Michel Lieben 🧠

Valley's GTM engine books as many meetings as 10 SDRs with just 1 person.

Their CEO, Zayd, believes every GTM can replicate it 👇

1. Content Engine

- He records everyone of his call via Fathom.ai or Fireflies.ai and mines them for content.
- He conducts bi-weekly content interviews on Riverside, turns these into short-form clips & saves the transcripts.
- He posts 5x per week on LinkedIn using content ideation tools for inspiration (e.g: Taplio, Bluecast, Wispr Flow)
- On their company page, they focus on social proof posts (i.e: testimonials, case studies, new users announcements)

He uses shottr to take screenshots, and turn them into good looking graphics via 'Shots'.

His personal account focuses on topics such as: 'founder journey', 'industry insights' and actually just about anything he deems interesting.


2. Signal-Based prospecting

Every Friday he scrapes:

- His profile visitors
- Company page followers
- Their website visitors (using Valley, RB2B, Vector 👻)
- His post engagers (on personal profile & company page)

Valley automatically qualified & tiers each lead (high/medium/low fit), filters out competitors and enriches contact details.


3. Personalized Outreach

For every qualified lead, Valley:

- Conducts deep research
- Crafts relevant messaging
- Deliver > 30% response rates

This adds to ~40-50 positive replies every day in their LinkedIn inbox.


4. Lead Management

For every leads that replies positively, but end up ghosting, they built a Zapier automation that pushes leads to Slack with their contact details.

Then, Alex Nelson, Valley's Founding AE, gives them a quick call to see if they're still interested.


5. Deal Management

- They use paage.io as one-pager proposals, which tracks what prospects spend most of their attention on.
- Payments are processed via Stripe.

This setup books around ~150 high-intent meetings per month.

....and can be reproduced for most B2B founders!

P.S: Anything you'd recommend Zayd and his team to get past 200 monthly meetings?

AI Agents are replacing employees.

Some companies even trust them with corporate credit cards.

We're seeing this disruption across all departments.

And by 2027, it's predicted that ~80% will adopt them.

That said, in many cases, what we believe is an AI agent... is just a clever workflow.

Let's look at a typical work task to illustrate this, via 3 scenarios.

For example:

→ Scheduling a quarterly business review with a major client.


A. Non-Agentic Workflows

Humans handle all the work, and leverage tools that act based on their instructions:

1. A manager remembers it's time for the business review.

2. They check their calendar and their CRM.

3. They ask ChatGPT to "draft an email to schedule a client call"

4. They complete the draft and send the email.

Human did all the thinking.
AI didn't take any initiative.
It just helped with content.


B. Agentic Workflow

AI is part of a system with automated triggers & logic.

1. A calendar automation gets triggered as it's been 90 days since the latest business review.

2. The automation checks for availability in the calendar of the manager.

3. The automation then triggers the drafting of an email to schedule a meeting.

4. The email is automatically sent.

The workflow is semi-autonomous.
It saves time...

But won't adapt to unexpected scenarios (i.e: follow-up, rescheduling)


C. AI Agents

The Agent has a 'goal-oriented objective'.

In this case: "Keep client happy & engaged".

1. Agent constantly checks CRM, activity & past clients' conversations.

2. It detects it's time for the quarterly business review. It also checks billing tier & checks recent usage drop.

3. It drafts a personalized note ('Hey Maïa, I see your team recently added 4 users, but they don't seem to use the platform that much...") and suggests times to meet.

4. It sends the email and monitors replies. It'll automatically follow up to suggest more time slots if it doesn't get an answer within 2-5 days.

5; Once the meeting is set, it comes up with an agenda based on previous convos, and warns the CS team of potential red flags (i.e: low usage → high churn risk)

It coordinates multiple tools.
It's contextual & personalised.

It focuses on a 'bigger goal' (i.e, client satisfaction) instead of a 'small task' (i.e, drafting & sending an email).

P.S.: Are you automating your repetitive work with AI at the moment?

What are you tackling in priority? 👇

Snowflake hit $4,000,000,000 ARR with 60% of its pipeline sourced from SDRs.

Here's their playbook (and how you can replicate it):

First, you need to ensure your departments work together towards the same goal.
 
For Snowflake: Marketing, SDRs & Sales are under ONE SAME team.

They made the test for specific regions.
- The ones that did it had up to 46% meeting rates.
- The ones that didn’t do this had 17% meeting rates.


1️⃣ Collaboration

Marketing & Sales work hand in hand.

Marketing gathers insights to be used by the sales team.
The sales team acts on them within 2 weeks.

