This episode was originally recorded in French for Cognism’s Prospect podcast with Laetitia Fall. The English audio you’re hearing is an AI-translated dub generated with ElevenLabs. Original French version.

Listen on YouTube, Spotify, Apple Podcasts, and Snipd.

We discuss:

• Why outbound isn’t dead, but pipeline got roughly 10x more expensive (1% conversion in 2015 to needing 1,000 emails per opportunity in 2023, source: Winning By Design)

• Why global SDR headcount grew over 20% in a year while public layoffs dominated the LinkedIn feed

• The Owner.com benchmark: 40 appointments per BDR per month, 25% close rate, $70-80K sourced revenue per BDR per month

• When to hire experienced SDRs vs juniors, and the 12-meetings-per-month threshold that signals your playbook is ready

• Why ICP work beats tool selection (Tier 1 closes at 25%, Tier 2 at 5%, you need 5x the volume to compensate)

• Snowflake’s 140 ICP data points and why 10-15 is the realistic target for most teams

• Multichannel orchestration when only 30% of your prospects are reachable on LinkedIn

• The data-quality test most teams skip: coverage rate per persona, per market

• AI in outbound (January 2026): what actually works, why most LinkedIn AI messages fail, and the foundation AI needs (market, CRM, message principles, signals)

Referenced:

• Cognism’s original French episode

• Host: Laetitia Fall

  • LinkedIn

  • YouTube

• Sources cited in episode: Winning By Design, Insight Partners (Jeremy Donovan’s portfolio data), Owner.com BDR benchmarks, Snowflake ICP methodology

My biggest takeaways from this conversation

The State of Outbound in 2026

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[Live Webinar] Why GTM Orchestration Breaks Without Contact-Level Execution

Every contact in a buying committee takes a different path. Most ABM nurtures them identically. Devin Reed (ex-Gong) joins Influ2 to break down where orchestration fails and how contact-level execution fixes it. May 6, 10 AM CST.

Save your spot

A few weeks ago I saw a post from the CRO of Vanta.

Someone sent her a Quake rocket launcher replica, a reference to her time as a professional Quake player. She posted about it. She took the meeting.

Then a similar post: the CMO at Incident.io got a signed vinyl of their favorite album of all time. Same reaction. Same outcome.

Both worked for the same reason. The research is the system. The gift is the output.

I went down a rabbit hole figuring out how to turn this into a repeatable system for a GTM team running ABM on tier-1 accounts.

Here’s the math. If your top accounts are worth $200k–$1M in ARR, a $300 gift is cheaper than the cold email sequence you’d run instead. You’re not adding to the budget. You’re moving acquisition spend from one channel to a better one.

Cold outreach is harder every quarter (not dead, harder). Generic gifting is the same problem in a new channel, a branded notebook is just another ignored touch. One of my SDR team already sent bottles of champagne or tequila to celebrate promotions and new jobs. Better than nothing. Not personal enough to break through on your top accounts.

The whole system scales with Clay and Claude Code (or any similar tool) once you’ve tested it by hand on 10–20 accounts. Then run it on your top 200 with your GTM team.

Prompts at the bottom.

The 2-step play

Step 1: Find the clue + score the prospect. A specific personal detail the prospect has publicly declared about themselves.

Each prospect lands in one of four buckets:

• Identity: they declared a past identity (”ex-pro Quake player,” “former touring drummer”)

• Passion: they declared a specific, narrow obsession (”favorite album of all time,” “seen Radiohead 7 times”)

• Milestone: no clue, but a recent trigger in the last 90 days (funding, promotion, book launch)

• No gift: nothing strong. Revisit in 90 days. Expect this 70% of the time.

Step 2: Turn the clue into a gift + note. Specific to the clue, not the broader category.

If Step 1 fails, Step 2 doesn’t happen. Most of your prospects won’t have a strong enough clue. That’s the filter working. And realistically, not all prospects will share specific clues that you can use

P.S. I’m not talking about personal stuff from Facebook or Instagram. I mean public business stuff.

Step 1 - The clue

Not every personal detail qualifies. There’s a specificity ladder.

Only Passion and Signature clues qualify.

The rule: focus on the statement, not the source. A Signature clue in a LinkedIn About section is as valid as one on a 2-hour podcast. What matters is specificity and that the prospect said it themselves.

Look for Signature language in their own words: “favorite of all time,” “changed my life,” “in a past life I was...,” “I grew up doing X.” Most common in podcasts, long-form posts, and keynote intros.

Where to look:

• LinkedIn (About section, posts, articles)

• Podcast appearances and interviews

• Conference talks, YouTube keynotes

• Their own blog, Substack, Medium

• Published articles, book forewords

• Company page “About” and “Founding story”

Here’s the output when I ran this on Kyle Norton (CRO of Owner.com):

Interesting thing:

When I was testing the prompts, Perplexity was the one returning the best output. Just to let you know, last time I tested, Perplexity and ChatGPT were both equally finding stuff. This time, ChatGPT failed, so just for FYI. This a good reminder to always keep testing the AI models + benchmarking them.

The decision

Run the research on your prospects of your top accounts. For each one, the output is a tier.

Step 2 - The gift + the note

Once you have the clue, the gift has to map to the specific niche, not the broader category.

What to send for each bucket:

Identity gift: an artifact from the past identity. Quake CRO got a rocket launcher replica. A former touring drummer gets a signed pressing of the album they toured behind. A former chef gets the cookbook from their old kitchen. The rule: it has to be the specific artifact, not the category. Not “a guitar pick”, the pick from the show.

Passion gift: a high-signal item inside the niche they named.

• “Huge Radiohead fan” → the limited Kid A Mnesia box.

• “Deep into pour-over coffee” → a Lance Hedrick-recommended grinder.

Milestone gift: tied to the trigger.

• New Series B → a framed print of their funding announcement.

• Promotion to CRO → a signed copy of The Qualified Sales Leader.

• Book launch → buy 10 copies, send to their team with a note.

No gift: don’t force it.

Here are some recommendations I got for Kyle:

Personalized Solid Oak Martial Arts Belt Display & Trophy Rack on Etsy:

1. Go to https://www.etsy.com/listing/667908227/martial-arts-belt-display-personalized.

2. Select ‘Oak’ finish and your preferred number of belt slots (1-slot is cleanest for a single black belt display).

3. In the ‘Personalization’ field enter: Top plaque line 1: ‘Slow is Smooth. Smooth is Fast.’ | Line 2: ‘Kyle Norton’ | Line 3: ‘Black Belt — OpenMat MMA’.

4. Add to cart. Production + shipping is approximately 7–14 days (seller ships from the US with free shipping).”

The note is the other half.

Here’s the actual handwritten note sent with the Quake replica to Vanta's CRO:

Two things make this note work:

First, the note stacks two references. “Professional gamer” is the surface clue. “Killcreek” is her old gamer handle, and the Vanity Fair quote about the rocket launcher is the flex. That’s the detail that proves the note wasn’t AI-written or outsourced.

Second, the pitch is one sentence with proof. Two recognizable customer logos (Ashby, Amplitude) + one hard number (25% convert).

Here’s the template you can use behind every note:

1. Research proof - the surface clue, in the prospect’s own language

2. The rabbit hole - a deeper detail that required real effort to find

3. Gift bridge - one line connecting research to why you’re sending this

4. Pitch + proof- one sentence on what you do, with logos or a number

5. Soft ask - specific, low-friction (”chat next week?” not “would love to connect”)

6. Name + direct email - not a calendar link

~60–90 words. Handwritten on a real card.

Here's an example for Kyle:

And that’s it!

Hope this is helpful.

Talk soon,

Elric

The 3 prompts

Three prompts:

PROMPT 1: Research & Classify

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Here’s everything I published in Q1 at Outbound Kitchen, plus what’s coming in Q2.

This newsletter is also available in video and audio. Watch or listen on YouTube, Spotify, Apple Podcasts, or Snipd.

What we cooked in Q1

March 2026

• Podcast - OK28: How ElevenLabs is Scaling Outbound From 5% to 46% With Human SDRs Jonathan Chemouny (GTM at ElevenLabs) on rebuilding SDR motion and moving reply rates from 5% to 46%.

• Podcast - Best AI for Account Research? I Tested 7 AI Models
  March 2026 benchmark. Seven models, same account research test. Which one wins and where each breaks.

February 2026

• Newsletter — I tracked 232 outbound teams. Here’s what I found.
  47% of the 232 outbound teams I tracked grew their SDR headcount in 2025.

• Podcast — OK26: 5 AI Cold Call Training Scenarios Every Outbound SDR Team Should Run
  Troy Johnson (SDR Enablement at Jumpcloud) on the 5 AI roleplay scenarios.

• Newsletter — ClickUp built THIS before scaling dials
  The call prep system behind 3x pipeline and 150 dials/day.

• Newsletter — 9 ways I use Claude Code for outbound
  Call prep, tradeshow workflows, campaign building. The 9 workflows I run before touching Clay.

January 2026

• Podcast — OK25: How to Build a Profitable Outbound SDR Team
  Jay Glenn on SDR P&L math, headcount decisions, and why the payback window is now 9 months.

• Newsletter — How to prove outbound is working (to your CEO)
  The exec dashboard that answers the questions your CEO is actually asking.

• Podcast — OK24: How DoorDash Scaled Outbound from $291M to $8.6B
  Diane Ring (ex-DoorDash) on full-cycle field reps, city-level ownership, and scaling to $8.6B without SDRs.

• Newsletter — How to Divide Your Outbound Market Into Territories (7-Step Guide)
  TAM → SAM → ICP → territories. Seven steps for splitting a market cleanly.

• Podcast — OK23: How to Build SDR Enablement from Scratch
  Troy Johnson on when to hire your first enablement lead and the 3 things every outbound playbook needs.

• Newsletter — 100 emails → 1 meeting (2015). Now it’s 1,000+
  Cost per opportunity is at an all-time high. What actually moves reply rates in 2026.

• Podcast — OK22: How to Cold Call for Higher Connect Rates
  Jason Bay (CEO, Outbound Squad) on higher connect rates, better conversations, and meetings that show up.

What’s coming in Q2

The Pantry (Launch: May 20th)

I’m converting the paid newsletter into The Pantry. Building it now. I’ve been saying “soon” for months. Should have shipped it in Q1. Finally committing.

When I recorded the video yesterday, I had not finalized the launch yet. I worked on it this morning, and the date will be May 20.

How it splits:

• Free newsletter: keeps running. Free advice, frameworks, playbook walkthroughs.

• Paid (Pantry): the full system. Systems, prompts, files, Claude Code setups (agents, etc), AI workflows. Everything I build with customers or my previous full-time roles, turned into something you can run yourself.

What’s already built and landing inside:

I’ve shipped a lot of internal tools for customers recently using Claude Code. Templatized versions land in The Pantry so you can run them on your own data.

Three worth calling out:

• Tradeshow attendee scrapers: workflows for pulling attendee lists from the apps and sites where they actually live.

• Account-based outbound campaign system: the one I didn’t plan to build, and the one I’m most impressed with right now. Account list → contact discovery → outbound message, with a feedback loop baked in. Works across cold email, cold calling, and LinkedIn outreach. Built for sales teams running real multi-channel motions, not solo reps.

• Rep call-shadowing system: records call transcripts with reps, then turns them into recommendations. Flags where time is being lost, what could be done differently, and where reps can add more value. Built to sharpen team workflows.

The campaign system isn’t ready yet. I’ll share progress.

Pricing when Pantry launches: $79/month or $499/year.

To everyone who supported the paid newsletter until now: thank you. You made this possible. That’s why your current rate stays, a small way to say thanks.

• Already a paid subscriber? Nothing changes as long as you stay subscribed. (If you cancel and come back later, the new rate applies.)

• On the fence? Subscribe before The Pantry goes live to lock in the current rate.

Subscribe now

Q2 podcast lineup

• Growth Marketing director of Gorgias

• Co-founder & CRO of Reachdesk

• Growth Outbound working with a team of 20+ rep outbound team and building their own internal sales app

Systems and newsletters in the pipeline

• Account research system

• How to scale outbound teams in 2026

• How I use Clay for outbound

• Account-based gifting system

• Cold calling system

• How Snowflake uses AI for outbound

• Event system: how to maximize tradeshow output as a sales team

• How to build AI outbound systems for your team

• Trend watch: top outbound teams building their own apps for SDRs and AEs

Help I’m still looking for

Finalizing my US mobile phone number benchmark for 2026. I have datasets from Clay data providers (Upcell, Leadmagic, etc), Wiza, Apollo.io, Lusha, and LeadIQ. Still need ZoomInfo (normally should be good) and Cognism.

If you work at a lead gen agency or in RevOps and have access to either, reply to this email. Will pay for this.

Happy to be back!

Let’s get cooking,

Elric

Listen on YouTube, Spotify, Apple Podcasts, and Snipd.

Jonathan Chemouny is GTM at ElevenLabs, where he scaled outbound from 5% to 46% of pipeline in one year with a small distributed team. He previously built SDR teams at Intercom and Lattice. His team runs with no job titles, no standups, and no activity metrics, operating on async Slack and trust-based autonomy.

Listen on YouTube, Spotify, Apple Podcasts, and Snipd.

This episode was first published on outbound.kitchen.

We discuss:

• Why an AI-native company at 95% inbound decided to hire human SDRs instead of automating everything

• How ElevenLabs defines outbound -- pure cold vs. PLG-assisted -- and why the distinction changes the entire playbook

• Why finance and VC backgrounds outperform career SDRs, and the 4-round hiring process that screens for AI fluency and pressure tolerance

• The operating system: no standups, no pipeline reviews, async Slack (”Slack militaire”), and AI agents replacing management overhead

• SDRs running demos, flying to meet prospects, and attending events solo -- one rep skipped President’s Club for CCW Berlin and returned with 60+ SQOs

• The AI SDR handling multilingual inbound qualification (78% of decisions require no human intervention)

• WhatsApp as a prospecting channel in Europe and why LinkedIn is outperforming email

Referenced:

• ElevenLabs VP of Sales, Carles Reina: Inside ElevenLabs $330M ARR Sales Machine & The 20x Sales Comp Plan Reps Must Hit (20x Base-to-quota model)

• Jonathan Chemouny on LinkedIn: linkedin.com/in/chemouny/

• ElevenLabs: elevenlabs.io

My biggest takeaways from this conversation:

Read more

Subscribe now

By the way, if you’d rather watch or listen to this newsletter, you can find it on YouTube, Spotify, Snipd or Apple Podcasts.

Six months ago, I tested 6 AI models for account research.

GPT-5 Thinking took the crown.

Since then, the landscape has shifted again:

• OpenAI: ChatGPT 5.2 Thinking

• Anthropic: Claude Opus 4.6

• Google: Gemini 3 Pro

• xAI: Grok 4.2 (Beta)

Time for round 3.

What I’m testing today: 7 models:

• ChatGPT 5.2 Thinking (NEW)

• Claude Opus 4.6 (NEW)

• Gemini 3 Pro (NEW - The 2.5 model hallucinated last time)

• Grok 4.2 Beta (NEW)

• Perplexity Sonar Deep Research (returning)

• Grok 4 (returning)

• Argon by Clay (NEW - first time testing a Clay-native model)

Why I keep doing this:

Two things keep changing: new models are released, and existing models keep improving. The best tool for account research six months ago might not be the best one today. I don’t assume, I test.

1. Each model is great for specific use cases.

2. I test the model before I scale it with Clay, Cargo or n8n.

3. Account research is where model quality matters most. Your message quality and discovery call prep depend on the quality of your research.

1. Today’s Test: TrackRec + Replit

TrackRek:

Today I’m testing this for a company called TrackRec. They help companies hire sales talent faster, verifies quota attainment, ranks candidates on data, cuts time-to-hire.

If you’re a rep at TrackRec, you need to know: Is this company hiring salespeople? Who’s the decision-maker? What’s their employer brand? What tools are they using? Is there a reason to reach out right now?

