Zero to $74M: Our Outbound Playbook

Context

Eight months ago, I left Carta and joined HockeyStack. We didn’t have a single outbound call or email in flight. No calls, no sequences, no process. Every dollar of pipeline came from inbound. That worked— until it didn’t scale.

We had to grow faster. So we built an outbound engine from zero. Today, that engine will drive $74M in annualized pipeline.

This isn’t theory. This is the exact system we use— built by operators, not consultants. We ripped it apart and rebuilt it to scale like software. Here's how we did it.

P.S: Want a Demo of HockeyStack.com to see how we automate this entire process? Click here.

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1. Inbound Was a Crutch

HockeyStack has been relying too much on Inbound. Our founders built a great audience on LinkedIn (probably how you found this guide) but it wasn’t scaling aggressively.

As our revenue targets doubled, inbound volume became unpredictable. It wasn’t scalable. It wasn’t controllable.

Outbound gave us control. But we didn’t want to do it the way everyone else does.

We wanted the most engineered, automated, and lethal outbound system in SaaS.

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2. Phase 1 — System Before Headcount

We didn’t hire a team. We wrote the system. And I accepted to be on the phones for a quarter as the Head of Sales Development to build the optimal system from scratch — not repeat what worked at Carta.

Fortunately, it took less than a quarter to figure it out and build the machine.

Here is what I did:

Define the ICP Like a Quant

We didn’t start with TAM. We started with actual closed/won data. We profiled:

• Company size, funding stage, industry
• Role of champion vs. signer
• Time-to-close
• Deal size

That narrowed us down to:

• B2B SaaS
• Series B or later
• $50K+ ACV
• Titles: Demand Gen, Rev/Marketing Ops, Performance Marketing, Digital Marketing, etc.

Every persona had:

• Known pain points
• Budget authority
• Short sales cycles

If it didn’t fit the model, we didn’t waste a byte of compute.

Codify the System

Before hitting the marketplace, we built every asset:

• Cold call script with messaging so sticky it resonates with all 10 of our ICP titles including live objection branching
• 6 email sequences (10–14 days, tailored by persona and buying stage)
• Trigger matrix to route accounts based on behavior

Everything was manual at first.

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3. Phase 2 — Automate Prospecting to Zero Manual Work

Then in our second quarter, I built a team of 5. All started manually prospecting. We were booking meetings, but it wasn’t enough.

We wanted SDRs focused on revenue generating activities, not data entry. So we built a prospecting pipeline with no humans in the loop.

Outbound Workflow Diagram

Every step is automated. No humans in the loop until a meeting is booked.

Step 1: Account Selection — Predictive, Not Reactive

Tool: HockeyStack Account Intelligence

We built a model that scored every account daily based on:

• ICP match
• Website behavior (specific URL patterns, pricing views)
• Hiring signals (headcount changes, open roles)
• Tech stack (tracked changes over time)
• Engagement with content (clicks, opens, intent from campaigns)

Only the top 2% of accounts entered the outbound queue.

Step 2: Contact Enrichment — Fully Automated

Once an account hit threshold score, the system:

• Pulled up to 3 buying committee contacts
• Validated emails and phone numbers
• Retrieved recent LinkedIn activity
• Tagged relevant content topics based on engagement history

No researcher. No manual lookup. Just clean, ranked targets.

Step 3: Sequence Assignment — Behavior-Led, Not Persona-Led

The system didn't just use job title—it used intent.

Example:

• Viewed pricing = "Conversion" sequence
• Read research = "Insight-led" sequence
• Engaged on LI but no site visit = "Brand familiarity" sequence

Each sequence was tuned to buying stage, not just persona.

Step 4: Real-Time Triggers

Events that auto-triggered outbound:

• Multiple page views within 2 days
• High-intent content interaction
• Added new tool to stack (tracked via Siftery)
• Hiring a Head of Demand Gen

These weren't just tracked—they triggered sequences in real time.

Step 5: Cold Outbound

Yes, signal-led outbound has higher conversion rates, but it’s not enough to build a massive pipeline.

There are lots of companies out there that do not have any type of signals but are still interested.

Some of them need that extra push, some of them don’t know your solution exists, and for some of them it’s lack of brand awareness.

We power our Cold Outbound Layer with HockeyStack as well.

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4. Our Tech Stack (Tuned for Speed and Control)

Everything is orchestrated. No tools operate in isolation. Every workflow is bidirectional.

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5. Performance Benchmarks (Month 6)

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6. Operator Takeaways

• Cold outbound is a leverage game: If it doesn’t scale with software, you’re doing it wrong.
• Speed beats personalization: The first rep to call after an intent signal wins.
• Calls convert: Our top 5 outbound deals in the last quarter all started with a call, not an email.
• Not every company should do emails: for our marketing ICP cold calling works much better.
• Don’t waste cycles on bad fits: Cut 98% of the market. Go deep on the 2% who will buy.
• Obsession with control is a feature: Every workflow is owned end-to-end by our growth team.

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7. Rules of the Engine

These are non-negotiable. They don’t flex. They win.

• No one researches manually. If a human is touching lead data, the system is broken.
• If a live demo view happens, the account is contacted in under 2 minutes.
• We do not personalize. We segment and convert.
• SDRs don’t write sequences. They execute.
• Every cold call is recorded, reviewed, and logged. Weekly.
• If a tool slows us down by more than 2 minutes, it’s replaced.
• Sequence logic is version-controlled. Playbooks are deployed like software.

This is how you run outbound like a machine. Because if you’re not engineering your sales motion, you’re just guessing and your competitors will beat you to closing the deal.

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8. What's Next

We’re not done. The next evolution:

• Marketing campaigns that drive signals.
• Fully autonomous AE-led outbound campaigns based on live deal data
• Website intent → outbound → meeting booked within 15 minutes

We’re building the most aggressive and engineered outbound engine in SaaS. If that makes you uncomfortable, good.