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


2️⃣ Intelligence

Snowflake relies a lot on signals.
Their rationale is to get in front of prospects as soon as they’re searching for their use cases.

They do that via:
- Third-party intent signals (job changes, funding rounds, web searches)

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

They rely on tools such as Bombora to spot accounts showing interest in the background. I’d recommend using Clay or Common Room for this.

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


3️⃣ Activation

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

That is:

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

Week 3: SDRs step in with outbound.

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

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


4️⃣ Engagement

They hit prospects everywhere they are.

→ Calls
→ Cold Emails
→ LinkedIn DMs
→ Custom microsites

True multichannel orchestration.

(I’d recommend using a platform like lemlist to replicate these cadences)


5️⃣ Optimisation

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

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

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

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

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

The results speak for themselves:

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

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

You can start by:
- Aligning marketing & sales on shared goals.
- Tracking buying signals (use Clay or Common Room)
- Launch ABM campaigns 2 weeks before starting outbound.

… and measure impact at the account level.


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


P.S: Kenny Damian made this fire breakdown. Follow him… he makes the best AI Agent x Sales content on LinkedIn.

I curated > 2,200+ AI Sales Tools across 55 categories. Here are my top picks:

(I use about 40% of these to run my $6M ARR outbound agency)

AI Agents

→ Relevance AI (Agent Builder)
→ Instantly.ai (Reply Agent)
→ Clay (Research Agent)
→ n8n (Agent Builder)
→ Artisan (AI SDR)

CRM

→ Breakcold
→ HubSpot
→ Attio

Data Enrichment

→ Prospeo.io
→ LeadMagic
→ FullEnrich
→ Wiza
→ Clay

Data Scraping

→ Instant Data Scraper
→ Firecrawl
→ Apify
→ Clay

Data Sourcing

→ Openmart
→ Ocean.io
→ LinkedIn
→ Exa

Intent Signals

→ Common Room
→ Unify
→ Clay

MCPs

→ Docker, Inc
→ Pipedream
→ Composio
→ Cursor
→ Claude

Messaging

→ Octave
→ Twain

Sales Assistants

→ Momentum.io
→ Attention
→ Claap

Visitor Identification

→ Midbound
→ Vector 👻
→ RB2B

Workflows

→ Relevance AI (Agentic Workflows)
→ AirOps (AI SEO Workflows)
→ Clay (GTM Workflows)
→ Default (Inbound Workflows)
→ n8n (General Automations)

P.S: Want to see the entire list of 2,000+ AI Sales Tools? Check it out here: coldiq.com/ai-sales-tools

Founder: "If I let my employees post on LinkedIn, they'll leave for better opportunities"

Me: "We closed $800K ARR with this LinkedIn strategy last month":

We have 12 people with 5,000+ followers regularly posting here.
(This amounts to 220,000+ follower)

Michel: 58,142
Alex: 52,670
Melissa: 39,646
Ivan: 18,106
Soheil: 11,599
Gerardo: 10,999
Millie: 10,231
Monika: 9,476
Kenny: 6,692
Natasha: 5,514
Juan: 5,408
Harry: 5,049

- They share their winning strategies & expertise
- They send visitors to our website
- They generate leads daily

And... they grow THEIR brand.

This generates > 100s of qualified sales calls for ColdIQ.

Founder: "But still, my A players will get poached"

Me: "You'd rather keep them by limiting their options instead of being the best opportunity for them?"

I welcome companies trying to poach my team members.

It forces me to consider what we provide to the people giving us their time... their most valuable asset.

But the truth is, the opposite actually happens:

1. It attracts NEW A-Players and makes our team want to STAY

Your team is getting paid to grow an asset (their personal brand) that 100% belongs to them. This is one more reason to stay at your company.

But also, the combined visibility it creates on LinkedIn attracts people who share the same work philosophy.

2. It's a WIN-WIN situation

For your team: they're growing their brand and making themselves more attractive on the job market.

For your company: it generates organic leads that have lots of context on your brand and are easier to close.

3. It enhances all your other efforts

- Hiring becomes easier when you're more visible.
- Messaging gets clearer when you can test it every day.
- Outbound campaigns work better when the senders have a brand.
- Deals close faster when leads have been seeing your posts for weeks.

Is 2026 the year your team takes over LinkedIn?

If so, we can help. Comment 'AUDIT' or 'STRATEGY' below, and we'll jump on a free consultation call to break down what your LinkedIn strategy should look like 👇

We crossed $6,000,000 ARR running cold emails for 100+ B2B companies.

But when Ivan added LinkedIn Ads to the mix, results skyrocketed.

So... Cold Email vs. LinkedIn Ads

Which one gets more leads?