Replit:

The company I’m testing on: Replit. $2.8M revenue to $150M+ ARR. $250M raise in September. 10+ open sales roles. CRO was on a podcast talking about hiring through his network.

I gave all 7 models the same prompt. 12 specific instructions. Same company, same prompt. Here’s what they found.

Disclaimer

These are my results. One company, one prompt, one test. Your results might be different. The point isn’t “use Perplexity.” The point is: here’s a framework for testing which model works best for YOUR account research.

Important

All models were tested in the web app, except Argon which was tested directly in Clay. Web app vs API vs Clay will give different results, different token limits, different output formats. Next time I will add API testing to the benchmark.ons.

2. What I Changed vs the last test

Last time: 3 criteria (web access, reasoning, additional insights).

This time: 6 weighted categories. Added Accuracy, Business Relevance, and Research Usability. Business Relevance asks: did it find what the BUYER needs? Research Usability: can a rep actually act on this?

Added an instruction completion table.

The prompt asks 12 specific things. Did you do what I asked? Yes or no. Perplexity did 10/12. Gemini did 1/12.

3. The Scores: Top 3 Deep, Bottom 4 Compressed

1. Perplexity Sonar — 9.2/10

Found the most. VP of SDR no one else found. Found both funding rounds. Found the CRO’s podcast and pulled quotes from it. One false claim: said RepVue had no profile when 5 other models found it. Best researcher, with one blind spot.

2. GPT 5.2 Thinking — 7.5/10

Zero false claims. 24 citations. Everything it said was true. But missed the January funding round, missed the podcast, missed 7 of 10 tech stack tools. Nothing wrong, but nothing unique. The safest model. Not the deepest.

3. Grok 4.2 Beta — 7.2/10

Fastest model, 56 seconds. Best RepVue depth, found sub-ratings no one else pulled. Honest about uncertainty, hedged on the $400M round instead of stating it as fact. But only found 1 tech stack tool.

Scoreboard (March 2026)

Bottom 4

• Grok 4 (6.1/10) — Found the $400M round but generic reasoning. Reliable, not insightful.

• Claude Opus 4.6 (5.6/10) — Best reasoning in the test. Worst champion identification. Missed the CRO despite checking 11 sources. Use for analysis, not finding people.

• Argon (Clay) (5.3/10) — Found the CRO and the podcast from just 4 pages. Most efficient model. But too thin for standalone research.

• Gemini 3 Pro (4.2/10) — Worst researcher. 1/12 instructions completed.

4. What I Found When I Verified Everything

After scoring, I manually verified every claim the models disagreed on. Six disputed facts. Checked LinkedIn, the articles, Replit’s website.

Zero hallucinations.

No model made stuff up. Last time, Gemini fabricated two executives. In this one, nobody invented anyone. That’s progress.

Three false claims

Claude said “no visible CRO.” Here he is. Ghazi Masood, CRO at Replit. Five other models found him.

Perplexity said “no RepVue profile.” Here it is. Overall rating 4.7, quota attainment 73%. Four models found it.

Only Perplexity found him. Nate Robbins, VP of Sales Development at Replit.

REPORTED vs. VERIFIED.

Press says the $400M round happened. Replit’s own website only shows $250M. Should your SDR reference funding the company hasn’t announced? Grok 4.2 hedged — said “follow-on talks.” That might be the most honest answer in the whole test.

Verification Summary

Zero hallucinations. 3 false claims total.

5. How I’d Actually Use These

Perplexity or GPT for the research, and if you want to go 1 layer deeper use Claude to analyse the findings.

• If you’re running 500 accounts: GPT is the safest. Zero false claims. You trade depth for safety.

• If you’re researching 10 high-value accounts: Perplexity. Spot-check the “not found” answers.

6. Where You Can Actually Use Each Model

Every model was tested in its web app (or Clay for the Argon Model). If you want to run these at scale in Clay or via API, here’s what’s available:

The scores in this test are web app scores. If you run GPT 5.2, Claude, or Gemini through Clay’s native integration, the output might be constrained by Clay’s token budget. Perplexity and Grok 4 are available directly in Clay. Grok 4.2 is beta and web-app only, you can’t use it in Clay yet. Claygent IS Clay’s model (Argon), so that score is exactly what you’d get.

In the next benchmark, I’ll test the models in the web app vs. Clay vs. API to measure the gap.

Here’s the prompt, If you want to get the prompt I used:

P.S. I’m also building a prompt builder for paid members so you can create your own account research prompt customized to your product.

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• Instant access to 40+ paid newsletters, including:

  • 6 AI prompts to find and reach accounts 10x faster

  • The Guide to Building an Enterprise Prospecting System

  • [Starter Kit] Step 1: Build your ICP + Persona Creation v1

• My Outbound Chef Kit: 130+ resources (20+ email templates, cold call scripts, AI prompts, top tools, and more). Value: $1,000+

And the best part? You can try it free for 7 days. Cancel anytime.

But I think you’ll love it!

👉 Start your free trial today.

If you only read LinkedIn, you’d think outbound is dead.

AI is replacing SDRs. Cold calling is dead. Email is dead. The SDR role is dead.

If you stopped there, you’d think outbound is in trouble.

Last year, I started tracking top teams to see what they’re actually doing. I also looked at global SDR numbers by country and company. I’ve been tracking 232 companies since March 2025.

I cross-referenced my research with data from Insight Partners, The Bridge Group, SaaStr, RepVue, and PeerSignal.

Here’s what the data shows for 2025:

• Global SDR headcount increased by 12%.

• 47% of the 232 companies grew their SDR teams in 2025.

• Top GTM teams like Rippling, Ramp, Vanta, and Owner.com expanded their outbound teams.

• AI companies are investing in SDR teams (OpenAI, Anthropic, ElevenLabs, Clay).

• Traditional industries, not just tech, are investing in SDRs too: logistics, banking, paint, marketing agencies, and more.

1. The market split into three tiers.

Global SDR headcount:

• 170,000 in March 2025.

• 190,000 by December, 2025.

That’s 20,000 new SDR roles in nine months.

And the hiring isn’t slowing down.

In December 2025, there were 11,259 open SDR roles globally, across 4,944. companies. By February 2026, that number hit 14,135 postings across 6,248 companies.

By Country (top 10)

The US holds 37% of global SDRs, but the growth is happening everywhere. Mexico grew 20%. South Africa grew 33%. Ireland grew 33%. The Philippines has 5,000 SDRs and grew 11%.

I have 213 companies with full March-to-December 2025 data. Here’s what I found:

Here’s what I found:

47% of companies grew their SDR teams. 12% cut. And 41% did neither, they added a head here, lost one there, averaging +1.5 SDRs per company across the full year.

And 41% did neither, they added a head here, lost one there, averaging +1.5 SDRs per company across the full year.

Aggregate Stats

• Net SDRs added across the 213 companies: +2,772

• Growers added +3,171 headcount (avg +32 per company)

• Decliners lost -532 headcount (avg -20 per company)

• Flat band: +133 across 87 companies (effectively flat)

• Median company grew +8.9% (+8 heads)

• Mean growth was +19.8% (pulled up by explosive growers)

The market is splitting into movers vs. the stuck middle.

By Broad Category

By Funding Status

54% of VC-backed companies meaningfully grew, but 13% meaningfully declined. No other funding category has this spread.

Biggest Growth Stories (Absolute Gains, March-Dec 2025)

The movers:

Cybersecurity went all-in. ThreatLocker (+60%), KnowBe4 (+52%), CrowdStrike (+12%). Six out of eight cyber companies in my data grew SDR teams. The security buyer is hard to reach, outbound is the play.

• CrowdStrike 280 (+12%)

• Fortinet 141 (+11.9%)

• Palo Alto Networks 113 (-1.7%),

• SentinelOne 113 (+27%)

• ThreatLocker 83 (+59.6%)

• Zscaler 42

• Rapid7 80 (+23.1%)

Traditional industries

Another thing I learned from this research: Traditional industries are also investing in SDR teams, not just SaaS companies anymore.

• HDFC Bank in India has 446 SDRs.

• Sherwin-Williams, a paint company, has 220.

• POOLCORP, which sells pool supplies, has 156.

• Labatt Breweries grew its SDR team by 67%.

• Accenture: 320 SDRs

• TP (Teleperformance), BPO/Outsourcing: 241 SDRs

The outsourcing market: 92% of SDR agencies in my dataset grew. Mid-tier agencies grew 20-49%. Companies want outbound, many just don’t want to build it in-house.

SaaStr and Emergence Capital surveyed 560+ companies and found 36% of B2B software companies cut SDR headcount in 2025. SDRs had the highest reduction rate among all sales roles.

Big Tech: Flat, Not Pulling Back

They’re maintaining, which for companies this size means they’ve decided the current headcount is roughly right. Amazon (AWS) is the exception worth watching.

Why the growth? My hypothesis:

More companies entering more markets means more sellers competing for the same buyers. Inbound alone can’t sustain growth when your category has 47 competitors instead of 12. Outbound is how companies create demand when demand doesn’t come to them.

If outbound were dying, the numbers would be going the other direction.

2. AI companies are hiring SDRs

39% of top AI companies with open GTM roles are actively hiring SDRs, data from Adam Schoenfeld at PeerSignal.

OpenAI is building its first SDR organization. Anthropic is hiring an 8-12 person BDR team. Clay, LangChain, ElevenLabs, and CoreWeave are all building SDR functions from scratch.

These are the companies building the AI tools that are supposedly replacing SDRs. And they are hiring SDRs.

There are currently 2x more Enterprise AE roles than SDR roles posted at AI companies, which means SDR hiring is coming, because those AEs need pipeline.

If AI were going to replace the SDR role, the AI companies would know first. Instead, they are investing in it.

3. What the winners built (and what the cutters got wrong).

Insight Partners surveyed 150 companies: top performers were 1.6x more likely to expand SDR teams. Only 2.9% of the best GTM teams eliminated their SDR function -- versus 9.8% of the broader market.

What I found in my dataset is similar to the data from Insight Partners.

The best GTM teams are investing more in SDRs.

• Rippling: 300 to 360+ SDRs (+20%)

• Ramp: 100 to 140+ (+40%)

• Vanta: 64 to 82 (+28%)

• Gong: 61 to 84 (+37%)

• Owner.com: 20 to 30 (+50%)

Since 2024, I study the best outbound teams:

Snowflake. Ramp. ClickUp. Owner.com. Rippling.

They don’t have a silver bullet. They invest heavily across the board:

• Systems: data infrastructure. AI and automation.

• Enablement.

• Talent: Hiring the right people.

Think of it like a Michelin-star kitchen. Each person is specialized. Each part of the system is optimized. They succeed because everything works together.

That’s what top outbound teams look like right now. Most companies are still looking for the one tactic that will fix everything. It doesn’t exist.

And the output tells the story.

• Owner.com and Ramp generate 3–4× more pipeline per rep than their competitors.

• ClickUp has shared publicly that they generate 3× more pipeline with the same number of SDRs.

• Verkada built a system where their MDRs (SDRs) are 4–6× more productive than traditional SDRs.

What’s the difference?

Productivity.

They built systems that let their team spend maximum time on high-quality prospecting, not preparing to prospect. If your reps are spending time on manual research, finding and cleaning data, writing individual emails from scratch, toggling between five tools, you’re burning budget on low-value work.

Top teams build backend systems that push data into tools reps already use.

AI

The best teams are using AI:

• Snowflake’s 15x’d their reply rate using AI to write outbound messages. They iterated 140+ times to get their prompts right.

• Gorgias cut 200 sequences down to 10 modular sequences and uses prompts to write targeted emails at scale.

• Ramp had a fully automated AI outbound motion and killed it a few months ago,they hit a ceiling. Now they’re investing more in the team, not automated outbound.

But here’s what most companies miss: most bought ChatGPT seats and told their teams to use it manually. That’s just adding another tool to the stack.

The real unlock: build AI workflows that run in the background and push outputs directly into your CRM or sales engagement platform, where your team actually works.

The cutters were cutting bad outbound.

Companies that cut treated SDR as a cost line. Hired bodies. Measured activity. Called it outbound. Companies that expanded treated SDR as a system. Invested in enablement. Measured outcomes. When the cost experiment got expensive, they cut. When the system produced returns, they scaled.

Most only had headcount.

Salesloft, a sales engagement platform, now has zero SDRs. They cut their SDR team. They’re PE-backed and focused more on efficiency than growth.

Outreach and Apollo also cut their SDR teams in 2024/2025 and in 2025 started rebuilding them from scratch.

I know three companies that tried cutting SDR teams entirely to replace them with AI. One early-stage company eliminated the team in 2024. By 2025, they hired a Head of BDR and eight BDRs on the floor. Two years without outbound pipeline, then a rebuild from scratch, because AI couldn’t replace the conversations that generate pipeline.

The other two, both around 1,000 employees, are in the same cycle. Cut. Trying to automate.

The SDR role is harder. That doesn’t mean it’s dead.

The role is evolving.

• Manager spans are shrinking, 6.4 reps per frontline lead, down from 8. That’s more coaching time per rep, not less.

• Ramp time hit 3.0 months, the fastest ever, down from 5.7 in 2020.

• Tenure rebounded to 1.9 years from a low of 1.4 in 2022. 97% of orgs now advertise advancement tracks.

GTM engineer

The GTM Engineer role is forming around it.

In November 2024, Brendan Short counted roughly 200 GTM Engineers globally, technical operators who build the infrastructure around SDRs (data pipelines, enrichment workflows, tool integrations) and other GTM teams.

He asked in one of his newsletters: The Rise of the GTM Engineer.

“Will this number be higher or lower this time next year? My bet: it will be much, much higher.”

Indeed, 15 months later:

• 2,125 people hold the title on LinkedIn.

• 67% got it in the last 12 months.

• One in four works at an agency.

4. The economics changed. The bar is higher.

The cost of outbound is rising from every direction.

Winning by Design documented a 10x conversion decline over 8 years: in 2015, 100 cold emails generated one opportunity. By 2018, it took 200. By 2023, it takes 1,000+. The volume required per opportunity has grown tenfold. And it keeps climbing.

Insight Partners advises 500+ B2B SaaS companies. Jeremy Donovan, their EVP of Sales, puts the breakeven at $40-50K ACV: below that, human outbound doesn’t pencil out. That threshold keeps rising. Companies with $20K ACV are redeploying SDR budget into inbound and channel partners.

The exception is extreme velocity, Owner.com runs 8-10K ACV with a 2-call, 6-day sales cycle and generates $70K/month per BDR in closed-won.

But that’s the exception, not the model.

SDR salaries

Base was flat at $55K for three years, then jumped to $60K in 2026. OTE stepped up from $80K to $85K in 2025 and held. Top performer ceiling peaked in 2024 ($131K) and has slightly declined since.

More attempts per opportunity. Higher cost per SDR (2015 → 2026). The economics of outbound have fundamentally shifted.

And yet the best teams are beating those economics. Bridge Group found pipeline per SDR up 26%, from $3M to $3.78M annually. Phone-centric teams generate 1.4x more qualified conversations than email-first teams. Insight Partners’ portfolio data puts it even starker: 70% of meetings are booked by phone. Not email. Not LinkedIn.

The gap between the top and the average is widening, not because of talent, but because of infrastructure & enablement.

You can’t outspend bad systems. You have to build better ones.

What this means for you

Someone posts “SDRs are dead” and it gets 500 likes. A survey says 36% of SaaS companies cut SDR teams. A vendor promises their AI tool can replace your whole team. And suddenly you’re in a board meeting defending the existence of your SDR org.

It depends who you’re learning from.

If you’re taking strategy cues from people who say outbound doesn’t work, you’ll make decisions based on that narrative. If you look at what Rippling, Ramp, Owner.com, and ClickUp are actually doing, building, expanding, investing in systems, the picture is different.

Being bad at outbound doesn’t mean outbound doesn’t work. It means you were bad at it.

