Floada

Didn’t plan for this, but the opportunity was too good to pass up (team, market, product, timing).

Floada uses AI to prevent cost and revenue leakage from contract data. 

Our platform recovers lost value by automating insights and actions, helping organizations boost profitability and streamline operations.

Co-Founder & Head of Sales

Pioneer Sales

Worked with early-stage SaaS founders to get their sales motion off the ground, combining hands-on selling, advising, sparring, and laying the foundation for a sales operation.

(Mandates included products in the community space, procurement, DevOps, customer service, and executive coaching)

Also, I wrote two free ebooks on some core business and sales philosophy (and lifestyle design) principles, that were downloaded by a few hundred people. 

Still available at www.dennissprute.com

Sales Advisor

BetterUp

Again, part of the region's first sales team—this time for a topic very dear to my heart. Learned lots about the science behind peak performance and well-being.

Closed six-figure deals and reached 87% of my top 15 enterprise accounts, building an $8M pipeline. Also trained teams on business writing and initiated a strategic partnership.

Sr. Enterprise Account Executive

Unbabel

In charge of EMEA Retail (grew by 6x), then DACH pod (grew by 10x to $2M+). Closed 6-7 figure deals with international enterprises. Responsible for +18% of active company revenue when I left.

Streamlined CoEs for large companies, increasing efficiency. Managed a small headcount.

Top AE (Global) - 2021
Top AE (EMEA) - 2020

Pod Leader / Sales Manager

Through my experience at HeyRide, I was trusted to work on large accounts from day one—also because I was the most experienced German-speaking rep (though I started with Retail vertical first).

Enterprise Account Executive

Groupon

Needed $ after HeyRide failed. Hit my numbers, trained teams in business writing, part of some innovation initiatives.

Sr. Account Executive

Hey Ride

Worked alongside a mentor, a former campaign manager for the NY governor. It taught me the scrappy startup hustle, building, and surviving on Burger King’s €5 daily deals.

Joining an accelerator at that age taught me more than college, so I dropped out for a bit. I also lost any fear of big-company execs by mingling with them as regular people.

We experimented a lot, but in the end, too many issues led us to shut it down.

Commercial Co-Founder

BILD

Started as an intern, then brought back for freelance gigs. In hindsight, an incredible school for sales. Tabloid journalism may get laughs, but this kind of writing that captures millions of readers is a true life skill.

Journalist

1st Sales Lead for early-stage AI startups. Main focus right now is on Procurement.

Companies are losing up to 9% of contract value without realizing it. Floada finds hidden leaks and automates fixes—recovering lost revenue and stopping overcharges across your entire contract portfolio.

Seamlessly integrates with shared drives, ERP, procurement, and finance tools to help leaders hit their targets.

Built by former DocuSign product developers with a long history of building AI-powered agreement analytics solutions.

—

My background in communication management—particularly journalism and PR—characterizes my approach to sales, coupled with an excitement for the 0-to-1 process and its strategic and tactical maneuvers.

Originally from northern Germany, I have also spent extended periods in the United States, Portugal, and Brazil.

Dennis Sprute

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 🧠🛠️

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 🥂

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

These 10 roles didn't exist a year ago.

Now they're replacing entire teams.

I've talked to so many people worried about AI "taking jobs."

Meanwhile, the companies actually hiring are creating new roles that didn't exist 12 months ago.

Here's what they're hiring for:

GROWTH ROLES

1/ Vibe Marketer / Head of Demand Gen

Runs fully automated funnels end-to-end.
Ads → landing pages → emails → workflows.

Stack: ChatGPT, Make, Customer.io, Framer, arcads AI, Fibbler

2/ Social Media Engineer

Uses AI to research what's working, write posts, and distribute across platforms.

Stack: Runway, Midjourney, Ideogram, Make, Taplio, Scripe

3/ Video Content Engineer

Creates high-production video. AI handles the editing, cuts, effects, voices, animation.

Stack: Google Veo, Runway, Arcads, ElevenLabs, Kling AI

4/ Content Engineer

Builds SEO + content systems. Ranks in Google, ranks in LLMs, builds programmatic content machines.

Stack: AirOps, Mentions, Surfer, Ahrefs, AlsoAsked

5/ GTM Engineer

Finds prospects, enriches data, personalizes messaging, runs outbound at 10x the volume.

Stack: Clay, Instantly.ai, Artisan, Expandi, FullEnrich

OPERATIONS ROLES

6/ Ops Engineer

Deletes half your manual work overnight.
Every system → automated. Every process → rebuilt.

Stack: n8n, Flowgent, Airtable, Slack, ClickUp

7/ RevOps & Attribution Engineer

Owns the full customer journey. Tracks anonymous research → pipeline → conversion → retention.

