Elric Legloire

Outbound GTM strategy for B2B SaaS companies | SDR leader | Follow me + 🔔 for prospecting, productivity, and sales career tips for SDRs

If your outbound doesn't work, it's not a talent issue. It's a system issue.

Most B2B SaaS companies don't have a system for outbound. They have individual reps doing their own thing, different definitions of the same terms, no standard processes, and knowledge that lives in people's heads instead of in systems.

The result: chaos that looks like a talent problem but isn't.

I created the Outbound Kitchen System, a standardized system any B2B SaaS company can implement to make outbound predictable and scalable. Shared data. Shared language. Shared methodology.

The systems has 6 sections:

The Foundation - Strategy, market, ICP, product fit, company stage
The Ingredients - Accounts, data, signals, research
The Recipe - Messaging, sequences, channels, plays, playbooks
The Kitchen - Operations, tech stack, AI, productivity
The Team - Talent, training, enablement, coaching
Plus The Menu - Metrics, dashboards, forecasting, planning

$50M+ pipeline sourced. 30+ B2B SaaS companies. 7 years.

Two ways to implement the system:

- The Full Menu (done for you) - 90-day implementation
- Private Chef Retainer (Done with You) - Ongoing advisory

Ready to implement the system? DM me or book a tasting.

Want to learn the model first? 
Get a seat → newsletter.outbound.kitchen

SDR Manager

I help SDRs perform to their full potential and crush their quotas by mastering the mindset, habits, and skills needed to perform at the highest level.

Rippling started their outbound team too late

They weren't ignoring outbound. 
They had inbound working. 
They had programmatic emails running. 
Automated sequences going out at scale.

At ~$100M ARR, they hit a wall.

Same 1,000 target accounts. Programmatic outbound was generating 5-10 demos.

When they sat down to plan for growth, the math didn't work. They'd miss their targets.

And they had no SDR team to fix it.

Matt Plank (their CRO) says it:

"If you think automated emails or marketing forms alone can scale your business, you've clearly never scaled anything before."

They panicked. Hired Ashley Kelly to build an SDR org from scratch under massive pressure.

Here's what most companies underestimate:

Building an SDR team takes 6-12+ months.

Hiring. Training. Ramping. Getting them productive. You can't flip a switch.

The result after building the team?

Those same 1,000 accounts now generate 30-70 demos. 3-7% conversion vs the 0.5-1% from programmatic alone.

Human SDRs outperformed automation 7x on the same accounts.

If you're planning to add an SDR team "when you need it," you're already 12 months behind.

📌 Want the complete breakdown? 

I put together a 7-email deep dive on how Rippling, Snowflake, and Ramp built their outbound engines.

Click "Visit my website" to get them.

I build outbound systems for B2B SaaS | Outbound is a function, not prospecting

I got this question from a GTM leader in December:

"How do you divide SAM into territories for each rep? I can't find this anywhere."

This is the question nobody answers well.

Here's why: most companies are working from TAM, not ICP.

They think they have 100,000 accounts.
Reality: maybe 11,000 actually fit their ICP.

That's a 10x difference in how you staff, plan, and divide territories.

The framework that works:

1. Define your TAM (everyone who could theoretically buy)
2. Filter to SAM (can actually use your product today)
3. Narrow to ICP (highest conversion probability)
4. Remove anti-ICP (accounts that waste rep time)
5. Score remaining accounts by fit and value
6. Calculate capacity (600 accounts per SDR per year)
7. Divide by potential, not account count

The biggest mistake? Dividing territories by equal account count.

Rep A gets 600 Tier 1 accounts.
Rep B gets 600 Tier 3 accounts.

Same count. Completely different potential.

Why this exercise matters:
- Build accurate territory plans
- Inform your hiring model
- Understand territory potential

Without this: you're guessing on headcount, misallocating accounts, and can't measure territory performance.

Which step is hardest for you: defining ICP vs SAM, or calculating real capacity?

Most execs see inbound converting at 40% & outbound at 20%.

They ask: "Why is outbound underperforming?"

It's not underperforming. They just don't have the context.

I've seen this pattern at company after company.

Then I found HockeyStack's research on 50+ B2B SaaS companies, it backed up exactly what I was seeing:
- Outbound win rate: ~1/2 of inbound
- Outbound sales cycle: ~2x inbound

Real numbers:
- Inbound: 28% win rate, 54-day cycle
- Outbound: 17% win rate, 82-day cycle

I call this the 2x Rule.

This is not failure.
This is how outbound works.

The problem?
Most exec dashboards mix all revenue sources together.

So outbound looks broken when it's actually performing exactly as expected.

The fix: dedicated outbound reporting that compares outbound to outbound standards.

Give execs this mental model BEFORE they see your outbound numbers. It stops the "why is outbound underperforming?" question before it starts.

I wrote a full breakdown:
- The exact metrics execs need to see
- How to set realistic expectations

Comment DASHBOARD and I'll send it.