Outbound works. Even in 2026.

And in competitive markets, it does something inbound can’t, it manufactures timing. While your competitors wait for hand-raisers, outbound lets you reach the right companies before anyone else knows they’re in-market.

Audit your system. Data infrastructure. AI workflows. Training and enablement. The right people. The winners aren’t doing one of these well, they’re doing all of them. If your system has gaps, fix those before adding headcount.

In March, I’ll share the full dataset (SDR headcount, salaries, GTM Engineer role, and more).

Until next time!

Elric

Sources:

• Original research via LinkedIn Sales Navigator (190K SDR headcount, 232 companies, 119 countries, March-December 2025).

• 2025 SDR Metrics and Trends Report: Bridge Group (SDR metrics, 351 companies)

• SaaStr/Emergence Capital (SDR team cuts, 560+ companies)

• Adam Schoenfeld/PeerSignal (AI company hiring)

• RepVue (SDR compensation)

• Winning by Design/Revenue Architecture (conversion trends)

• Jeremy Donovan/Insight Partners (Revenue Leadership Podcast E61)

As soon as you’re ready, here’s how I can help:

1. Outbound Consulting Call: Need quick help? Book a 40-min session here.

2. Outbound Private Chef:

   1. Part-time, I’ll build, optimize efficiency, and execute your outbound systems.

   2. Coaching/Advising: get tailored advice to fix your strategy, boost efficiency, and drive results.

3. Interested? Reply to this email or hit me up at bonjour@elriclegloire.com

Listen on YouTube, Spotify, Apple Podcasts, and Snipd.

Troy Johnson is the SDR Enablement Program Manager at JumpCloud, where he runs the SDR Enablement program for the Americas. His team books 80-90% of meetings through cold calls. He has over eight years in sales development, including six years managing SDR teams. This is his second appearance on the show, Part 1 covered SDR enablement foundations, and Part 2 dives into how they use AI to make reps more confident on the phone.

Listen on YouTube, Spotify, Apple Podcasts, and Snipd.

This episode was first published on outbound.kitchen.

We discuss:

• How JumpCloud uses AI role-play to certify SDRs on cold calls during onboarding, 100+ practice scenarios before going live

• Running a March Madness-style qualification competition to drive AI adoption and peer coaching

• The monthly rhythm for rolling out updated cold call talk tracks with live practice and manager demos

• Using Gong’s theme spotter to identify the most common phone objections and build targeted AI drills

• Building an SDR-to-AE progression program with AI call scenarios aligned to AE managers

• Why managers should practice AI role-play themselves to lead by example

• Tools used: Hyperbound, Orum, Gong, and ChatGPT Voice Mode as a free alternative

Referenced:

• Hyperbound: hyperbound.ai

• Orum: orum.com

• Troy Johnson on LinkedIn

• Gong

• ChatGPT

My biggest takeaways from this conversation:

Read more

• Instant access to 40+ paid newsletters, including:

  • 6 AI prompts to find and reach accounts 10x faster

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• My Outbound Chef Kit: 130+ resources (20+ email templates, cold call scripts, AI prompts, top tools, and more). Value: $1,000+

And the best part? You can try it free for 7 days. Cancel anytime.

But I think you’ll love it!

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The live sessions are back, first one in 12 months.

The podcast format has changed. No more talking-head conversations. We build live, show screens, walk through real examples.

First session: 5 AI Role-Play Use Cases for Outbound Teams and Cold Calling. Part 2 with Troy Johnson.

Built for GTM leaders developing cold calling skills at scale.

Register here.

You’ve seen this pattern before. Ramp, Owner.com, and now ClickUp.

Outbound teams producing outsized results.

Not just through headcount. Through systems.

This week, Kyle Coleman posted this. Same team size. 3x the pipeline.

In the post, he called out four systems driving the results:

1. XDR activity went from ~35 to ~150 calls per day through infrastructure changes

2. Automated signal monitoring that pushes intel into rep workflows programmatically

3. Every tool and process audited for friction, with XDRs co-authoring every change

4. AI embedded at every layer, context stitching, workflow automation, feedback loops

I already broke down ClickUp’s outbound strategy in a previous issue:

How ClickUp Scaled to $300M With 2 Outbound Teams

Since then, ClickUp’s Growth Ops team shared one of their recipes.

Today we focus on one specific system, the AI-powered call prep that turns a parallel dialer into a context machine. It’s the specific workflow under #4 that directly enables #1. When you use a parallel dialer like Nooks and go from 35 to 150 calls a day, you need a way to maintain quality at that volume. The AI-powered call prep is what makes that possible, it turns every dial into a context-loaded conversation.

Andy Cabasso (Growth Ops Manager) broke down the system architecture, what failed, and the one thing that made it stick.

P.S. key Results from Clickup:

• 11x LTV lift when customers move from self-serve to sales-assisted​

• 3x CAC reduction (50% from culture/team alignment, 50% from incrementality testing)​

• $1M pipeline/month from their inbound AI-SDR in the first month of piloting​ (via Retool)

• $300M+ ARR announced September 2025

• Same team size. 3x pipeline.

• Top SDRs booking 200+ meetings in a quarter.

The Recipe

ClickUp uses Nooks, a parallel dialer that lets reps dial six prospects simultaneously. When someone picks up, you have zero seconds to prepare. Before this system, reps had Salesforce, LinkedIn, Pocus, Outreach, and multiple dashboards open. Scrambling for context mid-conversation.

The Growth Ops team built a system that killed the scramble.

Here’s the exact architecture.

The system runs as an automated workflow in Retool. You could build something similar in Workato, n8n, Make, or Zapier.

Step 1: The trigger. Every time a prospect enters a sequence in their sales engagement platform, that platform sends a webhook to Retool with the prospect details. That webhook starts the workflow.

Step 2: Data pull. A set of SOQL and SQL queries pulls data from their data warehouse tables. They bring in CRM data about the contact and account, recent logged sales activities, details on the current email sequence the prospect is in, and product usage highlights: free vs. paid, signup date, key events.

Step 3: Enrichment. If there are gaps on the contact or company, an enrichment flow runs to update and fill in missing fields.

Step 4: Three parallel AI queries. Full context loaded. Three AI models fire at the same time:

• Query 1 (Perplexity): Looks up the company online and finds recent news relevant to ClickUp’s offer. Summarizes the context and how it ties into their pitch.

• Query 2 (OpenAI GPT) Summarizes the company context, the prospect’s activity history, and their product usage.

• Query 3 (Gemini): Uses everything they know about the prospect plus internal data to develop a full talk track for the rep.

Step 5: CRM write-back. A POST webhook writes these outputs into custom fields on the prospect record in their CRM. Those fields sync to their dialer.

The result: Prospect picks up. Rep already has background, activity summary, and a talk track on screen.

The rep sounds like they’ve been studying the account for 20 minutes. “Hi, I noticed your team has been using ClickUp for project management but hasn’t activated the automations, curious if that’s intentional.” That’s the difference between a hang-up and a conversation.

No training deck does that. Live context does.

That’s the recipe. Not more dials. Better conversations on every dial.

What Broke

The workflow worked on day one. The AI outputs were unusable.

Three things kept breaking:

1. Bad data queries from the warehouse.Wrong fields, stale records, incomplete data, everything downstream breaks. Andy Cabasso’s advice: "if the AI output is wrong, check your SOQL and SQL first. The data is usually the problem”.

2. Poor prompt engineering. Even with clean data, poorly constructed prompts produce generic or misleading outputs. If an AI output looks off, start by improving the prompt, tightening the instructions, and giving clearer examples.

3. Misalignment between what reps needed and what the system delivered. This one is the least obvious. The system might be technically sound, clean data, good prompts, but if it delivers information the rep doesn’t actually need in the moment, it’s noise.

Here’s what that looks like in practice:

“A prompt might tell a rep the prospect is on a free plan when they’re actually a paid customer. That’s a credibility-killer. And in a cold call, there’s no recovery from getting basic facts wrong.”

One wrong output and the rep never opens it again.

They tested everything. Different models for different jobs:

• Gemini performed best for structured, rule-based tasks

• GPT handled creative prompts and flexible phrasing

• Claude had decent real-time performance, but still lagged

• Perplexity was essential for up-to-date web context

No single model does everything well. If you’re running one model for every task, you’re getting mediocre output on most of them.

What Actually Made It Work

Their SDRs told ops when the outputs were wrong. Every time.

• The talk track was off → they said so.

• The data was stale → they flagged it.

• Format wasn’t useful → they pushed back.

Without that loop, the system would’ve looked good in a demo and died in production.

Most companies never get here. They invest in the architecture, the workflows, the integrations, the AI models. They ship something that looks impressive in a demo. And then reps quietly go back to their old way within a week.

The feedback loop itself is simple, a Slack channel or a weekly review. The hard part is reps who actually say “this output is wrong” and ops teams who actually fix it.

ClickUp got this right because they started with the culture before they scaled the technology. One of their SDRs flagged the original problem and then helped shape every iteration of the solution.

Talk tracks got more accurate. Reps stopped checking Salesforce manually. Call conversion improved. Each iteration compounded because the people using the tool were the same people shaping it.

The Takeaway

This is one system. ClickUp’s 3x didn’t come from the AI call prep alone. The first breakdown covers the rest of their outbound strategy. Read my first deep dive here.

Three questions to audit your own AI implementation:

1. Is the data correct? Audit your SOQL/SQL queries before blaming the model.

2. Are the prompts specific enough? Vague instructions produce generic results. Tighten the input, tighten the output.

3. Do the people using it have a voice in improving it? If reps can’t flag bad output and see it get fixed, they’ll stop using it.

ClickUp took reps from ~35 calls a day to ~150, with a top performer booking 200 meetings in a quarter. We’re still finding the ceiling on what a rep can do when the systems keep getting better.

Follow Kyle Coleman (Global VP Marketing, ClickUp) and Andy Cabasso (Growth Ops Manager) for the source material.

Until next time, build systems, not shortcuts.

Elric

What’s coming in February:

• Benchmark for U.S. mobile phone numbers (the first of several)

• 2025 outbound benchmark and recap

• How I use Clay

Thinking about upgrading to the paid newsletter? Here’s what you’ll get:

• Instant access to 40+ paid newsletters, including:

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  • [Starter Kit] Step 1: Build your ICP v1 + Persona Creation v1

• My Outbound Chef Kit: 130+ resources: 20+ email templates, cold call scripts, AI prompts, top outbound tools, and more, everything the best outbound teams use. Worth $1,000+

And the best part? You can try it free for 7 days. Cancel anytime.

But I think you’ll love it!

👉 Start your free trial today.

As soon as you’re ready, here’s how I can help:

1. Outbound Consulting Call: Need quick help? Book a 40-min session here.

2. Outbound Private Chef:

   1. Part-time, I’ll build, optimize efficiency, and execute your outbound strategy.

   2. Coaching/Advising: get tailored advice to fix your strategy, boost efficiency, and drive results.

3. Interested? Reply to this email or hit me up at bonjour@elriclegloire.com

• Instant access to 40+ paid newsletters, including:

  • 6 AI prompts to find and reach accounts 10x faster

  • The Guide to Building an Enterprise Prospecting System

  • [Starter Kit] Step 1: Build your ICP + Persona Creation v1

• My Outbound Chef Kit: 130+ resources (20+ email templates, cold call scripts, AI prompts, top tools, and more). Value: $1,000+

And the best part? You can try it free for 7 days. Cancel anytime.

But I think you’ll love it!

👉 Start your free trial today.

I’ve been using Claude Code since December. It hasn’t replaced Clay, but it’s changed how I use Clay.

Claude Code now comes before Clay in my workflow. It’s become my prep layer, the place where I do the thinking work before Clay does the enrichment and sequencing.

Here are 9 ways I use Claude Code:

1. Call prep that shows value (Before and during the call)

2. Tradeshow attendee workflow

3. Account-Based Campaign Builder

4. ICP/TAM analysis

5. Account list building

6. Merging and cleaning CSVs before Clay

7. Web scraping

8. For one client: a custom CRM lookup app because their CRM’s API was too limited for what I needed

9. Building a knowledge layer from customer conversations

For anyone who hasn’t used it:

Claude Code is Anthropic’s command-line tool that lets you give Claude tasks and it executes them, writing scripts, pulling APIs, scraping websites, processing files, building workflows. Think of it like having a technical co-pilot that can actually do things on your computer, not just answer questions.

It’s built for developers. I’m not a developer. But it turns out you don’t need to be one to get serious value out of it for outbound.

The problem with AI tools for outbound is the same problem with Notion. If someone hands you Notion and says “go,” you’re staring at a blank page. You need to see specific examples of how other people use it before it clicks. That’s what this newsletter is, the specific ways I’m using Claude Code for outbound right now, so you can see what’s possible and steal the ideas that make sense for you.

How I Use Claude Code for Outbound (On Top of Clay)

1. Call prep that shows value (Before and during the call)

I recently listened to Jeanne DeWitt Grosser, COO of Vercel (and former CBO at Stripe), talk about treating Go-To-Market (GTM) like a product, obsessing over the customer experience at every touchpoint. The line that stuck with me:

“Make every sales interaction great, whether customers buy or not.”

That made me rethink how I show up to prospect calls. I started asking myself: what am I actually bringing to this call? Because if the answer is just a list of qualifying questions, I’m not giving the prospect any reason to care.

So I started building things for them before the call even happens. Not just to show value, to educate them on how they should be thinking about their market:

• Here’s how you should think about your TAM.

• Here are companies showing specific pain signals online right now that could be great accounts for you.

• Here’s what the opportunity actually looks like.

And then I hand them a sample of what I’ve already done for them, so whether we end up working together or not, they walk away with something useful.

I’ve trained a Claude Code workflow on SPICED and Gap Selling, the same frameworks I use with clients. When I give it an account, it looks for:

• Situations that signal pain

• Problems I can tie to my services

• Critical events that might accelerate a deal

• Gaps between current state and where they want to be

And then I use that research to build actual deliverables I can share on the call:

• TAM analysis: for one of their markets, showing where the opportunity is

• In-market accounts: companies showing specific pain signals online that could be strong prospects for them, with the reasons why

• Account mapping: showing business units within a target account

• Account-Based Campaign Examples

The key decision I made here was to build these as visual dashboards instead of just handing over CSVs. I could give them a spreadsheet and let them scroll through rows. But when you show someone a visual breakdown of their market, where the opportunity is, which accounts are showing pain, how the segments break down, it lands completely differently. They can actually see what the opportunity looks like for their business. A CSV is data. A visual is a story.

Last week, I sent a message to a prospect before our call:

“Hey, I prepped a TAM analysis for the market you mentioned. Super excited to walk through it.”

During the call, they were already engaged. Because I’d already given them something useful before we even started talking.

Here's an example for the TAM analysis:

I think applying the idea of GTM as a product experience to outbound means exactly this: when someone gets on a call with you, they should get value whether they buy or not. Claude Code is what’s letting me do that without spending half my day on building this.

2. Tradeshow attendee workflow

This one’s still a work in progress, but it’s already saving hours of manual work.

Here’s what my old process looked like:

1. Go through the tradeshow website manually

2. Study the website to figure out what scraper I need (Apify, etc.)

3. Scrape the information

4. Bring it into Clay to cross-reference against the CRM

5. Look up contacts in another Clay table

6. Build a separate table to find contact info for people who aren’t in the CRM yet

7. Package the output and send it to my customer

That was multiple Clay tables, multiple tools, and a lot of manual decision-making at each step.

Now, depending on what the tradeshow gives you access to, there are a few ways I handle this with Claude Code:

Scenario 1: Tradeshow website (sponsors, speakers, exhibitors)

The most common one. I give Claude Code the tradeshow URL. It scrapes exhibitors, sponsors and speakers, figures out for each whether it’s a person or a company, checks if they fit my client’s ICP, looks them up in the CRM, finds the right contacts, and pulls contact info for anyone missing.

