Growth Marketing Manager at Salesflow.io | B2B SaaS Marketing | Meshing Marketing with Sales, Ops & Product

Hi, I’m Rachid 🤙

My first job was at 15, working for my dad. He’s always gone far and beyond for the customer, always providing value for money.  Fast-forward 13 years, I’m always asking myself “how much value can I provide?” Wherever I go, whatever I do. 

Now with 8 + years in the Marketing game, I’ve spent the majority of my career moving the needle to create profitable outcomes and produce cost-effective growth. I believe my focus and achievements have been based on several things, namely:

#1. Outcome Focused:
I like to roll up my sleeves and make things happen.  Tackling the entire growth journey, from acquisition to monetisation, through activation, retention, and referral. Delivering results results such as consistent lead flow, fitting tactics together to drive LTV up / CAC down, as well as delivering ROI, faster and at a lower cost.

#2. Full-Stack:  
I lean towards being 'full-stack' rather than a specialist. This has led to me producing better outputs by being good at a broad range of skills. I'm always curious, trying to understand everything, which has helped build a unique, complementary and valuable skill stack.
 
#3. Doing > Talking: 
The best way I learn is by actually doing. Experimentation, iteration, improvement, trial and error.  I try to spend most of my time observing and then doing things that have a real measurable effect. I take the ‘Theory Then Action’ route - before the action, I like to define the end goal, break it down into the actions I need to achieve it, and then the knowledge I need to have in order to take that action. 

#4. Standing Out:
There is nothing worse than indifference.  I try not to rely on the tactics that thousands are already employing. Instead, I approach the market with a fresh perspective and identify what unique value I can bring to the table. 

Outside of work, you can find me: 

Sharpening my sword - reading my Kindle, writing, learning a new skill or building/creating things.

Rachid EHabi

Co-Founder @ The Playbook Agency | Implementing AI into the Revenue Teams of Series A-C Companies Successfully |

Resist change to stay comfortable, embrace change to move forward.

Leo Branica

I moved away from running outbound campaigns over a year ago.

But I still get asked how to set up simple, effective cold email.

I recommend the same 3 tools every time:

InboxKit – Email infrastructure
Prospeo.io – The best verified email + phone provider
Instantly.ai – Easy sending that integrates with your stack

The setup:

1. Buy your inboxes in InboxKit
2. Connect and warm up in Instantly
3. Build your contact list in Propseo and export to Instantly
4. Upload Messaging in Instantly
5. Run and push positive replies into HubSpot

You can have all the gear and no idea.

Keep it simple. Get your V1 live. Then iterate.

Leo  Branica

Founder | GTM Infra as a Service | Removing Limitations for Revenue Teams

If you're selling a time-based outcome, you need to bring your proposal stage all the way to your prospecting stage.

Calculate the ROI before you reach out.

This is what I do for GTM Studios:

→ Find the number of sales reps 
→ Look up average salary per rep (adjusted for location) 
→ Estimate the size of their TAM 
→ Estimate hours needed to manually research that TAM 
→ Calculate the time I could realistically save them 
→ Convert that saved time into dollars 
→ Model what happens to pipeline if those hours go back into selling

By the time I get on a call, I'm not pitching. I'm confirming.

"Based on your team size and TAM, we're looking at roughly $X saved per quarter. Does that match what you're seeing internally?"

The proposal isn't a negotiation. It's a formality.

You'll disqualify bad fits faster. And the good fits will close themselves.

If you're looking to hire a GTM Engineer for the first time. 

Here are the 3 things you need to look out for so you don't get burnt. 

I score hires these main competencies. 

1️⃣ Outcome + systems mindset.

Your table could be the ugliest thing in the world. Doesn't matter. As long as the outcome is there.

Good GTM engineers ship functional workflows, not pretty ones. They build reusable infrastructure so you don't rebuild the same thing 10 times.

They're thinking: "How do I build this enrichment table once so every future workflow can use it?"

2️⃣ Knows where data lives and how to fetch it.