This is one of the best outbound books I've read.

It completely explains why so many teams struggle with it.

Here are my biggest takeaways from "Outbounding" by William Miller:

1. Why inbound reps struggle with outbound 

Inbound reps are trained to handle prospects who've already decided to change - they're essentially order-takers. Outbound requires diagnosing unrecognized problems, creating urgency around the status quo, and guiding prospects through early-stage change psychology.

2. Inbound vs Outbound = Different Buyer Psychology 

Inbound prospects have decided to change: 50%+ want demos immediately.
Outbound prospects don't know they have a problem: less than 10% are demo-ready. You're shifting from product-focused selling to change awareness creation.

3. Change Before Adoption

Outbound success follows Lewin's model:

- Unfreezing (create problem awareness)
- Changing (guide evaluation)
- Refreezing (solidify solution)

Most reps jump to "buy our product" when prospects are stuck in unfreezing.
Focus on why they need to change their current state, not why they should choose you.

4. Two Buyers, Two Messages

- ATL (executives): Care about ROI, risk, past failures, future threats
- BTL (managers/users): Care about features, functionality, present problems

ATLs live in the past and future while BTLs focus on present problems.
Use VAT Framework for ATLs: Value + Action + Time urgency.

5. "Validate, Don't Educate" for Execs 

Replace "Here's what we do" with "If you need to reduce costs, here's what works." Execs buy confidence in outcomes, not product features.

6. Solution Box Theory

What prospects think they're buying (Box A - your product) represents maybe 10% of the real value. The game-changer is Box B - their larger strategic initiative worth millions that your solution enables. ATL buyers have a 30% confidence gap in achieving Box B, and that's where urgency and big deals live. Stop selling your product; start selling their success in the bigger initiative. 

7. Account Research is a system, not a task

Systematic homework across company, executive, and industry dimensions transforms generic outreach into relevant conversations.

8. Toward vs. Away drives urgency

Prospects running away from pain buy 2x faster than those moving toward gain, diagnose their motivational direction.

--

📌 The fastest way to scale outbound sales?

It's not sending more emails.

It's learning from what billion-dollar companies do.

These 7 companies generated $6+ billion using systematic outbound (and their playbooks are more valuable than ever).

Want to see exactly how they built their sales machines?

I spent 100+ hours breaking down their complete strategies into 7 teardowns.

Click "Visit my website" at the top of this post to get instant access.

Gorgias built outbound automation before hiring a single SDR.

At $7,7K ACV, the unit economics didn't support an SDR army. So they engineered around it. 

(Early day ACV was $3k)

Today: 900 cold email inboxes. 5,000+ unique AI emails per day. 
Cost: $0.002 per email. (10 cents for 5k emails)

Not templates. Fully researched, unique messages.

Their system has three layers:

Research layer
- Pulls hiring signals, tech stack changes, events
- Feeds context to the LLM before any email gets written

Generation layer
- 400-500 line structured prompts (not short generic ones)
- GPT-4o-mini drafts the email
- PromptLayer tracks what converts

Review layer
- LLM categorizes every response and routes replies to reps
- Feedback loop improves prompts weekly

One sequence drove +150% positive replies vs. their old templates.

They evolved from 200 manually-written sequences to 10 modular AI-generated ones. When they added SDRs later, the team was layered on top of automation, not the other way around.

The key: they automate the process, not the conversation.

AI writes the first email. SDRs handle replies. That's where the skill matters.

Most companies hire SDRs first, then try to automate later.

Gorgias automated first, then added people where humans actually matter, conversations.

--

📌 I break down Gorgias & 6 other companies: Rippling, Snowflake, and Ramp's full outbound systems in a 7-part email series. 

Click "Visit my website" to get it free.

Old way: Train SDRs once. Hope it sticks.
New way: Build a practice culture with AI coaching.

Troy Johnson is back for Part 2.

Last time, he broke down how JumpCloud approaches SDR enablement. This time, he's going deeper, showing us exactly how to use AI role-play to build a practice culture that scales.

On the menu:

- How to use AI role-play beyond onboarding (5 use cases)
- How to get reps to actually adopt AI practice tools
- How to build an SDR progression program with AI coaching

Troy is the SDR Enablement Program Manager at JumpCloud. He's built AI role-play programs across onboarding, competitions, and progression tracks - and he's currently developing an SDR-to-AE accelerator using AI coaching.

This is show-and-tell format. He'll share his screen. Show us what's actually working.

When: Wednesday, February 18
Time: 6 AM PT / 9 AM ET / 3 PM Paris
Where: LinkedIn Live

Click "Attend" to register for the Outbound Live.  

Got questions? Drop them here to make sure they get covered.

Can't make it live? Register on Luma and I'll send the recording.

P.S. Outbound Live is a new show where outbound practitioners share their screen and build workflows live.