Scenario 2: Web app with full attendee list

Some tradeshows give you access to the attendee list through a web app. Sometimes Claude Code can scrape it directly via Apify or other tools. Other times I download the HTML and feed it to Claude Code so it can analyze the full list. Either way, it handles the enrichment from there.

Scenario 3: Mobile app only (what’s next)

Some tradeshows lock the attendee list behind a mobile app with no web version. Jordan Crawford recently showed a clever workaround for this: screen share from your phone to your computer, then use Claude Code to take screenshots and extract the information. I’m not doing this yet, but that’s my next step when a client needs it.

In all three scenarios, Claude Code handles what used to be steps 1 through 6 of my old process. The output is a CSV ready for Clay, which then pushes to the CRM. I send my client a Google Sheet with everyone prioritized — who to talk to first, who’s already a customer, who’s net new.

What used to take hours now takes under two. And I’m not done, the next version will include photos of each person and a talk track on why they’re worth talking to, so the team knows who to find on the floor. I’ve seen Jordan Crawford do something similar, and I want to take it further by pulling CRM context into that view.

3. Account-Based Campaign Builder

This is the one I’m most excited about, and the one I’m still actively building.

Right now, when I build a campaign for a client in Clay, it takes a long time. I’m creating multiple tables, clicking through enrichment steps, mapping contacts to accounts manually, writing messages one pattern at a time. The setup work before a single email goes out is significant.

Here’s what I’m building with Claude Code instead:

I start with two CSVs. One is the list of companies I want to prospect. The other is the contacts at those companies. I feed both to Claude Code, and from there, it connects the dots.

It maps which contacts belong to which companies. It looks at each account and finds the angles, who at that company could be a name-drop, who’s a recent hire, what’s happening at the company that creates an opening. It does the account research for each company on the list: what they do, what pain signals they’re showing, what’s relevant to my client’s value prop.

Then it pulls from my library of POV, talk tracks, cold emails and LinkedIn messages, templates I’ve built and refined across clients, and matches the right message to each situation and each contact. A recent hire gets a different message than a VP who’s been there three years. A company that just raised funding gets a different angle than one that just laid off their SDR team.

The output can go a few different directions depending on what I need:

• A CSV ready to go with the full emails or messages written out, plus a POV talk track for the reps so they know why each person is getting that message

• Or even pushing this directly to the systems where the rep are spending their time

• A prompt built specifically for Clay, so I can import it directly and Clay handles the enrichment and sequencing from there

Instead of building multiple Clay tables and configuring each one, I’m doing the thinking and the mapping in Claude Code first, and Clay becomes the execution layer.

I’m still building this out. The workflow isn’t fully systematized yet, right now I’m doing pieces of it across different sessions. But I can see where it’s going. When it’s done, I should be able to take a campaign idea, feed it two CSVs, and get back a fully researched, fully written campaign ready to load into Clay or hand to a rep.

I think this could be a game changer, not just for my own business, but for anyone running account-based outbound. The end goal is building this into a system that anyone can plug into. That’s what I’m working toward.

What Else I’m Running Through Claude Code Weekly

• ICP/TAM analysis: for clients and for my own prospect research

• Account list building

• Merging and cleaning CSVs before Clay

• Web scraping (or building Apify scrapers for harder sites)

• For one client: a custom CRM lookup app because their CRM’s API was too limited for what I needed

• Building a knowledge layer from customer conversations, I’m storing all my conversations with customers and prospects (call notes, pain points, objections, what they reacted to) and layering additional research on top (company data, market context, competitive landscape). Every conversation feeds it. Right now I’m using Clarify as my CRM and working on connecting it to Claude Code via MCP so this flows in automatically. The more context Claude Code has, the better everything else gets, call prep, account research, campaign setup. And when you store enough conversations across enough prospects, you start spotting patterns that sharpen your outbound messaging and targeting.

Why I use Claude Code over other AI tools?

It’s faster than Clay for certain tasks.

I love Clay. But for some things, merging CSVs, quick data analysis, prepping account lists, doing lookups, Claude Code is just faster. In Clay, you need to connect your accounts, create a table, set up your columns, configure your enrichments. That setup time adds up. In Claude Code, I describe what I need and it runs. For the stuff that needs to go into Clay, I prep it in Claude Code first so the Clay table is cleaner and simpler.

It connects to your stack.

Claude Code can connect directly to APIs and MCPs, Lemlist, EXA, Apify, client CRMs, so it can pull data, run lookups, and build lists on its own. That said, I only use it for reading right now. I don’t let Claude Code write to CRMs. I don’t trust it to not break something yet. Clay handles the write layer, which gives me a checkpoint before anything hits a client’s system.

It compounds.

Most AI tools are one-shot. You ask, you get an answer, you start over. With Claude Code, the workflows I build for one client, call prep, tradeshow scraping, ICP analysis, I reuse and improve for the next one. The frameworks I’ve trained it on (SPICED, Gap Selling) carry forward. Each client engagement makes the system better for the next client, even though I’m not sharing any data between them. The skills and the knowledge compound over time.

I’m just getting started.

I’ve been doing this since December. Most of what I showed you is V1 or V2. I can already see where this is going, and it’s way bigger than what I’m doing today.

I’m not saying any of this is perfect. The tradeshow workflow is still V2. The campaign builder is still coming together. But that’s the point, I’m building in public, and this is where I am.

The shift from “prepping to qualify” to “prepping to educate and show value” has changed how prospects show up to my calls. And Claude Code is what’s making it possible.

Elric

Thinking about upgrading to the paid newsletter? Here’s what you’ll get:

• Instant access to 40+ paid newsletters, including:

  • 6 AI Prompts for Researching Accounts & Cold Outreaching Them (10x Faster)

  • The Guide to Building an Enterprise Prospecting System

  • [Starter Kit] Step 1: Build your ICP v1 + Persona Creation v1

• My Outbound Chef Kit: 130+ resources: 20+ email templates, cold call scripts, AI prompts, top outbound tools, and more, everything the best outbound teams use. Worth $1,000+

And the best part? You can try it free for 7 days. Cancel anytime.

But I think you’ll love it!

👉 Start your free trial today.

As soon as you’re ready, here’s how I can help:

1. Outbound Consulting Call: Need quick help? Book a 40-min session here.

2. Outbound Private Chef:

   1. Part-time, I’ll build, optimize efficiency, and execute your outbound strategy.

   2. Coaching/Advising: get tailored advice to fix your strategy, boost efficiency, and drive results.

3. Interested? Reply to this email or hit me up at bonjour@elriclegloire.com

The podcast format has changed. No more talking-head conversations. We build live, show screens, walk through real examples.

First session: 5 AI Role-Play Use Cases for Outbound Teams and Cold Calling. Part 2 with Troy Johnson.

Built for GTM leaders developing cold calling skills at scale.

Register here

New podcast episode is up!

Listen on YouTube, Spotify, Apple Podcasts, and Snipd.

Jay Glenn is the founder of Jay Glenn Agency, where he helps B2B companies build financially sustainable SDR programs. After witnessing mass SDR layoffs in 2022, Jay developed a suite of P&L calculators that have become essential tools for SDR leaders proving ROI to their executives.

Listen on YouTube, Spotify, Apple Podcasts, and Snipd.

Grab the SDR P&L Calculator.

We discuss:

• Why 2022 was the wake-up call for SDR financial accountability

• The SDR P&L Calculator — walkthrough of inputs, outputs, and the 7.91x return benchmark

• The $50K ACV threshold for sustainable SDR models (and why lower ACVs fail)

• Customer lifecycle as the most underrated profit lever for SDR teams

• When to hire SDRs vs. when to invest in product and full-cycle AEs

• The Headcount Gap Calculator for modeling scale decisions

• Why inbound and outbound need separate conversion rate assumptions

• How to present SDR financials to your board (with or without good news)

Referenced:

• Jay Glenn on LinkedIn: ⁠https://www.linkedin.com/in/jayglenn/⁠

• Jay Glenn Agency: ⁠https://www.jayglenn.co/⁠

• RepVue (SDR compensation data): repvue.com

• Clay: clay.com

• TitanX (phone deliverability): titanx.com

My biggest takeaways from this conversation:

Read more

• Instant access to 40+ paid newsletters, including:

  • 6 AI prompts to find and reach accounts 10x faster

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And the best part? You can try it free for 7 days. Cancel anytime.

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A GTM leader asked me about this recently:

“CEOs don’t understand true lead sources and the number of touches needed to convert a lead. They need visibility into SDR/BDR work.”

Most companies have one revenue dashboard. Outbound, demo requests, PLG, partners, all mixed together.

Leadership sees “pipeline” and “revenue.” But they have no visibility into what outbound specifically contributes.

This creates problems:

You can’t prove outbound is working, even when it is. Outbound gets compared to inbound unfairly (more on this later). Budget conversations turn into “outbound isn’t producing.” And when cuts come, outbound goes first.

Most executives don’t understand what outbound actually takes. They see inbound demos converting at 40% and outbound converting at 20%, and they ask: “Why is outbound underperforming?”

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

The solution: a dedicated outbound section in your exec reporting. Organized by pipeline source. One that shows what outbound contributes, what it takes, and whether it’s working.

Here’s how to build it.

P.S. This is for execs and board meetings, so I’m not covering what front-line managers or reps should track and use.

PART 1: Why Outbound Needs Its Own View

1.1 The Visibility Problem

Outbound is buried.

When everything lives in one revenue dashboard, you can’t see what outbound specifically contributes. You can’t compare outbound to outbound standards - only to inbound, which isn’t fair. And budget decisions get made without understanding the motion.

The first question your exec dashboard needs to answer:

“What percentage of our pipeline - and revenue - comes from outbound?”

If you can’t answer this, you don’t have visibility.

Here’s what separation looks like:

Now you can see what each motion contributes - pipeline AND revenue - and have informed conversations about resources.

1.2 The Education Problem - CEOs Don’t Understand the Work

That’s the real problem. They see the numbers but don’t understand what it takes to produce them.

Track your own productivity metrics:

• Activities per account to activate

• Activities per meeting booked

• Activated accounts per opportunity

These aren't industry benchmarks to hit — they're YOUR baselines to track and improve. One company might need 80 activities per meeting, another might need 1000. The number matters less than knowing your number and improving it over time.

Once you know your numbers, the CEO understands:

• Outbound is not “send some emails and get meetings”

• There’s a predictable amount of work behind each conversion

• More pipeline = more resources (or better efficiency)

How outbound differs from inbound:

The 2x Rule for Setting Expectations

From my observation working at different companies - a simple mental model for executives:

If your inbound demo win rate is 40%, expect outbound at ~20%. If your inbound sales cycle is 60 days, expect outbound at ~120 days.

This is backed by data. HockeyStack analyzed 50+ B2B SaaS companies and found:

• Outbound conversion: 17% vs Inbound: 28%

• Outbound sales cycle: 82 days vs Inbound: 54 days

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

Part 2: The Framework: How to Structure Outbound Reporting

2.1 The Account Funnel

For mid-market and enterprise, use accounts, not leads.

Why? You’re working multiple contacts per account. Lead-based reporting doesn’t capture the full picture. Account-based shows the true conversion from target to won.

(Note: For SMB/high-volume, lead-based may still work.)

The Account Funnel Stages:

The key distinction:

• “Engaged” means they showed intent (passive).

• “Activated” means we did the work (active). An account isn’t activated until your SDRs have hit the minimum prospecting threshold, not just one touch.

The key question this funnel answers for execs:

“If I add 100 accounts to our outbound funnel, how much pipeline will I create?”

Build YOUR conversion rate from your own data over time.

2.2 Adding Quality to the Funnel

Counting isn’t enough. “10 meetings booked” doesn’t tell you if they’re the RIGHT meetings.

Add two quality dimensions:

Account Tier (ICP fit):

• Tier 1: Perfect fit, highest priority

• Tier 2: Good fit

• Tier 3: Acceptable fit

Contact Seniority (Above/Below the line):

• Above the line: VP+, decision-makers

• Below the line: Managers, individual contributors

Example dashboard view:

“12 meetings with Tier 1 accounts” tells a very different story than “45 meetings.”

2.3 Standardize Your Definitions

Without standardized definitions, you’ll spend board meetings arguing about what the numbers mean instead of what to do about them.

Define these before you build:

Winning by Design puts it well: “Measuring related sales metrics against different points creates confusion. You must measure against the same point.”

If you’re comparing outbound to inbound, compare at the same stage.

Action: Get alignment on definitions. Write them down. Share with the team. Do this BEFORE building any dashboard.

Part 3: The Dashboard - What to Actually Show Execs

3.1 The Metrics That Matter

Winning by Design breaks metrics into three types:

3.2 The Exec Outbound Dashboard

Execs need to answer 4 questions:

1. Is outbound contributing? (% of pipeline AND revenue)

2. Is it efficient? (Conversion rates, cost per opp, CAC)

3. Is it improving? (Velocity trend)

4. Are we on track? (Progress vs targets)

What to show:

A) Revenue & Pipeline Contribution (The headline)

• Revenue from outbound-sourced deals ($) + % of total revenue

• Pipeline generated from outbound ($) + % of total pipeline

• Comparison to other sources

• Progress vs target

B) Funnel Performance

• Accounts at each stage

• Conversion rates between stages

• Progress vs target for key stages (meetings, qualified opps)

• Trend over 4-5 periods

C) Quality Indicators

• Meetings/Pipeline by account tier

• Decision-maker involvement rate (% above the line)

• Win rate on outbound-sourced deals

• Average deal size

D) Velocity

• Pipeline velocity (current vs previous period)

• Trend over time

E) Productivity & Cost Metrics

Activity efficiency:

• Activities per meeting booked

• Activities per opportunity created

Cost efficiency:

3.2 What NOT to Show Execs

Keep these for manager dashboards:

• Activity counts (calls, emails, LinkedIn touches)

• Individual rep performance

• Open rates, click rates

• Daily/weekly metrics

Execs need outcomes and efficiency, not activity details.

3.3 Two Phases: Validate, Then Scale

Outbound isn’t a switch you flip. It’s a motion you build in stages.

Phase 1: Validate (0-18 months)

The goal isn’t revenue yet. The goal is proving outbound can work for your business.

Why 9-18 months? If you’re hiring new reps: one quarter to ramp, one quarter to build pipeline, one quarter to close. If your sales cycle is 90+ days, you won’t have reliable conversion data for at least two quarters. This is normal.

What to report:

• Accounts engaged and activated

• Meetings booked (with quality breakdown)

• Early pipeline created

• Learnings: what’s working, what’s not

What NOT to report:

• Revenue (it’s $0, and that’s expected)

• Win rates (you don’t have enough data)

• ROI (meaningless without conversions)

How to message it:

“We’re in validation mode. Our goal is to build a repeatable playbook. Here’s what we’re learning about our market, and here’s the quality of meetings we’re booking. In [X] months, we’ll have conversion data we can trust.”

You’re done with Phase 1 when you can answer: “If I add 100 accounts, how many opportunities will I get?”

Phase 2: Scale (18+ months)

Now you have data. Now you can talk about efficiency.

What to report:

• Revenue and pipeline contribution

• Conversion rates at each stage

• Pipeline velocity

• Cost per opportunity, Outbound CAC

• Progress vs. targets

How to message it:

“Outbound is contributing X% of pipeline and Y% of revenue. Velocity is improving. Here’s our path to [target].”

The mistake most teams make:

They try to report Phase 2 metrics during Phase 1. Revenue is $0, so they look like they’re failing. Execs lose confidence. Budget gets cut before the motion has time to work.

Don’t let this happen. Set expectations early: “We’re in validation mode. Here’s our timeline to Phase 2.”

Back to the original question:

“CEOs don’t understand true lead sources and the number of touches needed to convert a lead. They need visibility into outbound work.”

With this framework, they will.