Stack: Attio, Unify, Common Room, Usermaven, Default, Clay

8/ Talent/HR Engineer

Sources candidates, screens them, automates half the hiring process.

Stack: Clay, LinkedIn, Airtable, Ashby, Fetcher

PRODUCT ROLES

9/ Product Engineer

Builds apps without waiting on engineering timelines. AI handles design, code, logic, prototypes.

Stack: Lovable, GitHub Copilot, ChatGPT, Figma AI, Supabase, Guideflow

10/ AI Agent Engineer

Builds agents that run workflows across sales, ops, support, and product.

Stack: Relevance AI, n8n, Voiceflow, Claude

These companies are rebuilding departments around AI-first workflows.

Smaller teams. Higher output.

By 2026, most teams will have at least 5 of these roles.

Which one are you seeing the most demand for?

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 👇

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.

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!

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? 👇

Valley books 150+ meetings per month with ONE person.

I’m going to show you exactly how they’re doing it.

B2B companies are still hiring SDR teams for cold outreach.

Valley built a crazy system instead to tackle this.

Their CEO Zayd Syed Ali figured out how to:

- Generate demand
- Capture signals
- Book meetings automatically

Any founder can copy this... here's how 👇

1/ Content

Zayd turns conversations → content → leads.

To do this he:
- Records every call with Fireflies.ai
- Mines calls for clips, hooks, objections, insights
- Runs bi-weekly content interviews (Riverside)
- Repurposes into short-form content

On top of this he posts 5x/week on LinkedIn using Taplio, Bluecast, Wispr Flow

Two-track strategy:

Company page → social proof
Testimonials, case studies, new user announcements.

Founder page → POV + story
Founder journey, insights, opinions.

Tools: Shottr (screenshots), Shots (graphics)

This means that...
When he reaches out, prospects already know him.
They’ve seen the brand 3–5 times.

2/ Signal-Based Prospecting

Traditional SDR model:
Buy Apollo list → blast → hope for 2%.

Zayd’s model is different:
They only reach out to people showing interest.

So, every Friday they scrape:

- Profile visitors
- Website visitors (Valley, RB2B, Vector 👻)
- Post engagers
- Company page followers

Valley then:

- Auto-qualifies
- Scores fit (high/medium/low)
- Filters competitors
- Enriches contact data

This alone increases conversion by 5–10x.

3/ Personalized outreach

For every qualified lead, Valley:

- Runs deep research
- Creates relevant (contextual messaging)
- Personalizes at scale

The output:

- 30%+ reply rates
- 40–50 positive responses per day

This is one system doing the work of 10 SDRs.

4/ Lead Management & Closing

Lead replies → goes silent?
Zapier → Slack → instant callback.

Alex Nelson (Founding AE) jumps on it.

How they close:

- Google Meet
- DMs (accelerator closes in chat)
- Paage.io for proposals
- Stripe for payments

The result:

- 150+ meetings per month.
- 1 operator running everything.
- AI + connected systems doing the work of 10 SDRs.

If you want to build something like this for your company,
just drop “SYSTEM” below and I’ll happily walk you through it.

Lemlist's CEO showed us how they built a $37M ARR SaaS.

One thing stood out.

Every part of their growth has a system behind it.

Here's the breakdown:

1️⃣ Content Engine

Their team has 300,000+ combined followers on LinkedIn.

And it's not random. It's coordinated:

- Guillaume Moubeche
- Charles Tenot
- Kévin Moënne-Loccoz
- Lucas Perret
- Tal Baker-Phillips
- Erwan Gauthier

Each owns a lane (growth, SaaS, CEO lessons, etc.)

Plus 200K+ monthly SEO visitors.

Stack: Figma, Storyblok, Taplio, Ahrefs, Semrush

2️⃣ Outbound Engine

Yes, they use lemlist.

But there's a lot more behind it:

Data: Apollo, Prospeo.io, BuiltWith, Crunchbase
Intent: LoneScale, Snitcher, G2
AI: Dust, Clay, OpenAI, Claude, Mistral

They find buyers before they start looking.

3️⃣ Product Infrastructure

200K+ monthly visits → 7–8% convert → 15,000+ signups/month.

Stack: BigQuery, Google Cloud, Holistics, RudderStack,Replit, Mixpanel

4️⃣ Revenue Ops

Last month their sales team closed $685K ARR.

Sales: Hyperline, Claap, lemcal, HubSpot
Marketing: Customer.io, Default, Webflow
Finance & Support: Stripe, Qonto, Pennylane, ProfitWell, Intercom
Team: Slack, Notion

This is what $37M ARR ops looks like.

What part of their stack surprised you?

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 ☝️

Cold email got us to $6M ARR.

LinkedIn Ads took our results to an entirely different level.

People keep asking me which one generates more leads.

We have run cold email for over 200+ B2B companies - and layered LinkedIn Ads on top.