Here's the side-by-side comparison.

1. Key rules to make it work

→ LinkedIn Ads:

- Nail audience targeting
- Focus on strong creatives
- Optimize landing pages for conversions

→ Cold Email:

- Short, concise, actionable copy.
- 1:1 personalization + value nuggets
- Proper deliverability infrastructure setup.


2. How fast can you get results

→ LinkedIn Ads: Not straightaway = Requires 'complex' setup, ad approval from platform... and iterative optimisations before getting consistent results.

→ Cold Email: Can be fast = You can book meetings from Day 1 of campaign launch.


3. Cost to reach 10,000+ prospects

→ LinkedIn Ads: $500 to $1,500 (includes design of creatives & costs per 1,000 bought views [~$30 CPM])

→ Cold Email: $500 to $1,000 (includes email infrastructure + data + sales engagement software costs)


4. Tools you can use

→ LinkedIn Ads:

- Creatives: Figma, CapCut
- Lead Routing: Default, Zapier
- Tracking + Analytics: Fibbler, Usermaven

→ Cold Email:

- Sales Engagement: Instantly.ai, lemlist
- Email Infrastructure: ColdIQ, Instantly.ai
- Data Enrichment: Wiza, LeadMagic, Prospeo.io, FullEnrich


5. How deep can you personalise messaging

→ LinkedIn Ads: By segment ("i.e: tailored to "Sales leaders in AI SaaS")

→ Cold Email: Entirely = 1:1 personalized messages


6. Deliverability

→ LinkedIn Ads: ~95-99%. Directly delivered to the LinkedIn feed, multiple times.

→ Cold Email: ~60 to 70% if set up correctly. Risk of SPAM.


7. Challenges to making it work

→ LinkedIn Ads: Tough to find a winning combination of: creative + landing page + offer.

→ Cold Email: Hard to beat spam filters. If you do, it's hard to stand out in crowded inboxes.


So, are you team "LinkedIn Ads" or "Cold Email"?

LinkedIn Ads added us $80,000+ in new ARR in 2025.

Here's the funnel that books us qualified meetings on autopilot:

Most B2B orgs waste their ad spend because their funnel looks like so, for every prospect type:

Cold Audience → Direct CTA
Warm Audience → Direct CTA
Hot Audience → Direct CTA (Yes, again!)

Here's what we do instead:


1. BUILD TRUST (Top of Funnel)

The goal here = being unignorable.

We use the following formats:

- Document Ads (5-8 pages of pure value)
- Single Image Ads (Pain/Fear Hook + Solution)
- Thought-Leader Mini-Demo Videos (15 to 30s)

No need to sell hard here.
Just have leads stop their scroll and think to themselves:

"They understand me" or "This looks useful"


2. BRING PROOF (Middle of Funnel)

At this point, prospects have seen you a few times already.
They don't trust you just yet.

Thus, it's time to show receipts:

Build retargeting audiences with everyone who engaged (i.e: website visit, viewed half of your video ads, commented or liked ads... on a 90-day window)

The following formats perform best:

- UGC from real clients (success stories // testimonials)
- Big Result with social proof (timeline + mechanism)
- Before / After case studies

Prospects might be thinking, 'this is too good to be true'.
Show them it actually works.


3. CLOSE THE DEAL (Bottom of Funnel)

They've seen your ads & your content.
They watched your demo or your VSL.
They looked into your pricing.

It's time to double down.

Retarget these hot leads (30-day window, 75% video views, contact/pricing page visits) with:

- Direct CTA Ads (offer + what they'll get from talking to you)
- Testimonial Ads (short quote + success metrics)
- Conversation Ads (looks like personalised DMs)

This is the exact LinkedIn Ads funnel Ivan implements for our B2B clients, spending anywhere from $30K to $100K+ per month.


But this is just part of the equation.

The real magic happens when we combine LinkedIn Ads, with content & outbound into a GTM Flywheel that works in sync.

We used this system to generate > $1M in closed-won revenue for a 7-figure SaaS.

... and Ivan Falco recorded a 15-minute step-by-step video that breaks down the entire process (formulas, frameworks, timing, it's all in there).

Want to view it?

Let me know and I'll send the link over :)

I spend > $200,000/year on AI Sales tools.

I’d pay double the price for these:

(And recommend them to every revenue leader)

Here’s the breakdown by use-case:

1️⃣ For data sourcing

Data is the most essential part of getting results with cold outbound.