They’ll see what outbound contributes - pipeline AND revenue by source. They’ll understand what it takes - 100+ activities per meeting, the 2x rule for expectations. And they’ll know whether it’s working - conversion rates, velocity, cost per opportunity.

No more mixed funnels. No more unfair comparisons to inbound. No more “why isn’t outbound producing?”

Paid subscribers: I’m working on a Dashboard Recipe, the definitions, formulas, and requirements spec you can hand to your RevOps team to build this in whatever system you use. Keep an eye on your inbox.

Thinking about upgrading to the paid newsletter? Here’s what you’ll get:

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• My Outbound Chef Kit: 130+ resources: 20+ email templates, cold call scripts, AI prompts, top outbound tools, and more, everything the best outbound teams use. Worth $1,000+

And the best part? You can try it free for 7 days. Cancel anytime.

But I think you’ll love it!

👉 Start your free trial today.

As soon as you’re ready, here’s how I can help:

1. Outbound Consulting Call: Need quick help? Book a 40-min session here.

2. Outbound Private Chef:

   1. Part-time, I’ll build, optimize efficiency, and execute your outbound strategy.

   2. Coaching/Advising: get tailored advice to fix your strategy, boost efficiency, and drive results.

3. Interested? Reply to this email or hit me up at bonjour@elriclegloire.com

Diane Ring led B2B strategy and operations at DoorDash from 2018 to 2023, joining when the company had ~500 employees and $291M in revenue, and leaving post-IPO with 15,000+ employees and $8.6B in revenue. She was on the leadership team for Merchant Strategy & Operations, where she helped scale the sales team from ~200 reps to thousands across North America and international markets. Most recently, she was Sr. Director of Sales Ops at TouchBistro, leading strategy and ops for a 100+ person GTM organization.

Listen on YouTube, Spotify, Apple Podcasts, and Snipd.

We discuss:

1. Why DoorDash used full-cycle field reps with no SDRs — and the 4 reasons handoffs killed velocity

2. The General Manager model: how city-level ownership created a “general manager of revenue” mindset

3. The 3 pillars for scaling outbound infrastructure: data, tooling, and culture

4. Account scoring when your data isn’t perfect: why “just start somewhere” beats waiting for accuracy

5. How to adapt outbound playbooks for international expansion (and why US vendors often fail in Canada)

6. AI coaching in practice: real-time monologue alerts, post-call scorecards, and AI roleplay bots for onboarding

7. Building rep-centric infrastructure: minimizing CRM fields and reducing tool sprawl

Connect with Diane:

⁠https://www.linkedin.com/in/diane-ring/

Referenced:

• Trellus (AI dialer + coaching): https://www.trellus.ai/

• Gong: https://www.gong.io/

• Outreach: https://www.outreach.io/

• Momentum: https://www.momentum.io/

My biggest takeaways from this conversation:

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I got this question from a GTM leader in December:

“I’m reading your newsletter. A topic I find very interesting (and I don’t find elsewhere) is how to divide the SAM into territories for each rep. Is this something you plan to cover soon?”

This is the question nobody answers well. Not TAM for investors. TAM/SAM/ICP for territory planning.

Here’s the step-by-step process:

P.S. Before we start: TAM, SAM, and ICP are not fixed. They evolve as your product and GTM evolve.

• New integrations → SAM grows (more companies can buy)

• New use cases → ICP expands (new segments become ideal)

• New markets → TAM grows (new geographies, new verticals)

• New GTM resources → SAM grows (add French speakers → France becomes addressable)

Snowflake started selling only to ad tech and gaming. That was their entire ICP, maybe <1,000 companies. Now they sell to dozens of industries.

This isn’t a one-time exercise. Revisit it quarterly as your product and team grow.

Why This Matters

When companies plan their sales team, they use TAM instead of ICP.

“We have 100,000 companies in our market.”

But if your ICP accounts convert at 25-30% and everything else converts at 1% or 0%, you don’t have 100,000 accounts. You have a much smaller number that will actually buy.

What happened at Chili Piper:

We overestimated the market. TAM looked huge—all B2B companies that book meetings.

Reality: ~11,000 accounts globally fit our ICP.

At 600 accounts per SDR (3-month contact cadence), that’s a maximum of 18 SDRs worldwide.

We over-hired. Gave reps “enough accounts.” But many had near-zero probability of converting. Productivity dropped. Eventually, we laid off part of the team.

If we had done this exercise before hiring, we would have known the real capacity of our market.

The 7-Step Process

1. Define your TAM → Total market size

2. Filter to SAM → Companies that COULD buy

3. Discover your ICP → Companies you SHOULD target

4. Define Anti-ICP → Accounts to exclude

5. Score all accounts → Every account has a tier

6. Calculate capacity → How many reps your market supports

7. Divide by equal potential → Fair territories

Step 1: Define Your TAM (Total Addressable Market)

What: Count the total number of companies in your market.

Output: A number. The upper bound.

This is your starting point. The broadest definition of who could theoretically be a customer.

Examples:

• Chili Piper: All B2B companies that book meetings with prospects

• Rippling: All employers (any company with employees)

• Snowflake: All companies that store and analyze data

• Wiz: All companies using cloud infrastructure

• Owner.com: All restaurants

TAM is mostly useful for investors and market sizing. It’s not useful for territory planning on its own.

Step 2: Filter to SAM (serviceable addressable market)

What: Filter TAM to companies that COULD buy based on product requirements.

Output: A smaller list of companies that fit your product.

SAM filters for:

• Right integrations (CRM, tech stack)

• Right geography

• Right use case fit

Examples:

• Chili Piper

  • TAM: All B2B companies booking meetings

  • SAM filter: Uses Salesforce or HubSpot

  • SAM: B2B companies on supported CRMs

• Rippling

  • TAM: All employers

  • SAM filter: Supported geos, 50+ employees

  • SAM: Mid-market employers in US

• Snowflake

  • TAM: All companies with data

  • SAM filter: Already on cloud (AWS/GCP/Azure)

  • SAM: Cloud-adopted companies

• Wiz

  • TAM: All companies using cloud

  • SAM filter: Meaningful cloud footprint

  • SAM: Companies with real cloud infrastructure

• Owner.com

  • TAM: All restaurants in US

  • SAM filter: 1-10 locations, offers delivery

  • SAM: Independent restaurants with delivery

Step 3: Discover Your ICP

What: Identify the common traits of your BEST customers.

Output: A list of detectable signals that predict success.

The Definition Most People Get Wrong

Mark Roberge:

“A great ICP is based on LTV, not lowest CAC, and that’s where a lot of people get that message wrong.”

Broken intuition #1: ICP = where our inbound demand is That’s not necessarily who you built the product for.

Broken intuition #2: ICP = where we have the highest close rates Only true if they stick around.

The correct frame: ICP = companies where you solve a significant problem.

When you solve a real problem, customers renew, expand, and refer. That shows up as high LTV. LTV is the signal—not the definition.

How to Discover Your ICP

• Quality data: Customer conversations (Gong), interviews, CS calls → “Why did you buy? What problem did we solve?”

• Quantity data: External sources at scale (Clay, LinkedIn) → Validate patterns across your customer base

ICP Must Be Detectable

If you can’t find the signal in external data, you can’t build target lists at scale.

• Chili Piper ICP traits: SDR + AE model, high inbound volume, routing complexity Where to detect: LinkedIn (SDR headcount), job postings (demand gen, RevOps)

• Rippling ICP traits: Distributed workforce, tool sprawl, HR/IT/Finance Ops exists Where to detect: LinkedIn (multi-location, ops roles), job postings

• Snowflake ICP traits: Data team exists, building analytics/ML/AI Where to detect: LinkedIn (data engineer titles), job postings (dbt, Fivetran)

• Wiz ICP traits: Security team exists, compliance pressure Where to detect: LinkedIn (security roles), job postings (SOC2, compliance)

• Owner.com ICP traits: High delivery volume, DoorDash/UberEats dependency Where to detect: Google Maps, Yelp, Uber Eats/DoorDash presence

Step 4: Define Anti-ICP

What: Identify accounts with near-zero probability of converting.

Output: A “do not contact” list.

These are companies where CAC doesn’t make sense and same for LTV. If you give these accounts to reps, it doesn’t matter how good they are, these accounts will never close.

Examples:

Chili Piper:

Anti-ICP: Not using Salesforce/HubSpot CRM

Why: Product doesn’t integrate

Rippling Anti-ICP: <30 employees, contractor-heavy, locked into PEO Why: Too small, no pain, switching cost too high

Snowflake Anti-ICP: No data team, Excel-only, on-prem only Why: No buyer, no use case

Wiz Anti-ICP: No cloud footprint, no security team Why: No attack surface, no one to sell to

Owner.com Anti-ICP: No delivery, fine dining, large franchises Why: No margin pain, corporate procurement

At Chili Piper, if we had scored all accounts upfront, we would have seen some had 0-1% win rates. We paid reps to work accounts that were never going to convert.

Step 5: Score All Accounts

What: Assign a tier to every account based on ICP fit.

Output: A ranked list of all accounts.

Why Score?

Snowflake’s data:

• Tier A accounts: 25% had an open opportunity

• Tier B-E accounts: 5% had an open opportunity

• Tier A converts 5x better

If you don’t score, you don’t know how much real potential you have.

If you don’t score, you don’t know how much real potential you have. You might give reps accounts with 0% probability of closing.

How to Score

Use a simple 2-layer system:

• Layer 1: Fit Score (0-100) — How well does this account match your best customers?

• Layer 2: Value Prediction — What’s the potential deal size?

I covered the full scoring framework here

→ Quick Start: Build Account Scoring for Outbound

Step 6: Calculate Capacity

What: Figure out how many reps your market can support.

Output: A maximum headcount number.

The Formula

ICP Account Count ÷ Accounts per Rep = Max Reps

The Contact Frequency Rule

Accounts should only be contacted every 3 months. Touch them more often and reply rates tank.

This means:

• If an SDR works 200 accounts/month

• And accounts should only be contacted every 3 months

• Each SDR needs 600 accounts minimum in their territory

The Chili Piper Example

• ICP count: ~11,000 accounts globally

• Contact cadence: Quarterly (3 months)

• Accounts per SDR: 600

• Max SDRs: 18 worldwide

If you hire 30 SDRs, you’re burning through accounts twice as fast. Reps run out of fresh accounts. Productivity drops.

The Key Insight: Optimize Before You Hire

Before adding headcount, ask: “Have we maxed out our current team’s productivity?”

Doubling productivity is cheaper and faster than doubling headcount.

I broke down the full capacity planning framework here

→ Here’s how to plan your 2026 outbound team (the right way)

Step 7: Divide by Equal Potential

What: Create territories with equal potential, not equal account count.

Output: Fair territories where every rep has the same opportunity.

Start with Geography

Don’t over-complicate this. Divide by geography first—where are your ICP accounts?

If you have:

• 10,000 ICP accounts in the US

• 1,000 ICP accounts in Europe

You know your US team will be ~10x the size of your Europe team. That’s your starting point.

Vertical specialization (by industry) comes later, when you have the GTM team maturity. Companies like Snowflake can dedicate reps to financial services or healthcare. But that requires scale and enough accounts per vertical to justify it.

How to Divide

It depends on what data you have:

Early (no historical data) What you have: ICP definition but no win rate data How to divide: Equal ICP accounts per rep

Some traction What you have: Win rate data by tier How to divide: Equal Tier A accounts per rep, then balance the Tier B/C mix

Mature What you have: Deep historical data How to divide: Use conversion rates to balance expected pipeline per territory

Early stage: Make sure each rep has roughly equal ICP accounts.

With historical data: Make sure each rep has equal Tier A accounts (your highest converters), then balance the rest so no one is overloaded with low-probability accounts.

Quota Should Reflect Territory Maturity

If a rep is working a territory with proven data that it’s working, their quota should be higher than someone starting a new territory from scratch.

Equal potential ≠ equal quota. A mature territory with momentum should carry a higher target.

The Mechanics Depend on Your GTM

The exact process for territory assignment depends on your model—inside vs. field, segment splits, language requirements, existing customer relationships.

But the principle stays the same: balance by potential, not by count.

Where to Get the Data

• Horizontal B2B SaaS: LinkedIn Sales Navigator + Clay → Headcount by function, company size

• Restaurants: Datalane → Restaurant-specific data, delivery status

• Ecommerce: Storeleads → Online stores, platforms

• Benefits/Brokers: Benefitflow → Employer benefits data

• Enrichment at scale: Clay → Combine sources, validate signals

Quick Reference: All 5 Companies

Chili Piper

• TAM: B2B companies booking meetings

• SAM: Uses Salesforce/HubSpot

• ICP: SDR+AE, high inbound, routing complexity

• Anti-ICP: No CRM integration

• Data: LinkedIn, Clay, BuiltWith

Rippling

• TAM: All employers

• SAM: Supported geos, 50+

• ICP: Tool sprawl, distributed, Ops roles

• Anti-ICP: <30 employees, PEO locked

• Data: LinkedIn

Snowflake

• TAM: Companies with data

• SAM: Cloud + analytics needs

• ICP: Data team, building AI/ML

• Anti-ICP: No data team, Excel-only

• Data: BuiltWith, HG Insights

Wiz

• TAM: Companies with cloud

• SAM: Cloud + security pressure

• ICP: Regulated, security team, compliance

• Anti-ICP: No cloud, no security

• Data: BuiltWith, HG Insights

Owner.com

• TAM: All restaurants

• SAM: 1-10 locations, delivery

• ICP: High delivery, marketplace dependency

• Anti-ICP: No delivery, fine dining

• Data: Datalane, Google Maps

The Takeaway

Your TAM doesn’t build pipeline. Your ICP does.

The 7 steps:

1. Define TAM — Total market (for investors)

2. Filter to SAM — Companies that COULD buy (product fit)

3. Discover ICP — Companies you SHOULD target (LTV signals)

4. Define Anti-ICP — Accounts to exclude (0% probability)

5. Score all accounts — Tier every account by ICP fit

6. Calculate capacity — How many reps your market supports

7. Divide by equal potential — Start with geography, balance by ICP accounts or Tier A accounts

Which step is the hardest for you right now?

1. Defining ICP vs SAM

2. Finding the right data

3. Scoring accounts

4. Calculating capacity

5. Dividing territories fairly

Hit reply and tell me, I’ll cover the most requested topic in a future issue.

Elric

🔒 Paid Subscriber Bonus: The Territory Planning Toolkit”

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Troy Johnson is the SDR Enablement Program Manager at JumpCloud, where he supports three outbound and inbound teams across the Americas. After six years as an SDR manager, he transitioned into enablement and ramped himself up by interviewing 15+ enablement leaders externally and using AI to find patterns across the conversations. He now runs a bi-weekly peer group with other SDR enablement managers to share best practices.

Listen on YouTube, Spotify, Apple Podcasts, and Snipd.

We discuss:

1. What SDR enablement actually is, the difference between a “head coach” and a “skills coach”

2. How Troy ramped himself up in 90 days by interviewing 15 enablement leaders and using AI to find patterns

3. The three essential components every SDR playbook needs from day one

4. How to split your time between content, coaching, and training (the 30/30/30 framework)

5. When to hire your first SDR enablement person — team size, motions, and complexity signals

6. The ideal onboarding structure: 2-3 weeks of foundations + “Prospecting Bootcamp” through day 60

7. Using AI to accelerate business acumen — the underrated use case most teams miss

Where to find Troy:

On LinkedIn: ⁠https://www.linkedin.com/in/techsalestroy/

My biggest takeaways from this conversation:

The Head Coach vs. Skills Coach Model

Read more

• Instant access to 40+ paid newsletters, including:

  • 6 AI prompts to find and reach accounts 10x faster

  • The Guide to Building an Enterprise Prospecting System

  • [Starter Kit] Step 1: Build your ICP + Persona Creation v1

• My Outbound Chef Kit: 130+ resources (20+ email templates, cold call scripts, AI prompts, top tools, and more). Value: $1,000+

And the best part? You can try it free for 7 days. Cancel anytime.