AI can fetch what's publicly available. But it doesn't always know where to look.

- Did you know most law firms list their partners on their about page? 

- Or that job postings tell you more about tech stack and scaling plans than BuiltWith?

- Funding rounds? Crunchbase gives you historical data. Google Alerts gives it to you in real time.

A good GTM engineer knows there are multiple ways to get the same signal - and which one gives you better data.

They understand how to architect signals from scattered public sources and turn them into something you can actually score and route.

3️⃣ Revenue team collaboration. 

Building the table is half the job. They need to understand who to target, how to find them, what to research, and how sales will action it.

They ask: 

"Do we even know who our ICP is? 

What data do we actually need? 

Where are the gaps?"

They fix core ICP data, fill data gaps, and clean data hygiene before building fancy workflows on top of broken foundations.

If they're building in isolation without talking to the people who'll use the data, they're building the wrong thing.

If I had a revenue team of 3-5 sales reps and had to build the GTM infra from scratch

Here's exactly what I'd use.

HubSpot CRM - Perfect for a small sales team. Easy to set up, scales with you, and plays nicely with everything else on this list.

Clay - TAM mapping, account prioritisation, and building the enrichment workflows that feed your outbound. This is your data engine.

lemlist - Multichannel sequencing across email, LinkedIn, and phone. Multiple inboxes, automated and manual steps in one flow. Proper orchestration.

Aircall - Integrates directly with HubSpot and Lemlist so your call steps sit inside your sequences, not outside them.

Fireflies.ai - Great call recorder. Integrates with everything, transcripts are solid, and your reps will actually use it.

Jointflows - Underrated. Helps your team execute deals properly with shared workspaces and mutual action plans. Keeps the buyer engaged post-discovery.

@Claude - Sits on top of everything. Drafting sequences, summarising calls, building prompts for Clay, drafting proposals. The glue.

Total stack. Nothing unnecessary.

The tools aren't the hard part. 

Building the workflow that ties them together is.

----------------------------------- 

If you're building your GTM infra from scratch and looking to implement these tools, I am opening up 2 spaces for beta customers who want their sales engine set up and all talking to their CRM.

If you're running a revenue team that's having sales/customers calls every day

You have no excuse to be spewing generic AI slop in your outreach, enablement docs and marketing.

Your calls are the answer.

Every objection.

Every use case.

Every way your best prospects describe their own problem — it's all there.

The issue?

It's sitting in Fathom/Fireflies/Gong collecting dust.

So I'm building a v1 of a GTM Data Lake.

Step 1: Get every call into one place.

I used Claude Code to hit the Fathom.video API and pull down every transcript automatically.

One script, one command — 497 calls, dated and formatted, ready to actually use.

Connect Claude Co Work to the download folder and query away!

That's the foundation.

What will I do next?

-> Spin up one pagers for specific persona's pains
-> Design campaign Ideas from real life conversations
-> Create relevant Linkedin content

Your competitors are guessing what resonates.

You don't have to.

This is what it produced based on my 11 calls with prospect & clients in 1 relevant industry. 

1 prompt.

These are 3 simple ways I am becoming more AI Native as a business Owner. 

1️⃣ Krisp + Claude: Every call I have is recorded and transcribed. Client sessions, team syncs, sales calls. The insights I share verbally don't die in a voice note anymore.

Connect it to Claude, prompt away, mine it for ideas, content, and patterns.

2️⃣ Gmail + Briefcase: Every invoice and receipt gets auto-forwarded to my Briefcase email. 

It handles the bookkeeping and reconciliation automatically.

My accountant got our last month's books and had zero questions. 

3️⃣ Claude Team Skills: My team now produces work at the level I do. Not because they have years of AI experience. 

Because I packaged how I think into Skills they can run themselves.

It removes me as the bottleneck.

------------------------

The aim of these workflows is to generate and scale context within my business. 