Daniel Puga, Elric Legloire and 41 other attendees

5 AI Role-Play Use Cases for Outbound Teams - From Onboarding to Objection 

The Outbound Paradox: 
While everyone rushes to replace SDRs with AI, elite teams are doing the OPPOSITE, investing MORE in outbound talent and outperforming competitors.

Want to see exactly how they're doing it? 👇

In the past 12 months, I've reverse-engineered the outbound engines of 8 Michelin-Star outbound teams:

• Snowflake : $4.6 B+ ARR
• Ramp: $1B+ ARR
• Rippling : $570 M+ ARR
• ClickUp: $300M+ ARR
• Pigment: $100M+ ARR
• Gorgias: $80M+ ARR
• Owner : $50 M+ ARR
• HockeyStack : $70 M+ pipeline

After 140+ hours dissecting their strategies, I discovered their secret sauce:

They treat outbound like a Michelin‑star kitchen, where both human expertise AND technology create something remarkable.
 
You'll get 8 detailed breakdowns:

• How they use AI as a force multiplier (not a replacement)
• Their contrarian outbound playbooks that others miss
• Complete tech-stack analysis 
• Real outreach examples that consistently convert

These teardowns normally live behind my Outbound Kitchen newsletter paywall. 

Today they’re on the house. 

I'll deliver one company breakdown every 1 day.

To get the full series: 

• Like this post
• Comment “outbound” below
• Connect with me if we aren't already (so I can DM you) 

Need it faster? DM me “outbound” and you'll get the email series today. 
 
I’ll send you the link ASAP.

I did the math on what bad contact data costs outbound teams.

It wasn't pretty.

You already know the drill:
- Bounced emails
- Wrong numbers
- Sequences that never land
- Follow-ups to people who left 6 months ago

The question isn't whether bad data costs you. It's how much.

Multiply every bounce by:
- The research time on accounts that went nowhere
- The pipeline you didn't build because you were dialing dead numbers
- The momentum you lost chasing ghosts

Bad data isn't just annoying. It's expensive.

The fix isn't buying more data. It's buying smarter.

Waterfall enrichment pulls from 20+ data providers in sequence. First source fails? It tries the next. And the next. Until you get a verified contact.

One source gives you gaps. Twenty sources working together close them.

This is why I started using FullEnrich.

Not because it's fancy. Because the math finally makes sense.

Brand partnership • I build outbound systems for B2B SaaS | Outbound is a function, not prospecting

Saad Khan

B2B Sales & Marketing Intern

Sales Director @Aligned | GTM Consultant

I sell the way I buy. 

Human and high performing sales leader - or at-least, I try to be.

Director of Sales And Business Development

250% Increase in Pipeline 
140% increase in Qualified Pipeline 

Apparently Hubspot CEO just found out about signal's. Thats cute - i've been doing signal sales before it was even called that (Ask for my 2022 QBR), additionally I was one of the first sales leaders that build a signal sales engine/playbook before it was glamorized by the likes of Clay etc. 

Whats the point of all of "signals"? The days of locking in your TAM are over. It's all about getting to who your SAM and how to use data to hit deals that are ready to be hit. Talk to people ready to talk and move deals along with data-backed insights vs guesswork. If you want to improve speed-to-lead, the real lever is knowing who is actually worth moving fast for.

For my team, that came from stacking signals, not treating any one of them as intent on its own. Here’s what we looked at:

1. Website visitor signals
Using website visitor deanonymization tools is a game changer.
Not only does it save time, it reduces guesswork. If all you see is a company name, you still have to dig through contacts to figure out who might matter. Knowing who is actually on the site and what they’re looking at gives you clearer starting context and makes it easier to create the right talk track.

2. Product signals
For PLG companies, signups are a weak signal on their own.
Roughly 40% of freemium users never activate or fully understand the product, which means treating every signup as sales-ready wastes time. So instead of looking at signups, we focused on what people actually did inside the product:
- Inviting teammates
- Hitting the paywall
- Reaching power-user behavior
- These actions told us who was getting past the activation hurdle.
- Then we layered in one more signal: return visits to the website.

Most users never came back BUT the ones who did were usually returning to log into the product, not to browse content.

That overlap mattered because it showed active evaluation (people moving between the product and the site as they tried to make it work).
Those were the accounts worth prioritizing.

3. Content signals
Another unique signal layer was content engagement. We cross-referenced those same people against our social content that explained the category and the pain we solve. That helped us see who actually understand (and are interested) in what we do.

At that point, we weren’t guessing anymore.
We could see who was active, who understood the product, and who was actually evaluating a purchase. This essentially create a lead funnel that enable use to focus on the accounts that were most likely to close.

I talk through this approach in more detail on Agents of Revenue with Spara.
How are you looking at intent signals to prioritize leads?

 Read the full write up on my playbook for winning inbound today in the comments below

#sales #khantent #management

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