But I think you’ll love it!

👉 Start your free trial today.

“AI is replacing SDRs.”

I keep seeing this on LinkedIn.

So I started tracking the data myself.

Based on my tracking via LinkedIn Sales Navigator:

• March 2025: 170,000 SDRs globally

• December 2025: 190,000 SDRs globally

That’s +20,000 SDRs. +12% growth in 9 months.

AI isn’t replacing SDRs. But something else is happening that most GTM leaders are missing completely.

The Reality Is More Nuanced

I’ve talked to companies that fully replaced their SDR team with AI.

One of them fired their 3 BDRs the day after we spoke. They wanted to do everything with AI. No humans. Full automation.

12 months later, they hired a new Head of BDRs and are rebuilding the team internally.

AI is making productive SDRs more valuable, and unproductive ones redundant.

That word, productive, is what this newsletter is about.

The Economics Are Broken

Let me show you something.

Conversion rates have collapsed:

• 2015: 100 cold emails → 1 opportunity

• 2018: 200 attempts → 1 opportunity

• 2023: 1,000+ attempts → 1 opportunity

That’s a 10x decline in 8 years.

(Source: Book: Revenue Architecture by Jacco van der Kooij, CEO of Winning by Design)

Why the collapse?

It’s saturation. The same thing that happened to digital ads is now happening to outbound:

• More SaaS companies, more providers

• More sales teams sending more volume

• Inboxes are flooded

• Most messages aren’t relevant

• Buyers are overwhelmed and tuning out

Meanwhile, SDR salaries rose from $44K (2015) to $80K (2024) to $85K today—and now they’ve plateaued.

Here’s the math that should worry you:

Salaries doubled. Conversion rates collapsed 10x. That means your cost per opportunity has increased dramatically, even though salaries have finally stopped rising.

You’re paying more per output than ever before.

Here’s the forcing function:

If conversion rates keep declining, and you can’t reduce headcount costs, and you’re running the same playbook, something has to change.

You can’t out-hire this problem. You can’t out-train it.

There’s only one lever left: Productivity.

The Formula Most Leaders Miss

Most GTM leaders get two out of three things right.

Here’s what I’ve learned working with outbound teams over the past 14 months:

Outbound Results = Talent × Productivity × Enablement

Not addition. Multiplication.

Most leaders invest heavily in two of these:

• Talent: Hire more SDRs. Hire experienced reps. Build out the team.

• Enablement:Train them. Coach them. Run call reviews. Improve messaging.

Then they step back and say: “Go figure it out.”

It doesn’t work.

Why? Because they’re missing the multiplier: Productivity.

Let me be specific about what I mean by productivity.

It’s not about working harder or spending more hours on the phone. It’s about maximizing the time your team spends on actual prospecting—not on manual tasks that can be automated today.

In 2022, if you wanted to enrich data automatically, you needed technical people to build it. Today? Tools do it for you. AI can extract intelligence from calls, update your CRM, research accounts, all in the background. What wasn’t possible three years ago is now table stakes.

But productivity also means focusing on the right accounts—the ones with the highest chance to convert, at the right time, with the right information. Because if you’re sending generic messages to the wrong companies, it doesn’t matter how many hours your reps work.

Productivity is all of this working together.

Here’s what I saw across 15 companies I worked with in 2025:

• They pick one data provider and call it done

• They buy one tool and expect magic

• They let SDRs figure out the rest on their own

• Then they wonder why results aren’t coming

They invest in talent. They invest in enablement. But they underinvest in the systems that make talent and enablement actually work.

If Productivity is low, you can multiply Talent and Enablement all day. The result stays flat.

Why Productivity Gets Ignored

Here’s what I think is happening.

In 2020, maybe even 2024, you could get away with ignoring productivity. Hire people. Train them. Let them grind. Results showed up eventually.

But the environment has changed:

• Conversion rates are down 10x

• Salaries doubled while output collapsed

• Cost per opportunity is at an all-time high

• Saturation is increasing

• Buyers are harder to reach and quicker to ignore

The old playbook, hire more, train, doesn’t scale anymore. It’s hitting a wall.

Here’s what’s possible when you get productivity right:

If a rep is booking 10 meetings a month with the wrong systems, they should be booking 20 with the right systems.

That’s not a stretch. That’s table stakes.

Top companies like Owner.com and Ramp are getting 3-4x their competitors’ results. And they’re not doing it by hiring 3-4x the headcount.

They’re maximizing productivity per rep before hiring more.

What Productivity Actually Means

This is where most leaders get confused.

Productivity is NOT:

• The number of tools you’ve deployed

• The automation percentage you can report to the board

Productivity IS:

Contacting the right accounts.

Tier 1 accounts convert at 5x the rate of lower tiers. If your reps are spraying across 40,000 accounts instead of focusing on the right 1,000, you’re burning capacity.

Having the right data.

Coverage. Quality. Accurate phone numbers. If 40% of your numbers don’t work, your “productive” calling time is actually 60% productive.

Knowing the context.

Your system should know who’s already familiar with your brand—who’s visited your website, who’s a former champion now at a new company, who’s shown intent. These signals should feed prioritization automatically, not require reps to dig for them.

Removing manual work.

Research, data cleanup, message writing, this should happen in the backend, not eat up rep time.

Maximizing revenue-generating activities.

If an SDR works 40 hours a week, how many of those hours are spent actually prospecting vs. preparing to prospect?

Here’s a simple benchmark:

Your reps will spend ~20% of their time on internal tasks (meetings, 1:1s, admin). That’s unavoidable. The question is what happens with the other 80%. Most teams I see are at 40-50% actual prospecting time. The rest goes to list building, data cleanup, manual research. Best-in-class teams hit 70-80% prospecting time. That gap, from 50% to 80%, is nearly doubling productive capacity with the same headcount.

And this compounds. When your reps ARE prospecting, are they targeting the right accounts? Time on prospecting × ICP quality = actual output. Fix one without the other and you’re still leaving capacity on the table.

One question cuts through the noise: Does this tool add clicks or remove them?

The Backend vs. Frontend Test

Here’s a simple framework you can use immediately.

When you’re evaluating a tool, ask: Is this for the backend or the frontend?

Frontend tools = tools reps interact with directly.

• They add clicks

• They require training

• They eat into prospecting time

Backend tools = tools that run automatically.

• AI workflows

• Data enrichment

• Automation that feeds outputs to where reps already work

Most companies buy frontend tools and call it “investing in productivity.”

They’re wrong.

Real productivity investment means building backend infrastructure so your reps can focus on selling:

• AI workflows that do account research automatically

• Data enrichment that runs on a schedule, not on-demand by reps

• Automation that routes the right accounts to the right reps with the right context, already in their CRM

Your reps shouldn’t spend time cleaning data.They should be prospectors.

This Is Complex. That’s The Point.

I’m not going to pretend this is easy.

Building real productivity infrastructure, data systems, backend automation, signal routing, is complex. It requires thinking through a lot of moving pieces that most teams try to do manually.

And here’s the thing: there’s no single tool you can buy to solve this. Each company is different. Some companies, like Pigment, have built their own custom systems from scratch.

Should you build or buy? That’s one of the main questions I’ll be exploring in this newsletter throughout the year. Because it’s not a simple answer, and getting it wrong is expensive.

But that complexity is exactly why it’s a competitive advantage.

Most teams won’t do this work. They’ll keep hiring, keep training, and keep wondering why results aren’t scaling.

The ones who invest in productivity will compound.

What This Means for Your Team

If productivity is the multiplier, here’s what changes:

Maximize output before hiring.

Top outbound teams aren’t scaling headcount first. They’re getting more from each rep before adding more reps. That’s the model.

Bring in Ops earlier.

Most companies wait too long to invest in operations and data roles. If productivity is the multiplier, you need people building the systems, not just people working in them.

Measure what matters.

Stop tracking:

• Number of AI tools deployed

• Automation percentage

• Cost savings

Start tracking:

• Time reps spend on revenue-generating activities

• Conversion rates by account tier

• Data enrichment rate and accuracy

If you can’t measure productivity, you can’t improve it.

The Transformation

Here’s what this looks like in practice.

Before (most teams today):

• Reps spend 40+ hours/week, but only 15-20 hours actually prospecting

• 30-40% of phone numbers don’t work

• Every rep sources their own data, does their own research

• Results: 10 meetings/month

• Cost per meeting: high + increasing

• Response: “Hire more reps”

After (productivity-focused teams):

• Reps spend 40 hours/week, 30+ hours actually prospecting

• Data is validated, enriched, and routed automatically

• Research happens in the backend before reps touch accounts

• Results: 20-40 meetings/month, consistent or improving

• Cost per meeting: low + stable or decreasing

• Response: “Maximize before we scale”

Same headcount. 2-4x the output.

That’s what investing in productivity looks like.

Two Questions to Ask Yourself

Before you hire another SDR or schedule another training session, ask:

1. What high-value activities should your reps focus on exclusively?

2. What’s currently distracting them that AI/tools/data should handle?

If you can’t answer these clearly, you have a productivity problem.

And no amount of hiring or enablement will fix it.

Why I’m Writing This

This isn’t just about what I’m focused on in 2026.

I’m seeing this as a common challenge across almost every company I talk to. GTM leaders are stuck, conversion rates are declining, cost per opportunity is rising, and the old playbook isn’t working. But most don’t know where to start fixing it.

Productivity is complex to solve. There’s no single tool, no quick fix. It requires rethinking how your systems work together.

That’s exactly why I’m excited to dive deep into this topic this year.

Whether it’s the newsletter, the podcast, or the work I do with customers—productivity is the thread that ties it all together. I’ve been working on this with customers throughout 2025, and I’m going all-in on it in 2026.

This newsletter is just the beginning. More to come.

If you want to explore what this looks like for your team, reply to this email. Let’s talk.

Elric

Coming in January based on your questions:

• TAM vs SAM vs ICP (updated version) → Next week

• Outbound dashboards and reporting for exec/board meetings

• How I use Clay as my outbound orchestration layer

Also posting in January:

• Best mobile data provider in North America for 2025

• Outbound benchmarks for 2025

The podcast is back too. If you missed the first episode of the year, listen here.

Thinking about upgrading to the paid newsletter? Here’s what you’ll get:

• Instant access to 40+ paid newsletters, including:

  • 6 AI Prompts for Researching Accounts & Cold Outreaching Them (10x Faster)

  • The Guide to Building an Enterprise Prospecting System

  • [Starter Kit] Step 1: Build your ICP v1 + Persona Creation v1

• My Outbound Chef Kit: 130+ resources: 20+ email templates, cold call scripts, AI prompts, top outbound tools, and more, everything the best outbound teams use. Worth $1,000+

And the best part? You can try it free for 7 days. Cancel anytime.

But I think you’ll love it!

👉 Start your free trial today.

As soon as you’re ready, here’s how I can help:

1. Outbound Consulting Call: Need quick help? Book a 40-min session here.

2. Outbound Private Chef:

   1. Part-time, I’ll build, optimize efficiency, and execute your outbound strategy.

   2. Coaching/Advising: get tailored advice to fix your strategy, boost efficiency, and drive results.

3. Interested? Reply to this email or hit me up at bonjour@elriclegloire.com

Last year I went quiet. Too much client work, not enough building in public. That changes in 2026.

This year I’m going deeper, more data, more benchmarks, more of what actually moves the needle in outbound. Starting with the operational side that most teams ignore entirely.

Which brings me to today’s episode.

The average cold calling connect rate is 5.4%. Top teams hit 13-15%. That gap isn’t just about what reps say on the phone, it’s about everything that happens before the conversation: data quality, verified mobile numbers, dialers that don’t show up as spam. The operational foundation.

Jason Bay (CEO of Outbound Squad, worked with Rippling, Shopify, Zoom) breaks down what’s actually working right now, connect rates, conversion benchmarks, and the skills that separate average from elite.

Listen on YouTube, Spotify, Apple Podcasts, and Snipd.

More coming this year: benchmarks on mobile data providers, a weekly live show, and the data behind why outbound isn’t dead, even if your team is struggling.

Talk soon.

Jason Bay is the Founder of Outbound Squad, where he trains sales teams at companies like Rippling, Shopify, and Zoom on cold calling. He's known for his data-backed approach to cold calling frameworks, drawing on research from Gong and Nooks analyzing 100K+ calls. His methods help reps move from the average 4.6% conversion rate to 20-35%, and get meetings that actually show up.

Listen on YouTube, Spotify, Apple Podcasts, and Snipd.

We discuss:

1. Why cold calling is harder but not dead — and what the data from Rippling, Gong, and Nooks actually shows

2. The “Permission-Based Opener”: how to survive the first 80 seconds (where most cold calls fail)

3. The “Reverse Pitch”: why problem-based language gets 3x more meetings than product pitches

4. “Money Questions”: how top reps expose gaps and create real reasons to meet

5. How to diagnose cold calling problems rep-by-rep: activity → connect rate → conversion → show rate

6. The tactics behind 75-80% show rates (when the average is only 56%)

7. Jason’s 3 non-negotiable cold calling principles

Referenced:

• The hidden power of cold calling: Insights from 300M calls

• Book: Why Cold Calling Sucks (affiliate link)

• How the Top 1% of Reps Run Cold Calls

Where to find Jason Bay:

Founder of Outbound Squad, sales trainer for companies like Rippling, Shopify, and Zoom

• On LinkedIn: ⁠https://www.linkedin.com/in/jasondbay/⁠

• Outbound Squad: ⁠https://outboundsquad.com

My biggest takeaways from this conversation:

Read more

• Instant access to 40+ paid newsletters, including:

  • 6 AI prompts to find and reach accounts 10x faster

  • The Guide to Building an Enterprise Prospecting System

  • [Starter Kit] Step 1: Build your ICP + Persona Creation v1

• My Outbound Chef Kit: 130+ resources (20+ email templates, cold call scripts, AI prompts, top tools, and more). Value: $1,000+

And the best part? You can try it free for 7 days. Cancel anytime.

But I think you’ll love it!

👉 Start your free trial today.

This is my last newsletter of the year.

We shipped a lot of content in 2025, so I pulled the resources you engaged with most, the ones you shared, replied to, and told me were useful.

If you missed any of these, use the holiday break to catch up. Take notes. Prep for 2026.

Happy reading!

Your 2025 Outbound Reading List (Top 10 + What’s Coming)

Top 10 newsletters

#10 - How Gorgias scaled to 80m+ ARR without cold calls

No SDRs until $60M+ ARR. They scaled with automated cold email, ads, and customer referrals. Proof that you can build serious revenue without a traditional SDR team.

Read it here:

#9 - How Pigment Scaled to $100M ARR with Outbound

What stood out: they hired engineers and built custom outbound tools. In a market full of legacy competitors, they invested in the stack to be different. This is enterprise prospecting done right.

Read it here:

#8 - How HockeyStack went from 0 to $74m in pipeline in just 8 months

The most recent “launch outbound from scratch” breakdown I’ve written. If you’re building outbound in 2025/2026, this is your playbook, it shows exactly how fast you can move with the right approach.

Read it here:

#7 - How Owner.com Scaled Outbound to $40M+ ARR

Everyone on LinkedIn says you can’t run outbound below 50K ACV. Owner.com proves them wrong. This shows how they built a productive SDR team with deals under 10K ACV and still got ROI.

Read it here:

#6 - 6 AI prompts To Help You Launch Outbound in 2025 (10x Faster)

For early-stage teams. These prompts help you define your ICP, identify segments to target, and figure out what to say - all before you’ve sent a single email.

Read it here:

#5 - Fix that before you scale outbound

My favorite topic this year. Most companies try to scale outbound before fixing what’s broken. This is about investing in systems, data, and AI before adding headcount. It’s where I spend most of my time with clients.

