 lead gets way more personalization than a Tier 3.

Step 5: Data enrichment that works

Prospeo.io and LeadMagic for emails, FullEnrich for phone numbers - all happening inside Clay so we don't lose context.

Step 6: Multi-channel re-engagement based on score

This isn't random outreach. Every message is contextual, every touchpoint provides value.

The results that matter:

- Made us 557k in revenue for October
- Team grew to 30+ FTEs
- 750+ meetings booked in 2025 already
- One client: $272,600 closed at 7X ROAS in 90 days

The system works because it's not just outbound - it's orchestrated revenue generation across every touchpoint where your buyers show up.

We're adding this GTM workflow FREE for the next 3 ghostwriting clients (15 of 18 spots already taken). Comment 'CONTENTIQ' to grabs yours ☝️

How I'd build a repeatable outbound system if I had to start from scratch:

(There's a public database of your competitor's churn reasons... and most teams aren't using it)

1/ I'd start by scraping competitor reviews

You can use G2. Or Capterra. Or Trustpilot.

And it's full of pain points, written by people actively looking for a better option.

Focus on 2–3 core competitors with a decent number of reviews.

It's a goldmine. You'll find everything from UI complaints to missing integrations to slow support.

Tools you can use:
- n8n / Make (for scraping)
- Apify / PhantomBuster (pre-built scrapers)

2/ I'd extract pain themes using AI

We don't read these manually.

We use ChatGPT to group complaints into themes:
- Feature gaps
- Support response time
- UX or onboarding issues
- Security concerns
- Pricing

You now have a live database of what your prospect hates about their current tool.

Tools you can use:
- ChatGPT (for clustering complaints)
- Google Sheets (for organizing themes)

3/ I'd align those complaints with my actual positioning

Map those complaints to your actual value props.

Here are 3 examples:

a. If their reviews mention "hidden fees," and your pricing is transparent, lean into that.
b. If they complain about integrations you support, name them.
c. If support is a weakness and you have a live-chat SLA, say it.

Now you're not just pitching. You're presenting a clear solution to a known frustration.

Tools you can use:
- Loom (for quick demo videos)
- Your pricing page / integration docs (as proof points)

4/ I'd launch targeted outbound

Once we know who's unhappy and why, we push that data into:
- Clay (for enrichment + personalization)
- Instantly.ai (for sending)

The messaging angle is already validated, and the frustration warms the list.

You're simply showing up with a better option.

Tools you can use:
- Clay (enrichment + personalization)
- Instantly.ai / Smartlead (for sending)

5/ I'd automate it into a system that runs weekly

We've built versions of this using:
- n8n (for scraping)
- ChatGPT (for clustering complaints)
- Google Sheets (for inputs)
- Clay + Instantly.ai (for execution)

It runs weekly. We review angles, update copy, and refresh the list.

Once it's live, it becomes one of your highest-converting outbound motions.

Why? Because you're hitting real pain points with a proven better solution.

Tools you can use:
- n8n / Make (workflow automation)
- ChatGPT (analysis)
- Google Sheets (central hub)
- Clay + Instantly.ai (execution)

6/ I'd run this consistently

This works across industries, and especially well in crowded SaaS categories.

But it requires setup. And it requires letting the system run long enough to see results.

Give it a shot.

P.S: Questions? Drop them below or DM me. Happy to unpack any step. 👇

We scaled to $6M ARR.

If I had to start again, this is what I’d build first.

Most people overcomplicate GTM.

They chase channels. Growth hacks. Headlines.

But if you strip everything back, early-stage growth comes down to a few simple systems done well.

Nothing fancy.
Nothing loud.
Just the foundations that actually move pipeline.

If I was starting from zero again, here’s exactly what I’d put in place.

1️⃣ Email infrastructure

I wouldn’t touch ads.
I wouldn’t build a giant content engine.
I’d start with email, because it scales the fastest when you're unknown (yet).