There are several ways to find data.
For example:

A. AI Agents like Clay, Exa & Relevance AI can browse the web to source hard-to-find data points.

B. B2B databases like LinkedIn & Ocean.io include an extensive range of filters to help you build lists.

C. Niche databases like Openmart are very helpful to source data on local businesses.

D. Buying intent platforms like Clay & Common Room will help you reach out to leads with context.

E. Scraping software like Apify or Instant Data Scraper will help you extract data from any platform.


2️⃣ For data enrichment = emails or phone numbers

We use a handful of (very) reliable platforms.

For example:

A. Individual solutions like Prospeo.io, Wiza & LeadMagic help us find 100,000s of email addresses every month.

B. Waterfall platforms like FullEnrich & Clay aggregate the best individual solutions (including the ones cited above).


3️⃣ For cold outreach

Landing in spam is the #1 reason cold email campaigns fail.

We use sending platforms that prioritise deliverability.

Examples include:

A. Instantly.ai for email sending.

B. Expandi (Outreach Playbook Talks) & Valley for LinkedIn outreach.

C. lemlist for multi-channel outreach including phone, email & LinkedIn touchpoints.


4️⃣ For deal management & closing

Managing your pipeline can get messy when your prospecting becomes (a bit) too efficient.

A. For deal management, examples include: Breakcold, HubSpot or Attio.

B. For meetings, examples include Attention & Momentum.io, which keeps track of your conversations, records them, gathers insights, and takes action on your CRM. (Salesforce for Momentum).


P.S: What's the next AI Sales tool I should absolutely add to my $200K software bill?

We grew our GTM agency from 0 to > $6M ARR in the past 2 years.

And we’re launching a program teaching you exactly how:

That is,

→ the LinkedIn content strategy that generates 2M+ impressions per month
→ the processes that allow us to deliver outbound to 80+ B2B companies
→ the GTM engine that books us 100+ monthly qualified meetings
→ the outbound & GTM playbooks we deploy for all our clients
→ our internal ai, agentic & automation processes
→ our hiring, systems & leadership playbooks

… and much more.

But why learn from us?

- ColdIQ is a lemlist, Smartlead & Instantly.ai expert (and one of few agencies that received their golden plaque)
- ColdIQ is 1 of 4 Elite Studio Clay partner (the highest tier there is!)
- ColdIQ has ran GTM & delivered results to 200+ B2B companies.
- We how to generate revenue from LinkedIn.


But most importantly, each of our teacher actively does what they preach.

- Louis recorded our outbound & Clay modules, and is among ColdIQ's highest performing go-to-market engineer, delivering results for our largest clients.

- Ivan teaches our ABM + LinkedIn ads modules, and is actively running campaigns responsible for $1M+ in closed-won revenue at > 5X ROAS.

- Alex teaches our hiring & operations modules, while actively running all of ColdIQ’s internal operations.

- Niklas teaches sales, while leading a team that closes $60K to $85K in new MRR every month.

- Soheil teaches service delivery at scale & systems, while actively leading our agency.

- And I, Michel, teach "generating revenue from LinkedIn", while posting here every single weekday (and I haven’t missed a day in 2025, that’s my biggest flex).


If that sounds interesting, schedule a call with our team right here: coldiq-accelerator.com

And if you have any questions, please feel free to add them below (so everyone can see the answer) 👇

Cold Email reply rates are shrinking. Teams are investing $1000s in complex cold email infrastructure for < 3% reply rates. Meanwhile, WhatsApp outreach boasts ~30% reply rates.

Does that mean you should switch from Email to WhatsApp outreach?
It's a bit more complex than that...

Here's the side-by-side comparison we did with Erwan Gauthier (Head of Growth at lemlist):

1. Key rules to win

→ WhatsApp Outreach:

- Priorize existing warm leads (from positive replies, demos or meetings).
- Add context from previous touchpoints (meeting notes, updates).
- Respect timing & consent.
- Make it conversational.

→ Cold Email:

- Provide value & personalise your outreach.
- Set up a solid deliverability infrastructure.
- Write concise & actionable copy.


2. Speed to results

→ WhatsApp Outreach: Instant. Replies come within minutes.

→ Cold Email: Can be fast. You could book meetings from the first day of a new outreach campaign.


3. Cost to reach 10,000+ prospects

→ WhatsApp: Not made for mass outreach. But in theory it could cost as low ~$20 (cost of connecting a phone number to lemlist).

→ Cold Email: $500 to $1,000 (including email infra, data & sales engagement software)


4. Software

→ WhatsApp:

- CRM Sync: HubSpot, Pipedrive or Salesforce
- WhatsApp Integration: lemlist
- Waterfall Enrichment: lemlist

→ Cold Email:

- Email Finding tools: Prospeo.io, Wiza, LeadMagic, FullEnrich
- Email Infrastructure: ColdIQ
- Sales Engagement: lemlist


5. Messaging personalisation

→ WhatsApp: Manual outreach = 100% personalized.