Read it here:

#4 - How to build outbound from scratch in 2025 (Full Guide)

The complete playbook: ICP definition, personas, messaging, tool selection by stage, hiring, and when to scale. If you’re launching outbound, start here.

Read it here:

#3 - How Snowflake Scaled Outbound to $4B ARR

My favorite breakdown. Snowflake runs ABM and enterprise prospecting as one team: SDRs, Sales, and Marketing operating together, not in silos. No other company I’ve studied has this level of alignment.

Read it here:

#2 - 6 AI Prompts for Researching Accounts & Cold Outreaching (10x Faster)

For teams where outbound is already working. These prompts help you research accounts faster and write better messages. Works with Claude, GPT, or Clay.

Read it here:

#1 - How Ramp Scaled to $1B ARR With Outbound

Ramp operates differently. Speed is embedded in everything, company culture, GTM, outbound execution. They were early on AI, they experiment constantly, and they move faster than anyone else I’ve studied.

Read it here:

Top 3 podcast episodes

We didn’t ship many episodes this year (more on that below), but these three got the most listens:

#3 - How build a strong outbound culture with Prospecting Days (Guide). With Ralph Barsi, VP of Sales at Kahua

Ralph has systems for everything. This episode breaks down how to run prospecting days that actually build outbound culture - not just activity spikes. I also wrote a companion guide if you want the full framework.

Listen here:

P.S. I’ve written: this guide on how to run one prospecting if you want to go deeper. Read it here.

#2 - 0 → 2,300 Meetings: Building an Outbound Sales Machine with Matt Roberts (Head of Sales Development at Mosaic (acquired by HiBob)

Matt built outbound from zero at Mosaic, scaled to 10 BDRs, and booked 2,300 meetings before the HiBob acquisition. This is the full story of how long it actually takes to build an outbound engine.

Listen here:

#1 - I tested GPT-5 and Opus 4.1 for account research

This was an experiment, not an interview. I tested the latest AI models for outbound research and recorded the results. The download numbers surprised me - turns out you want to see which models actually work for outbound. I’ll do more of these in 2026.

Listen here:

What's coming in 2026

The show is back. Three formats:

• Live fixing outbound – I workshop and fix broken outbound systems

• Live building from scratch – I build outbound workflows in real-time

• Live show & tell – Outbound operators present their workflows

Less conversation, more showing. First episodes drop soon on LinkedIn.

My focus for 2026: productivity. How to invest in systems, automation, AI, and data to reduce manual work and increase output per rep.

Productivity is the focus, but the bigger goal: building the complete resource for outbound leaders.

Coming in January based on your questions:

• TAM vs SAM vs ICP (updated version)

• Dashboards and reporting for exec/board meetings

• How I use Clay as my outbound orchestration laye

If there’s something specific you want me to cover, reply to this email. I’m listening.

See you next year!

Elric

Chef, Outbound Kitchen

Thinking about upgrading to the paid newsletter? Here’s what you’ll get:

• Instant access to 40+ paid newsletters, including:

  • 6 AI Prompts for Researching Accounts & Cold Outreaching Them (10x Faster)

  • The Guide to Building an Enterprise Prospecting System

  • [Starter Kit] Step 1: Build your ICP v1 + Persona Creation v1

• My Outbound Chef Kit: 130+ resources: 20+ email templates, cold call scripts, AI prompts, top outbound tools, and more, everything the best outbound teams use. Worth $1,000+

And the best part? You can try it free for 7 days. Cancel anytime.

But I think you’ll love it!

👉 Start your free trial today.

As soon as you’re ready, here’s how I can help:

1. Outbound Consulting Call: Need quick help? Book a 40-min session here.

2. Outbound Private Chef:

   1. Part-time, I’ll build, optimize efficiency, and execute your outbound strategy.

   2. Coaching/Advising: get tailored advice to fix your strategy, boost efficiency, and drive results.

3. Interested? Reply to this email or hit me up at bonjour@elriclegloire.com

• Instant access to 40+ paid newsletters, including:

  • 6 AI prompts to find and reach accounts 10x faster

  • The Guide to Building an Enterprise Prospecting System

  • [Starter Kit] Step 1: Build your ICP + Persona Creation v1

• My Outbound Chef Kit: 130+ resources (20+ email templates, cold call scripts, AI prompts, top tools, and more). Value: $1,000+

And the best part? You can try it free for 7 days. Cancel anytime.

But I think you’ll love it!

👉 Start your free trial today.

Two weeks left in 2025.

I spent a few hours this week reflecting on 2025, studying the top outbound teams, working with customers across early-stage to $50M ARR, and talking to GTM leaders and B2B founders about what’s actually working.

If you own outbound at your company, whether you’re a CRO, VP Sales, GTM leader, or SDR Manager, this is for you.

Everyone on LinkedIn is saying the same thing:

“SDR teams are getting cut. Outbound is dead. AI is replacing reps.”

I started tracking the data. Here’s what actually happened:

→ March 2025: 170,000 SDRs globally

→ December 2025: 190,000 SDRs globally

+20,000 SDRs in 9 months.

Outbound isn’t dead. Companies still need reps. But the playbook changed, and most teams didn’t adapt.

Here’s what I learned.

8 Things I Learned About Outbound in 2025

1. Outbound isn’t dead. It’s just harder, and most companies are still running the 2022 playbook.

I heard “outbound is dead” more times this year than I can count.

It’s not dead. But it is getting significantly harder—and the data proves it.

The numbers tell the story:

According to Jacco van der Kooij (CEO of Winning by Design), conversion rates have been plummeting:

• 2015: 100 cold emails = 1 opportunity (1% conversion rate)

• 2018: 200 outbound attempts = 1 opportunity (0.5% conversion rate)

• 2023: 1,000+ attempts = 1 opportunity (0.1% conversion rate)

At the same time, SDR salaries nearly doubled, from $44K in 2015 to $85K by 2025.

Lower conversions + higher costs = drastically lower ROI.

Why is this happening?

Channel saturation. The same thing that happened with ads is happening with outbound.

You don’t read every ad on your phone anymore, you’ve learned to tune them out. Prospects are doing the same with outbound.

They’re getting more messages than ever. Some written by AI. Some written by reps. Most are bad. And AI has accelerated this problem, making it easier to send more volume, which creates more noise.

But here’s what most companies miss:

The companies saying “outbound is dead” are the same ones making the same mistakes:

• Wrong execution

• Wrong expectations

• Hiring junior SDRs and hoping they figure it out

Junior reps used to be able to handle outbound at early-stage companies. Not anymore.

Outbound in 2025 requires experience. If you hire junior reps, you need a founder or head of sales deeply involved, training them, showing them what works, iterating with them.

You can’t hand someone a sequence and wait for results. The bar is too high now.

The takeaway:

Outbound is harder. That’s a fact. But it’s not dead.

The teams that are winning have adapted. They’ve invested in systems, hired the right people, and built processes that cut through the noise.

The teams that are losing are still running 2022 playbooks, high volume, low quality, hope-based prospecting.

If you don’t have the right people and the right systems, you’re not going to get results.

2. The top outbound teams do 100 things well, not one thing great.

I studied the best outbound programs this year. Snowflake. Ramp. ClickUp. Owner.com.

They don’t have a silver bullet. They invest heavily across the board:

• Data infrastructure

• AI and automation

• Training and enablement

• Hiring the right people

Think of it like a Michelin-star kitchen. Each person is specialized. Each part of the system is optimized. They don’t succeed because of one dish, they succeed because everything works together.

That’s what top outbound teams look like in 2025.

Most companies are still looking for the one tactic that will fix everything. It doesn’t exist.

3. AI is the productivity unlock, but only if you build systems, not just buy tools.

Snowflake 15x’d their reply rate using AI to write outbound messages.

One of my clients showed me what their team was writing versus what AI could produce. The AI output was better, faster, more relevant, better structure.

But here’s what most companies miss: AI doesn’t replace your team. It multiplies their output.

The best teams I worked with this year use AI for:

• Data enrichment and cleaning

• Automated research

• Message writing

• Spotting patterns (deal risk scoring, pipeline alerts)

• Enablement and scorecards

Meanwhile, most companies bought ChatGPT seats and told their teams to use it manually.

That’s not a productivity unlock. That’s just adding another tool to the stack.

Here’s the real unlock: Build AI workflows that run in the background and push outputs directly into your CRM or sales engagement platform, where your team actually works.

But it’s not plug-and-play. AI needs training. Snowflake iterated 140+ times to get their prompts right. One of my clients took 30-40 iterations just to dial in messaging.

The business implication: Companies that invest in AI systems (not just seats) are generating the more pipeline with the same headcount. Companies that don’t are stuck scaling linearly, more reps, more cost, same results.

If you’re not willing to invest time in building and training your AI workflows, you won’t see results.

4. Productivity is the new competitive advantage, and most teams are leaving 2x on the table.

Owner.com has BDRs booking 40 meetings a month for their SMB motion.

Most teams are stuck at 10 meetings a month.

What’s the difference?

They optimized for productivity. They built systems that let their team spend maximum time on high-quality prospecting, not preparing to prospect.

Here’s the biggest mistake killing outbound ROI in 2025:

Your team is still doing work that should be automated.

If your reps are spending time on:

• Manual research

• Finding and cleaning data

• Writing individual emails from scratch

• Toggling between 5 different tools

You’re burning budget on low-value work.

Top teams automate in the backend, data, research, AI, and push the output directly into the tools where reps work.

The question to ask when evaluating your stack: Is this removing friction for my team, or adding it?

Most companies are still buying tools FOR their team to use. They should be buying tools that run IN THE BACKEND and make their team more productive without them touching it.

Here’s what this means for your business:

The old playbook: Hire 10 reps. Scale headcount. Generate pipeline.

The new playbook: Hire 5 reps who produce the output of 10.

The ROI:

• Lower headcount cost (cheaper)

• Higher rep productivity (more pipeline/revenue per rep)

• Better rep retention (higher commissions, less burnout)

But it requires investment in systems, AI workflows, automation, data infrastructure that runs behind the scenes.

The litmus test: Can I 2x my team’s output with better systems? If not, you’re underinvesting in infrastructure.

Most GTM leaders are still focused on hiring and coaching. Not enough are focused on building the systems that make their teams 2x more productive.

Which brings me to the next learning.

5. Most GTM leaders are investing in the wrong layer of their outbound motion.

This is my most contrarian take.

I stopped listening to most outbound & SDR leadership content this year. Here’s why:

Everyone is focused on coaching. Enablement. How to ramp reps faster. How to run better 1-on-1s.

I’m not saying enablement and coaching aren't important.

They are.

But if you don’t have the right systems, coaching won’t save you.

There are 3 pillars to outbound success:

1. Talent – Do you have the right people?

2. Systems – Do you have the right tech stack, AI workflows, and data infrastructure to maximize productivity?

3. Enablement – Are you training and coaching your team so they can be successful and actually enjoy the role?

Most GTM leaders invest heavily in #1 and #3. They don’t invest enough in #2.

They buy 2-3 tools, run a training on those tools, and think they’re done.

They’re not building systems. They’re adding tools and hoping their team figures it out.

Here’s the reality:

Outbound is getting harder. Channel saturation is increasing. If you don’t have systems that maximize productivity, your coaching won’t matter.

You can train your team on messaging all day long. But if they’re spending 6 hours a week on manual research and data cleanup, you’re not going to 2x results.

The best GTM leaders in 2025 invest in systems first, then coach on top of that foundation.

6. You need to validate outbound before you scale outbound, and most early-stage companies skip this step.

Product-market fit is the first milestone for early-stage companies.

But there’s a second milestone most companies skip: validating your outbound motion.

Here’s the mistake I saw over and over this year:

Companies hit product-market fit, then immediately try to scale outbound. They hire a team of SDRs, buy a stack of tools, and hope it works.

It doesn’t.

You can’t scale what you haven’t validated.

If you’re an early-stage company just getting started with outbound, your goal isn’t to scale. It’s to validate:

• Is your ICP right?

• Does your messaging resonate?

• Are your channels working?

• Can you get repeatable results?

Once you have that, once you’ve proven the motion works, then you can scale.

Skipping this step is why so many early-stage outbound motions fail. They go straight from zero to hiring 5 SDRs without ever proving the system works.

Don’t make that mistake.

7. In competitive markets, outbound creates timing, and most companies are leaving market share on the table.

Here’s a learning I didn’t expect:

I worked with a company this year selling into a traditional, competitive market. Their competitors weren’t doing outbound. They were creating content, going to conferences, waiting for inbound.

My client went proactive. They built an outbound motion and started reaching out to the right companies before their competitors even knew those companies were in-market.

The result: They’re gaining market share while their competitors wait around.

Here’s the insight:

Outbound doesn’t just generate demand. It manufactures timing.

If you’re in a competitive market and your competitors aren’t investing in outbound, that’s a massive opportunity.

Most companies think outbound is only for high-growth SaaS companies. That’s not true.

If you’re in a market where competitors are reactive, outbound is how you win.

8. Most companies that say “outbound is dead” are just bad at it, and they don’t even know what outbound actually is.

When I hear “outbound doesn’t work for us,” 99% of the time it’s bad execution.

Here’s what happened:

They hired 2 junior SDRs. Gave them a list. Told them to send 10,000 emails. Got no results. Declared outbound dead.

But the deeper problem isn’t just bad execution, it’s that they don’t know what outbound actually is.

Most companies think outbound = cold emails sent by SDRs.

That’s not outbound. That’s cold outreach.

Real outbound is a full-funnel, cross-functional motion:

• SDRs prospect and book meetings

• AEs close outbound deals, which requires different discovery, different process, different training than closing demo requests (AKA order takers)

• CSMs and Account Managers proactively reach out for upsell and cross-sell opportunities, they don’t wait for customers to contact them

If you only invest in “SDRs sending cold emails,” you’re not doing outbound. You’re doing bad cold outreach.

And then you wonder why it doesn’t work.

Outbound is a system. It’s not a tactic. It’s not a top-of-funnel SDR function you can hire two people to figure out.

It’s a shift in how your entire GTM team operates.

What This Means for Your GTM Strategy in 2026

If you’re running outbound right now, here’s what you need to prioritize depending on where you are:

Early-stage companies:

• Validate your outbound motion before you try to scale it. Prove your ICP, messaging, and channels work first.

• Focus on the right 1,000 companies, not 40,000. Use AI to identify companies currently struggling with the problem you solve.

• If you hire junior reps, make sure a founder or head of sales is deeply involved in training and iteration.

• Track your champions moving to new companies. That’s your lowest-hanging fruit.

Companies with existing teams:

• Strategic priority #1: Invest in systems that maximize team productivity. Automate research, data, and message writing in the backend.

• Stop adding tools for your team to use. Add tools that run behind the scenes and push outputs into their workflow.

• Ask yourself: Can I 2x the output of my current team with better systems? If not, you’re underinvesting in infrastructure.

• Measure what matters: Track qualified pipeline and revenue generated by outbound, not just activity metrics.

B2B companies in competitive markets:

• If your competitors aren’t doing outbound, you’re leaving market share on the table. Build a proactive motion and reach the right companies before they do.

• Outbound isn’t just for high-growth SaaS, it’s for any market where you can manufacture timing and win deals before competitors know they’re available.

Outbound isn’t dead. But the playbook from 2022 is.

If you’re still running the old motion, manual research, junior reps, hope-based prospecting, tools stacked on top of tools, you’re going to keep struggling.

The teams winning in 2025 built systems. The teams that will win in 2026 will too.

What did you learn about outbound this year? Hit reply and let me know.

Leave a comment

Let’s get cooking!

See you in the next newsletter.

Elric

Chef, Outbound Kitchen

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A lot of outbound content is just cold outreach content.

Cold calling scripts. Email templates. LinkedIn tactics.

That’s fine, but it stays on the surface. The resources here go deeper, how to train SDRs, how to sell outbound deals, how to build systems that actually work.

Here’s what I use:

My go-to outbound resources

The outbound team I study

Snowflake, Ramp, Rippling, Owner, Pigment, Gorgias, ClickUp, Hockeystack

This is where I learn the most right now.