1/ What it takes to make each one work

LinkedIn Ads

You win or lose on:

- Audience targeting
- Scroll-stopping creative
- Landing pages that convert

If one piece breaks, the whole thing falls apart.

Cold Email

The game is all about:

- Short, punchy messaging
- Clean personalization
- Perfect infrastructure

Nothing else matters if your email doesn't reach the inbox.

2/ Speed to results

LinkedIn Ads:

Slow start. Setup, approvals, creative testing, landing page tuning.
Takes time but compounds fast once you find a winner.

Cold Email:

Instant.
If your domain + infra + offer are dialed in, you can book meetings on Day 1.

3/ Cost to reach 10,000 prospects

LinkedIn Ads:
~$1,500–$2,500
(depends on creative + ~$30 CPM)

Cold Email:
~$500–$1,000
(infrastructure + data + sending tools)

Pretty similar, but cold email has more moving parts.

4/ The stacks that work

LinkedIn Ads Stack

Figma, CapCut → creative
Default, Zapier → routing + workflows
Fibbler, Usermaven → attribution + analytics

Cold Email Stack

Instantly.ai, lemlist → sending
ColdIQ infra + Instantly → domains, warmup, deliverability
Wiza, LeadMagic, Prospeo.io, FullEnrich → data + enrichment

5/ Personalization depth

LinkedIn Ads:

Segment-level personalization.
Everyone in “Sales leaders in AI SaaS” sees the same creative.

Cold Email:

True 1:1 personalization.

- Individual pain points
- Individual triggers
- Individual context

6/ Deliverability & visibility

LinkedIn Ads:

95–99% visibility
Guaranteed. They see it.

Cold Email:
60–70% inbox placement if your infra is world-class.
Spam risk always exists.

7/ The real challenge with each

LinkedIn Ads:

Finding the perfect creative + offer + landing page combo.
Most people burn budget before they get the formula right.

Cold Email:

Deliverability.
The technical side is what kills most campaigns.

So which one works better?

Cold email is:

→ Faster
→ Cheaper to test
→ Easier to personalize

LinkedIn Ads are:

→ More scalable
→ More visible
→ More predictable

We run both because they multiply each other:

Cold email drives conversations.
LinkedIn Ads creates familiarity.
Together, reply rates go up, CPL drops, and close rates jump.

What are you running right now - LinkedIn Ads, cold email, or both?👇

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. 👇

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 👀)

Behind Snowflake's $4B ARR...

$2.4B generated by SDRs alone.

They have a crazy 5 step system that warms every account before outreach happens.

Snowflake turns every SDR into a closer by making sure prospects already know who they are before the first touch.

This is the framework behind their 46% meeting rate (vs 17% in regions that ignored it):

1/ Collaboration

Snowflake run one GTM strategy, one account list, one message, one goal.

Marketing feeds Sales insights they can act on.
Sales executes within 14 days.

Most companies operate in silos. Snowflake operates as a single unit.

2/ Intelligence

60% of buying research happens anonymously.
Snowflake listen and act on intent signals.

So...

First-party signals like website visits, email engagement, product usage.
Third-party signals like competitor research, job changes, funding rounds.

They use tools like Bombora to flag "high-propensity" accounts - which convert 4x better than random CRM leads.

3/ Activation

When an account shows buying intent, Snowflake launches a 3-week sequence:

Weeks 1-2: ABM warms the account with tailored content, ads, emails, and microsites.
Week 3: SDRs reach out.

Prospects are then familiar with Snowflake before they make contact.

36% meeting rate for pre-warmed accounts vs 10% for pure cold.

That's 3.6x more meetings without sending more messages.

4/ Engagement

Snowflake hits accounts from multiple angles, but always with one consistent story.

- Personalized emails
- LinkedIn outreach
- Custom microsites
- Calls

Their personalized microsites alone deliver 4x higher meeting rates than generic ones.

Nothing feels random.
Every touch reinforces the same message.

5/ Optimization

Every two weeks, ABM, SDRs, and AEs run alignment sessions.
From this, they can see:

- What's resonating
- What's stalling
- Which accounts are warming up
- Which messages are working

Snowflake doesn't track attribution.
They measure impact at the account level and optimize the entire system together.

The results?

- 2-4x more meetings on ABM accounts
- Deals close 2x faster
- Top-tier accounts convert 5x better
- 40% of Tier A accounts turn into pipeline (vs 10% for non-ABM regions)

Snowflake obviously has a huge budget.
But most teams don't need 300 SDRs or their budget to use this.

You just need the sequence:
Align Marketing, SDR, and Sales on shared account goals.

Track first-party intent - website visits, email engagement, product usage.
Warm accounts two weeks before outbound.

Are you warming accounts before you reach out?

Snowflake Outbound Strategy Breakdown 

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 

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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