→ Cold Email: 1:1 personalized messaging;


6. Nurturing capability

→ WhatsApp: High = You can maintain ongoing personal touchpoints effortlessly.

→ Cold Email: Low = Built for direct conversion.


7. Deliverability

→ WhatsApp: 95-100%. Direct to the recipient's phone. No spam folder*

→ Cold Email: Around ~60 to 70% if set up correctly. Spam risk is high.


8. Average reply rate

→ WhatsApp: ~30%

→ Cold Email: 1-10%


9. Challenges to making it work

→ WhatsApp: Risk of account restriction if abused. Tough to scale high volume of relevant conversations.

→ Cold Email: Hard to beat spam filters. When you do, you still need to stand out in flooded inboxes.


P.S: Ever experimented with WhatsApp for outreach? Curious to hear how it went 👇

LinkedIn got me past $6M ARR. But Jake Trinder, the mastermind behind Instantly.ai & Clay's channels, argues YouTube is better.

His proof? He grew multiple channels from 0 to > 7-figure revenue from YouTube.

So we did a side-by-side comparison 👇

1. Core Focus

→ LinkedIn: Booking meetings by publishing relevant snackable content.

→ YouTube: Building trust & booking meetings via in-depth educational videos.


2. Key Rules to Win

LinkedIn:

A. Find outlier/viral/proven publications using tools like Taplio.
B. Consistent high-quality posts relevant to your ICP.
C. Frequent engagement actions with your audience.
D. Optimized profile (banner, title, featured section).

YouTube:

A. Nail combination of thumbnail + title before recording.
B. Focus on quality. YouTube = "Winner takes all"
C. Deep research on titles, thumbnails & trends.


3. Posting Time & Frequency

→ LinkedIn: 3 to 7 posts per week. Same posting time every day.

→ YouTube: 1 video per week. Posting when audience is most online.


4. Top Software

→ LinkedIn:

- Content Ideation + Analytics: Taplio
- Visuals: Figma, Canva, OpusClip
- Writing: Claude, Grammarly

→ YouTube:

- Content Ideation: 1of10, Viewstats, vidIQ
- Production: Adobe Premiere Suite
- Recording: Tella, OBS Studio


5. Expected Reach

→ LinkedIn:

- Audience = B2B focused (i.e: sales, marketing, HR & tech buyers).
- Prospects browse the feed to educate or entertain themselves.
- Over 310,000,000 monthly active users.

→ YouTube:

- Audience = Broad, top-of-funnel (creators, entrepreneurs, founders).
- Audience is actively searching for the content you're creating.
- Over 2,500,000,000 monthly active users.


6. Engagement Expectation

→ LinkedIn:

- Decent conversion rate. 'Easy' to produce content scale.
- You can reach out to post engagers (DMs).
- Leads are nurtured daily.

→ YouTube:

- High conversion rate from long-form content.
- Audience can binge-watch channels.
- Can't contact viewers directly.


7. Challenges

→ LinkedIn:

- Can take weeks/months before generating any leads.
- Staying consistent is hard.

→ YouTube:

- Lots of upfront work to get 1 good video out.
- Consequent investment in studio setup.
- Talking to a camera can feel weird.


If you had to pick one platform to scale your business, which would you choose?

P.S.: If you need help with YouTube, reach out to Jake. He's the best at growing B2B brands on there. If you need help on LinkedIn, send me a DM :)

6 months. $3M in pipeline. $500K closed.

Results from the ABM campaign Ivan ran for AirOps 👇

Here's the step-by-step to replicate this:

1. Identify your most profitable clients.

Sounds obvious. But look at who you've already closed and who you've generated lots of revenue from.

Target more accounts like them.


2. Create your ABM target

Map your total addressable market. Priorize lookalike accounts worth the extra effort.


3. Break down your personas

Identify buying groups. Deeply research your persona. Speak their language.


4. Personalize every touchpoint

Make sure your ads, landing pages & emails are all tailored to the account & persona.


5. Sync all your channels

Gain insights from each motion (ads, outbound, content) to fuel the other ones. Track every engagement in your CRM.


6. Personalize messaging at every stage

Use campaign engagement metrics to adjust your messaging based on buying journey stage & pain points.

7. Keep iterating

Cut what doesn't work. Double down on what does.


P.S: We recorded a step-by-step video laying out the exact system that added $3M in ARR for us this year. It's right here: https://lnkd.in/eqU3DKsZ