🟥 Another AI project being worked on right is how to deliver amazing GTM workflows for our clients at unbelievable prices 🟥 

This is being done through productisation, using AI to combine the ability to create tables whilst maintain client context. 

This is coming soon 👀

Why I sit with my clients' sales team before touching AI.

Most builders open their apps and start building.

I open with a conversation.

On every new engagement, the first thing I do is sit with the sales team. 

Not the founder. 

Not the revenue leader 

The people actually doing the prospecting.

I ask them three things:

1. What is your core account ICP? What is the minimum you'd work with?
2. If you had one hour to research one account, what would you do?
3. When you're looking for the buying committee, who do you look for?

Then I reverse-engineer the AI workflow from the answers.

Most executives come to me with a list of things they want to build. 

1. Job board scraping. 
2. Glassdoor scores. 
3. Funding alerts. 
4. Headcount changes.

All valid. But when I dig in, they almost always that these are deemed nice to haves by the sales team, they tend to have much more nuanced requirements. 

You only find that out by sitting with the people who have to act on it.

Build the same workflow without that conversation and you end up with enriched data nobody acts on.

In this case, your buyer isn't the end user - they don't determine the success of your project.

I've hired 10+ GTM engineers. I've watched clients hire them and fail. 

I've spoken to agency owners who've hired and fired them on repeat.

The mistake is almost always the same.

We've confused a technical GTM engineer with a strategic one.

👉 Technical engineers build what you tell them. Fast, clean, capable. Brilliant, when someone strategic is pointing them in the right direction.

👉 Strategic engineers work backwards from the outcome. They push back on the brief. They ask why before how. They architect the system, not just the table inside it.

The problem: you can't tell them apart from their LinkedIn profile.

LinkedIn rewards content, not thinking. 

The person posting "10 Clay workflows that doubled our pipeline" looks strategic. They're not always. 

So you hire from what you can see. Three months later, reality looks nothing like what you expected.

When hiring, stop asking to see their work.

🔴 For a strategic hire — give them a real scenario you need solved and watch how they respond. Do they jump to the workflow, or ask what outcome you're trying to move?

🔴 For a technical hire — give them a detailed scope of what you need and see how clean and quickly they execute. Don't expect the them to blow you out the water with their GTM acumen.

Knowing which one you need is half the battle.

Been working on something interesting this week.

We took closed-won call transcripts from the last year and ran them through Claude. 

Not for summaries or call coaching - for prospecting intelligence.

The question was simple: 

what patterns show up in conversations where we actually won the deal?

Here's what we found:

The language is incredibly specific. Prospects said things like:

 "35% of developer time is spent writing SQL for data extraction - we'd rather have them working on code that adds value."

"we're running 100,000-200,000 row Excel templates and it's breaking at scale."

"file permissions set to 777 universally - it makes me want to pull my hair out."

The triggers are concrete.

1. PE acquisition in the last 12 months showed up in 3 deals. 
2. New CTO or VP of Engineering hired in the last 6 months in 5 deals. 
3. Contract expiring within 90 days in 4 deals.

These aren't vague - they're binary events you can track.

The tech stack pain is brand-specific.

"Redpoint is a bit behind on the whole Kubernetes thing and we're tired of waiting for them to catch up."

Legacy ETL tools like Informatica, Talend, and SSIS came up in 8 out of 10 calls. Not just "our current tool" - specific vendor names.

How this translates to account enrichment:

Signal 1: PE/VC acquisition (weighted 3x)
Crunchbase enrichment → last funding date + amount
Score: +30 points if TRUE

Signal 2: New leadership (weighted 3x)
LinkedIn People Search → find current CTO, VP Eng, CDO
Agent prompt: "For each executive at {{company}}, determine tenure in months. Flag anyone in role <6 months."
Score: +25 points per new exec

Signal 3: Legacy tech stack (weighted 3x)
BuiltWith enrichment → detect Informatica, Talend, SSIS, legacy tools
Cross-reference with job postings mentioning "migration" or "modernisation"
Score: +20 points if legacy detected + hiring for replacement