The setup is simple:

→ 20 secondary domains
→ 40 mailboxes
→ 20–25 emails per mailbox per day

Warm everything up for two weeks.
Authenticate properly (SPF, DKIM, DMARC).
Rotate domains every 9–12 months.

Do this right and 95%+ of your emails land where they're meant to: the primary inbox.

2️⃣ Lead signals

Most people email too early.

They reach out when they want the meeting, not when the buyer is actually looking.

So I’d track 10+ buying signals first - simple things that show intent:

- Downloads
- Hiring spikes
- Website visits
- Funding rounds
- Tech stack changes
- Competitor research
- LinkedIn profile views

The goal is timing.

You don't need more leads.
You need leads who are ready.

3️⃣ Sequence timing

For SMB:

5–8 touchpoints across 30 days.
Shorter gaps. Faster signals.
A simple mix of email + LinkedIn.

For enterprise:

10–18 touchpoints across 60 days.
More education.
More channels.
Less pressure.

4️⃣ GTM workflows

This is where most teams fall apart.

Deals ghost
Leads sit untouched
Handoffs get messy
Nobody knows who's owning what

I'd set up 6 workflows on day one:

→ Ghosting (auto-close inactive deals)
→ Discovery nurture
→ Proposal follow-up
→ Closed-won onboarding
→ Lead routing
→ AE handoff

It’s not exciting work.
But it removes chaos.
And chaos is what kills early GTM.

5️⃣ The metrics that matter

People still obsess over open rates.
They don’t matter.

Track reply rate.
Track positive replies.
Track meetings booked.
That’s it.

Industry reply rate is 1–5%.
Good is 10%+.
Great is 25%+.

PRR tells you everything you need to know:
How many people said yes.

Nothing else matters.

6️⃣ Reporting

If you want pipeline to compound, you can’t just “hope it works.”

I’d check the same dashboard every day:

Deliverability >95%
Reply rate 15%+
Positive replies 1–5%
Meetings booked
Show rate
SQL conversion
Close rate
Spam rate
Bounce rate
Domain reputation

If I had to start again, I wouldn't try to do all the things. I'd build these foundations, stay patient, and let the system do its job.

Everything else comes later.

What would you add to this list? 👇

P.S. Kenny Damian crushed it putting this GTM cheatsheet together - feel free to send a DM if you need help with this.

AI agents are replacing entire GTM workflows.

So I tested 50+ of them to see which ones perform.

Most perform great in demos.

Then I plug them into our workflows and... not so much.
So I ran them through everything we use at ColdIQ.

Research, enrichment, outbound, scoring, support - the whole lot.

Some were fine. Most were absolute garbage.

So we consolidated everything the team found, compared notes, and built a list of the ones that consistently delivered.

Here's what worked... ↓

1️⃣ Sales Agents

- Artisan
- Valley
- Topo (YC W24)
- AiSDR

2️⃣ Research Agents

- Claygent
- Airtop
- Attio

3️⃣ Customer Service Agents

- Intercom
- Parahelp
- Forethought
- Sierra

4️⃣ Visual Agent Builders

- n8n
- Relevance AI
- Lindy
- Wordware (YC S24)
- Dify
- Taskade

5️⃣ Marketing AI Assistants

- Tome
- Aomni
- Copy.ai
- Jasper

6️⃣ AI Executive Assistants

- Fyxer AI
- Tasker AI
- Shortwave

7️⃣ Enterprise Development Platforms

- StackAI
- Microsoft Autogen
- LlamaIndex
- CrewAI
- LangChain
- Cohere

8️⃣ Ready-Made Agent Libraries

- Beam AI
- Sintra
- Lyzr AI

What agent tools am I missing from this list?

Drop them in the comments, always looking to test new ones.

P.S. Give Kenny Damian a follow. He's the goat when it comes to AI agents.

Ai Agents Categories

ColdIQ made 557k in revenue last month.

80% came from content.

Not ads.
Not cold calling.
Content.

Last month we launched ContentIQ - the system behind all of it.

Most people talk about “posting more.”