I study what’s working, what’s not, and what you should be doing. Studying top teams going after different personas helps you see what’s transferable and what’s not. That’s what I share in my deep dives.

Books

Gap Selling (Keenan)

Most outbound resources stop at “get the meeting.” Gap Selling goes beyond that. It teaches you how to sell outbound deals — not just book them. Outbound meetings shouldn’t be treated like demo requests. This book shows you the difference.

Outbounding (Skip Miller)

Similar thinking to Gap Selling. This one covers the buyer journey and explains why outbound deals shouldn’t be treated like demo requests. Different buyer, different process. It covers the fundamentals of what outbound should actually be.

I wrote a summary with my takeaways here:

Busting Silos (Travis Henry + Hillary Carpio)

Written by the Snowflake team. They share how they aligned their full go-to-market team — marketing, sales, and SDRs — to go after target accounts together. If you want to understand how Snowflake built their outbound machine, start here.

The SaaS Sales Method for SDRs (Jacco van der Kooij & Dan Smith)

This one focuses on different ways to break into an account. It includes maps showing how to do it. One of the only books I’ve found that goes deep on multi-threading and account entry strategies.

Podcasts & Content I Check Regularly

Revenue Leadership (Kyle Norton)

Kyle is the CRO behind Owner.com. I love this podcast because he shares behind-the-scenes from his own team. He also interviews leaders from other top outbound teams.

20Sales (Harry Stebbings)

This is where I hear directly from the people behind the top teams I study. If I want to understand how Ramp or Rippling thinks about outbound, I start here.

Stage 2 Capital & Mark Roberge

Great content hub for structuring your sales team. Data-driven frameworks for how to build and scale.

Outbound Squad (Jason Bay)

Practical and focused on cold outreach. But Jason also covers the frameworks that make outbound work today.

Winning by Design

The books and the blog. They talk a lot about frameworks, and I love how they use visuals to explain complex systems. Makes it easier to implement.

Lavender Blog

My go-to for email copywriting. They write a lot about how to keep subject lines simple and what actually works in cold emails. Focused specifically on email — and they do it well.

Newsletters Worth Reading

Prospecting from the Trenches (Florin Tatulea)

My go-to newsletter for tactical outreach. I’ve been reading it for years. Still a happy reader.

Cannonball GTM (Jordan Crawford & Doug Bell)

A newer one I started reading recently. I read every issue now. They show practical examples of what’s possible in 2025 — how to build GTM strategies and how to use AI. Very current.

People I Follow for Clay/AI Workflows

Eric Nowoslawski

Focused on cold outreach and email specifically. If you want to see what’s possible with Clay for prospecting, follow Eric.

Elijah Awoke

More focused on systems for SDR teams, calling workflows, process automation. Different angle than Eric, equally useful.

Communities Where I Learn

Pavilion

Good conversations, especially about AI right now.

SDR Leaders of USA & EMEA

Focused on leadership for outbound teams. Less tactics, more team-building and strategy.

Clay Cafe

If you’re using Clay, this is where people share workflows and ideas. Similar content to what Eric and Elijah post, but from a broader community.

What would you add to this list? Drop your favorite outbound resource, I’m always looking for ones that go deeper than tactics.

P.S. Relaunching my podcast in 2026. If you know any good freelance podcast producers, I’m hiring.

Subscribe now

Last week, I broke down the 3 mistakes that destroy outbound growth:

1. The Top-Down Trap: Hiring before you prove capacity math works

2. The Territory Trap: Ignoring TAM when planning SDR headcount

3. The Timeline Trap: Forgetting ramp, tenure, and turnover realities

Today: how to do it right.

I’ll walk you through the exact framework to plan 2026 headcount without lighting money on fire. We’ll run two scenarios side-by-side so you can see the difference between the 2022 playbook (hire your way out) and the modern outbound playbook (optimize first, then scale).

For paid members, you’ll get my new V3 Outbound Headcount Planning Spreadsheet at the end of this newsletter.

P.S. If you missed last week’s newsletter, you can read it here.

Outbound Headcount Planning 2026: How to Do It Right

The Three Constraints That Govern Outbound Headcount Planning

1. Capacity Constraint

• Outbound capacity: How many SQOs/S2 can your SDRs produce?

• Sales capacity: How many SQOs/S2 can your AEs actually work?

• These must stay aligned. More SDRs without AE capacity = wasted pipeline. More AEs without pipeline = expensive bench warmers.

2. Market Constraint

• Your TAM is finite. Each new SDR or AEs shrinks the territory per rep.

• Contact frequency matters: accounts should only be touched every 3 months. That means each SDR needs 3x their monthly account volume in their territory.

• Some markets hit limits faster than others.

3. Timeline Constraint

• SDR ramp: 3 months average (Bridge Group, 2025)

• AE ramp: 5.7 months average (Bridge Group, 2024)

• Sales cycle: Add this on top of ramp before you see revenue

• SDR tenure: 23 months average, with 49% annual turnover (Bridge Group, 2025)

• AE tenure: 33 months average, with 30% annual turnover (Bridge Group, 2024)

Solution 1: Bottom-Up Capacity Planning

Counters Mistake #1: The Top-Down Trap

The Principle

Stop starting with revenue targets. Start with what your team can actually produce.

Top-down planning says: “We need $3M ARR, so let’s hire enough people to hit it.”

Bottom-up planning says: “What can our current team produce? What’s the gap? What’s the cheapest, fastest way to close it?”

The Dual-Capacity Framework

You need to track two numbers:

• Outbound Capacity = SDRs × SQOs per SDR per month

• Sales Capacity = AEs × SQOs each AE can work per month

For this article, we’ll simplify: Sales Capacity = Quota. In reality, capacity and quota aren’t always equal, but we’re keeping this focused on outbound math.

The Calculation

Let’s say your goal is $1.5M net new ARR from outbound (with another $1.5M coming from inbound, handled directly by AEs).

Here’s the math:

• $1.5M ARR ÷ $11,400 ACV = ~132 deals needed

• 132 deals ÷ 12 months = ~11 deals/month

• At 10% win rate = 110 SQOs/month needed

Now compare to your current output:

• 5 SDRs × 10 SQOs = 50 SQOs/month

• Gap: Need 110, producing 50

Here’s where most teams make the mistake. They see a 60 SQO gap and immediately think: “We need more SDRs.”

But there’s a better question: Can we increase productivity before we increase headcount?

Productivity Before Headcount

• Hiring 6 more SDRs at 10 SQOs each = 60 more SQOs

• Cost: ~$558K/year in new salaries alone

• Plus 3 months until they’re productive

• Plus 49% of them will turn over within 2 years

Or:

• Increase current SDRs from 10 → 20 SQOs each = 50 more SQOs

• Cost: Outbound Ops (AKA GTM engineer) + new tools = $50k-$150K/year

• Faster impact (no ramp time)

• No turnover risk on new hires

Same output. 4x cost difference.

This is why the first question in any headcount conversation should be:

“Have we maxed out our current team’s productivity?”

Solution 2: TAM-Based Territory Validation

Counters Mistake #2: The Territory Trap

The Principle

Your market is not infinite. Before you decide how many SDRs to hire, you need to know how many accounts exist for them to work.

This is why Salesforce can have 1,500 BDRs while other companies cap out at 50.

It’s not about company size, it’s about total addressable market.

The Contact Frequency Math

Accounts should only be contacted every 3 months.

Touch them more often, and you’re spamming. Your reply rates tank. Your domain reputation suffers. Prospects block you.

This means:

• If an SDR works 200 accounts/month

• And accounts should only be contacted every 3 months

• Then each SDR needs 600 accounts minimum in their territory

• With 5 SDRs, you need 3,000+ qualified accounts

Before hiring your 6th SDR, ask: “Do we have 3,600 qualified accounts?”

The Chili Piper Example

At Chili Piper, we sold to companies with sales teams of 10+ reps. Sounds like a big market, right?

Here’s the reality when you run the numbers on Sales Navigator:

That’s 11,000 accounts globally. And that’s before filtering for CRM usage (Salesforce/HubSpot only), which shrinks the list further.

At 600 accounts per SDR (3-month contact cadence), that’s a maximum of ~18 SDRs worldwide before you’ve exhausted the market.

This is why you must map and score your market before you plan headcount.

The TAM Validation Checklist

Before adding SDRs, confirm:

1. Total ICP accounts identified: How many companies fit your criteria?

2. Accounts with verified data: How many have accurate contact info?

3. Accounts already worked: Subtract customers and active pipeline

4. Net addressable accounts: What’s left for outbound?

5. Accounts per SDR at 3-month cadence: Net addressable ÷ (SDR count × 3)

If accounts per SDR drops below 500, you’re over-hiring.

Market + Product Constraints

TAM isn’t just about geography. It’s about your product.

Companies like Salesforce can keep growing because they:

• Sell multiple products to different teams

• Serve SMB to Enterprise

• Operate worldwide

Their market is essentially every company on earth.

But if you sell HR compliance software specific to California regulations? Your market is a fraction of that. A US-only company targeting enterprise accounts? Smaller still.

Know your constraints before you hire.

Solution 3: Time-Aware Hiring Plan

Counters Mistake #3: The Timeline Trap

The Reality of Ramp, Tenure, and Turnover

The Bridge Group 2025 + RepVue data::

SDRs:

• Ramp time: 3 months

• Average tenure: 23 months

• Annual turnover: 49% (12% involuntary, 16% voluntary, 21% promotions)

• Total cost: ~$93K/year (OTE + tools)

AEs:

• Ramp time: 5.7 months

• Average tenure: 33 months

• Annual turnover: 30% (19% involuntary, 11% voluntary)

• Total cost: ~$178K/year (OTE + tools)

Let’s do the math on what this actually means:

An SDR hired in January 2026:

• Starts producing: April 2026 (after 3-month ramp)

• First deal closes: August 2026 (after 4-month sales cycle)

• Full revenue impact: 7 months after hire

And statistically:

• 1 in 4 will leave within 12 months (voluntary)

• 1 in 8 will be let go (involuntary)

• 1 in 5 will be promoted out of the role

You’re not just hiring an SDR. You’re buying a lottery ticket that takes 7 months to scratch off, and half the tickets expire within 2 years.

The Phased Hiring Approach

Instead of hiring all at once, gate your hiring decisions:

Phase 1: Optimize (Months 1-6)

• No new SDR hires

• Focus entirely on increasing productivity

• Invest in GTM Engineer, better tools, improved processes

• Target: 10 → 20 SQOs per SDR

Phase 2: Validate (Month 6)

• Did productivity increase?

• Is the improvement consistent (±15% month-over-month)?

• If YES: Consider hiring

• If NO: Keep optimizing

Phase 3: Controlled Scaling (Months 7-12)

• Add SDRs only if productivity gains are proven

• Hire in small batches (2 at a time)

• Watch TAM per rep closely

• Re-evaluate every quarter

Phase 4: Continuous Monitoring (Ongoing)

• Track actual vs. expected ramp

• Monitor turnover rates

• Adjust hiring plan quarterly based on real data

Putting It All Together: The 18-Month Comparison

Let’s run two scenarios for a company planning 2026:

Starting Point:

• B2B SaaS, $11,400 ACV, multi-geo

• Current team: 5 SDRs, 5 AEs

• Current SDR output: 10 SQOs per SDR per month

• AE quota: $600K/year each ($3M total capacity)

• Total AE Capacity: 220 SQOs/month (5 × 44)

• AE Capacity for Outbound: 110 SQOs/month (50/50 split with inbound)

• Goal: $1.5M net new ARR from outbound

• Required: 110 SQOs/month (at 10% win rate)

• Current output: 50 SQOs/month

• Gap: 60 SQOs/month

Scenario A: Optimize First (2025/2026 Playbook)

Strategy: Increase SDR productivity from 10 → 20 SQOs before any hiring.

Investment:

• Fractional Outbound Ops (AKA GTM Engineer): $60K/year

• New tools (Data, signals, AI, enrichment): $30K/year

• Total: $90K/year

Month-by-Month Plan:

First number = ramped SDRs, second = new hire ramping

⚠️ The Capacity Constraint Revealed: Notice months 13-18 show negative capacity gaps. This isn’t a bug. The model is telling you: “Outbound is producing more SQOs than your AEs can handle.”

At this point, you have three options:

1. Hire more AEs to handle increased pipeline

2. Slow SDR hiring to match AE capacity

3. Shift AE focus from inbound to outbound

4. Accept waste — some SQOs won’t get worked

18-Month Totals (Scenario A):

• Total SQOs Generated: 1,855

• Total ARR Closed: $1,533,300

• Final Team: 7 SDRs (net +2)

• Total Outbound Investment: $925,500

• Final Monthly SQO Output: 130

• Accounts per SDR (6,000 TAM): 857 ✓ (healthy)

• Cost per SQO: $499

Scenario B: Hire First (2022 Playbook)

Strategy: Hire more SDRs at current 10 SQOs output to close the gap.

Math: Need 110 SQOs. At 10/SDR, need 11 SDRs. Hire 6 more.

Investment:

• 6 new SDRs: $558K/year

• Additional tool seats: $48K/year (6 × $8K)

Hiring Timeline:

• Month 1: Hire 2 SDRs

• Month 3: Hire 2 SDRs

• Month 5: Hire 2 SDRs

Month-by-Month Plan:

Note: At 49% annual turnover, a team of 11 SDRs loses ~5 people per year. This model shows turnover eating into productivity gains.

The Turnover Tax: Scenario B spends months 9-18 in a constant backfill cycle. Every time someone leaves, you’re back to ramping.

18-Month Totals (Scenario B):

• Total SQOs Generated: 1,725

• Total ARR Closed: $1,476,300

• Final Team: 10 SDRs (but constant churn)

• Total SDR Hires Made: 7 (6 original + 1 backfill shown, more likely in reality)

• Total Outbound Investment: $1,480,281

• Final Monthly SQO Output: 100 (and unstable)

• Accounts per SDR (6,000 TAM): 600 ⚠️ (getting tight)

• Cost per SQO: $858

The Side-by-Side Comparison

Scenario A generates $57K more ARR, at 37% less cost, with a smaller team, and better TAM health. Cost per SQO is 42% lower.

The Bottom Line

The companies that win in 2026 won’t be the ones who hire the most SDRs.

They’ll be the ones who:

1. Optimize before they scale: Doubling productivity is cheaper and faster than doubling headcount

2. Respect their TAM: Every hire shrinks territory per rep

3. Plan for reality: Ramp time and turnover aren’t edge cases, they’re the default

Start with what you have. Make it work better. Then scale.

Elric

Head Chef, Outbound Kitchen

🔒 Paid Subscriber Bonus: The V3 Outbound Headcount Planning Spreadsheet

I’ve been refining this model, and V3 is ready.

What’s new in V3:

Fully Dynamic Model: Every input cascades through the entire 18-month projection. Change your ACV, sales cycle, team size, or targets, and watch both scenarios recalculate instantly. No more hardcoded cells.

AE Capacity Split: The model now accounts for inbound vs. outbound revenue split. Enter both targets, and it automatically calculates how much AE capacity is actually available for outbound. This is the constraint most planning models miss.

Capacity Constraint Alerts: Negative capacity gaps (when outbound SQOs exceed what AEs can handle) now highlight in red automatically. The model tells you when you’re about to create pipeline your team can’t work.

Instructions Tab: Step-by-step guide for customizing the model to your business. Explains what each input means, how the capacity gap works, and what to do when you see negative gaps.

What’s inside:

• Inputs Tab — 25+ customizable inputs (blue = editable, black = calculated)

• Scenario A — 18-month “Optimize First” projection with productivity ramp

• Scenario B — 18-month “Hire First” projection with turnover modeling

• Dashboard — Side-by-side comparison that auto-updates

• Financials — Detailed cost breakdown and ROI analysis

Download it here:

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