Signal 4: Active hiring for data roles (weighted 3x)
LinkedIn Jobs API → count open roles matching "data engineer", "ETL", "data platform"
Claygent prompt: "Analyse job descriptions at {{company}}. Do they mention migrating from legacy systems, building new data infrastructure, or Kubernetes/cloud adoption?"
Score: +20 points if 2+ relevant job posts

Signal 5: Quantified pain in public content (weighted 2x)
Claygent prompt: "Research {{company}}'s engineering blog, case studies, and Glassdoor reviews. Look for mentions of: manual data processes, developer time waste, Excel-based workflows at scale, data pipeline challenges. Quote specific phrases."
Score: +15 points if pain language detected

The scoring model:
80+ points = Tier A (immediate personalised outreach)
50-79 points = Tier B (sequenced outreach, AI Assisted Sequence)
30-49 points = Tier C (nurture, re-score monthly)

We ran this across 200 accounts. 

The insight isn't that AI is magic. It's that the language your best customers used before they bought is sitting in your call recordings.

Something that's helping clients spin up effective segmentation, scoring and messaging in their sales process.

Is specialised sales enablement documents.

Every campaign we spin up now gets paired with what I call an enablement doc.

It's not a brief. It's not a one-pager. 

It's the answer to five questions:

1. Why this industry?
2. Why now — what's happening in the market?
3. What challenges are they facing (or about to face)?
4. What case studies do we have?
5. What sales transcripts to get specific pain 

This allows us to scale internal knowledge.

You can use this for: 

1. Account Qualification 
2. Account Scoring 
3. Account 360 
4. Messaging Suggestions

Without this, your AI-generated output is just… generic noise.

With it, you're giving AI the context it needs to write something that actually resonates.

Most teams skip straight to "build the workflow."

The enablement doc is the bit that makes the workflow feel relevant.

My new favourite phrase

"claude --dangerously-skip-permissions"

If you're trying to build a company lookalike list and struggling to find good fit companies

Here's one way to go about it.

The reason lookalikes can be tricky is that most approaches rely on industry tags, headcount ranges, and sub-industries. 

The problem? Those signals are too broad. 

A fintech and a payroll software company can share the same LinkedIn industry tag but have completely different buyers.

Here's a more precise approach:

1. Start with a seed company — one of your best customers

2. Use Claygent to enrich what that company actually does — their real product, not their industry tag

3. From that enrichment, extract specific search queries (e.g. if they're an FP&A platform, your query becomes "FP&A platforms" or "FP&A services")

4. Run those queries through Perplexity to find companies that match that description

5. Pull the results back and re-qualify each result against your original seed company to validate the match.

You end up with companies that genuinely look like your best customer — not just ones that share a broad industry label.

If I was a new Revenue Operations leader and told to implement AI workflows, 

here's the thing that could make or break your first six months.

The sequence.

1️⃣ Start with the CRM audit — and don't take anyone's word for it.
Everyone will tell you the data is good. 

How many accounts have a domain? 
How many contacts are duplicated? 
Where are the silos? 
What lives in the CRM vs what only exists in someone's spreadsheet?

Your single source of truth needs to actually be one. Otherwise it doesn't matter what tool you buy or what workflow you build on top of it.

2️⃣ Sit with the sales team.

Not the CRO. The reps. Build the system around how they actually work.

Do they work from the CRM or LinkedIn? 
What are they tracking manually that you could automate? 
Do they struggle with data coverage or connects? 
What do they research when looking into an account? 



3️⃣ Pick your first build.

TAM mapping is the faster win. You're organising data that already exists rather than building something net new. Results in weeks, not months.

Get that working. 

Then layer in the signals, sequences, routing logic, and AI messaging on top.

⏪Most people do this in reverse. 

They buy Clay, build the workflows, and find the data problems three months later.

Get the foundation right first. Everything compounds from there.

taplio

The Battle

Rachid EHabi

Leo Branica

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The Battle

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Leo Branica

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