I want to show you what actually drives revenue.

Here’s the full breakdown of how we do it at ContentIQ 👇

1️⃣ Content foundation (the part everyone skips)

Before the engine runs, we build the infrastructure.

Phase 1: Onboarding

The non-negotiables:

- 1-hour strategy call → sharpen positioning
- Content audit → reality vs perception
- Voice capture → so your content sounds like you
- ICP definition → clarity = revenue
- Content calendar → narrative arcs, not random posts
- Community channel setup → where engagement compounds

Tools:
Gmail, WhatsApp, Slack
Attention.ai, Circleback, Loom
Clay, ChatGPT
Asana, Notion, Monday

This foundation is 70% of the results.

Phase 2: The content engine

Two tracks running in parallel:

Track 1: Creation

- Bi-weekly founder interviews
- Extract ideas, frameworks, stories
- Weekly content plans
- Graphic design
- Approval flow

Track 2: Production

- Finalised + delivered in 2–3 days
- Speed = momentum. Momentum = revenue.

Tools:
Canva, Figma, Adobe
Taplio, Scripe
(plus everything from Phase 1)

2️⃣ Lead tracking & scoring

Most companies post and hope for the best.

We post and measure.

We track:

- Profile views
- Impressions
- Comments
- Saves
- DMs (highest intent)
- Engagement depth

We run ICP 1 and ICP 2 separately.

Because:

A profile view ≠ a profile view.
A comment ≠ a comment.
A DM ≠ a DM.

We score each action so we know who is engaging and how qualified they are.

Tool: Teamfluence™

3️⃣ Automated outreach (the secret sauce)

All that engagement data flows into the automation stack.

Here’s what happens behind the scenes:

1. High-intent signals identified
2. Lead enriched with additional data
3. ICP-fit scored
4. Personalised outreach triggered
5. Across email + LinkedIn

The system does the work.

Tools:
Clay
Attio
Common Room

4️⃣ The Funnel Architecture

Most teams do ONE thing and wonder why they plateau.

Here’s the full blueprint:

→ LinkedIn content = Awareness + credibility
→ Engagement tracking = Intent identification
→ Automated outbound = Intent → conversations → revenue

When all three connect, you stop “posting content”…
and start building a pipeline engine.

---

5️⃣ The offer

For the first 10 signups to ContentIQ, we’re giving you:

The entire automated outreach machine
+
The full content engine.

Not just posts.
Not templates.
The whole workflow that built our business.

Here is the link: https://lnkd.in/ddStnRu3
(And yes… this is where it gets really good 👀)

This one tool rewired our entire workflow ↓

And saved 20 hours a week.

Two months ago, we rolled Fireflies.ai into our operations.
Not for transcription (they've already won that category),
but for meeting intelligence and workflow automation.

Here’s exactly how we’re using it:

1️⃣ Walk into every call already briefed

Before a meeting even starts, Live Assist pulls up:

→ Your past conversations
→ Key decisions from the last call
→ Open tasks + commitments
→ Context you forgot you even needed

You're not going through old notes or trying to remember what you said last week.

You just show up ready (game changer for prep).

2️⃣ Real-time suggestions during the call

This is the part that genuinely changes how you operate.

Live Assist listens live and surfaces:

→ Talking points
→ Objection handling
→ Context from previous calls
→ Background details you missed
→ Prompts tied to what the client is saying

And if you need something specific mid-call,
you can actually ask the agent to give you an answer.

3️⃣ Zero manual notes

Your team stays focused on the client.
Fireflies handles the note-taking:

→ Clean notes
→ Organised
→ Time-stamped
→ Accurate
→ Updating as the call unfolds

No one is typing.
No one is distracted.
Nothing gets missed.

4️⃣ Instant client summaries

Call ends → Summary appears.

→ Key points
→ Next steps
→ Decisions made
→ Assigned action items

We push this straight into Slack so everyone stays aligned.

And we also send all the data to a Claude project so we can keep track of what's happening with every client.

We're building a lot of internal tech at ColdIQ. And Fireflies has a Claude MCP integration.

So now we can query meeting notes across the entire business directly from Claude.

- "What did we promise this client last month?"
- "What objections came up in our last 10 sales calls?"
- "What feedback did prospects give about pricing?"

Just ask and you get the answer in Claude directly.

This is why we’re scaling Fireflies.ai across every team.

If you want the link to test Live Assist yourself,
drop a “Fireflies” below and I’ll send it over. 👇

How we use Fireflies 

We didn’t expect much from this ABM campaign.

But in 90 days it generated $2M in pipeline and $300K in revenue.

Most teams think ABM is about creating more:

→ More impressions
→ More retargeting
→ More pressure

But that wasn’t the problem.

They were struggling because the right people didn't trust them yet.
So instead of doing “more,” we tried doing the opposite.

1. We started with the customers who already chose them.

We pulled their best deals and looked for patterns.
Not just the big names - the ones who actually got the most value.
Those patterns became our targeting strategy.

2. We built a small, intentional target list

Not a huge TAM spreadsheet
Not thousands of cold accounts

Just 2,000 that looked like their best buyers

3. We mapped the people behind each account

Three to four real decision-makers:

- Their pains, priorities & timing
- What they already believed
- Where they were getting stuck

4. Personalize at every touchpoint

- Ads built around their challenges
- Landing pages that addressed their objections
- Emails synced to where they were in the process

Everything worked together.

5. We aligned every channel

- Outbound warmed them
- Content educated them
- Ads familiarised them
- The CRM tracked the signals

Each touch made the next one easier.

6. We optimized constantly

Some messages converted.
Some didn’t.

We got rid of what wasn't converting and doubled down on what was.

That's when we saw a huge change.

The result:

→ $2M+ in qualified pipeline
→ $300K closed revenue
→ All in 90 days

Ivan documented the entire playbook - the framework, the timing, the execution details.

Comment "PIPELINE" if you want it.

52x ROI ABM Campaign 

Clay is one of the most powerful tools in B2B right now.

But most people don't know where to start.

Most people open a Clay table, stare at it for 10 minutes, and close it because they don't know what to build.

We've built 500+ Clay tables for clients. Here are the 5 workflows you should start with:

Workflow 1: Waterfall Email Finder

The problem: If you use one email finder you are getting something like a 40% finding rate. That means 60% of your list is useless.

The fix: Stack multiple providers in sequence. Start with the first one (ie Prospeo.io). If the first provider doesn't find the email, try another one like LeadMagic. You can run more than 10 different providers to maximise your chance to find the right email. 

Result: 85-90% email findign rate vs 40% with a single provider.

Workflow 2: Signal-Based List Builder

The problem: You're blasting the same message to everyone. 

The fix: Pull companies from Ocean.io or Apollo. Then start to enrich to find relevant signals. 

For example: Use Claygent to scrape funding news. Track hiring spikes with LinkedIn enrichment. Check tech stack changes with BuiltWith. Score them: 3 signals = immediate outreach, 2 = nurture, 1 = long-term.

Workflow 3: Inbound-led Outbound 

The problem: People are visiting your website but you are not capturing the intent.

The fix: RB2B identifies website visitors. Push to Clay for enrichment. Find decision-makers at those companies companies. Then push the data to Instantly.ai for outreach.

Workflow 4: LinkedIn Engagement -> Outreach

The problem: People engage with your posts and you never follow up.

The fix: Trigify.io tracks who engages with your posts. Push people engaging with your content to Clay. Enrich to find more relevant data. Do some ICP scoring and reach out to leads fitting your ICP. 

Workflow 5: Champion Reactivation

The problem: Your past champions changed jobs and you're not tracking them.

The fix: Export past customers from your CRM. Use UserGems 💎 or Clay tracks job changes. Enrich to rind the right data then reach out offering to help again.

Stop staring at empty Clay tables.

Build these 5 workflows first and you'll already have a good outbound engine going.

Which one are you starting with?

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