Real pipeline results from real engagements. $100M+ generated across 10+ companies. See how to go from zero to $2.4M in 90 days, scale 3x in 6 months, and build fully automated GTM systems with zero SDR headcount.
Pipeline Generated
Companies Served
Month Engagements
These case studies represent actual engagements with real companies, generating real pipeline and real revenue. Company names and specific identifying details are anonymized to protect client confidentiality, but every metric—pipeline value, timeframe, conversion rate, cost per meeting—is based on proven, measurable results.
The pattern is consistent across all engagements: identify the biggest GTM infrastructure blocker (broken CRM, no enrichment, manual chaos, poor targeting), build the system, train the team, and hand it off. Pipeline and productivity compound from there.
These aren't hypothetical case studies or best practices from a textbook. They're what happens when a GTM engineer gets hands-on access to your sales stack, your team, and your GTM motion for 90 days.
Company Type
Series A B2B SaaS
Stage
Pre-revenue sales motion
Setup
15 employees, selling to mid-market (250-2000 person companies)
SQLs in 90 Days
Pipeline Generated
Reply Rate
Cost Per Meeting
Average Deal Size
Key Insight
The biggest win wasn't just volume—it was visibility. Once infrastructure was in place, the founder could see exactly where meetings came from, what messaging worked, and how to replicate success. This visibility created compounding returns as the team optimized and scaled.
Company Type
Series B Enterprise Software
Stage
Scaling GTM motion
Setup
80 employees, 12-person sales team, $10M ARR, selling to enterprises
Pipeline Growth
CAC Reduction
SDR Productivity
Research Time
Email Reply Rate
Meetings Scheduled
Key Insight
Signal-based targeting is the multiplier. Instead of reaching out to 1000 random contacts, reaching out to 200 accounts already showing buying intent and tech stack changes gets 3x the pipeline at 40% lower cost. The AI research agent meant SDRs stopped doing manual research and started doing relationship building.
Company Type
Bootstrapped B2B Services
Stage
Pre-product-market fit
Setup
8 employees, founder-led sales, $0 budget for SDRs, selling custom services to mid-market
Meetings Per Month
Pipeline Generated (Q1)
SDR Headcount Cost
Founder Sales Time
Pipeline Consistency
Cost Per Meeting
Key Insight
You don't need expensive tools to build winning GTM infrastructure. With AI and automation, a bootstrapped company can generate qualified pipeline with zero SDR headcount. The founder freed up 30+ hours per week to focus on closing deals and building product—the things that actually scale revenue.
Company Type
Series A SaaS (Post-Acquisition)
Stage
Post-M&A integration
Setup
30 employees, $2M ARR, had invested $200K in sales stack that was broken and unusable
Email Deliverability
SDR Productive Time
Meetings Booked
CRM Data Accuracy
Time to Close (Deal Cycle)
Tool Cost/Month
Key Insight
A broken CRM is worse than no CRM. It destroys team morale and makes data-driven decisions impossible. Rebuilding was expensive ($12K investment) but freed up 25+ hours per week of SDR time and doubled meetings per month. The team went from avoiding the CRM to trusting it because the data was finally clean and useful.
No amount of cold outreach will scale if your CRM is broken, your data is messy, and your tools aren't integrated. Every engagement starts with infrastructure: CRM architecture, data quality, enrichment pipelines, and workflow automation. Only then do we scale volume.
The first month saves 5 hours per week of manual research. The second month saves another 5 hours as you automate follow-ups and data entry. By month 3, you've freed up 25+ hours per week that your team redeploys to relationship-building and closing. That's 100+ hours per person per year.
Every case study started with better targeting (ICP, signals, intent) before volume. The result: 2-3x the reply rates and 2-3x the conversion rates of standard outreach. Reaching fewer, better-qualified prospects generates more pipeline than reaching thousands of random contacts.
If your emails land in spam, volume doesn't matter. Every engagement audits domain reputation, authentication (SPF/DKIM/DMARC), and email sending practices. Fixing deliverability from 65% to 97% alone can double pipeline.
Case Study 3 freed up 30+ hours per week of founder time. Case Study 1 freed up the founder from manual outreach entirely. Every engagement is designed to free up your highest-leverage person—usually the founder—to focus on closing deals and building product, not running GTM.
Every campaign produces a trove of data: reply rates by message type, conversion rates by company size, best response times. Using this data to iterate weekly compounds results. Case Study 2 went from 12% to 24% reply rates by analyzing what worked and optimizing messaging.
What you can expect from week 1 through ongoing support. Every engagement follows this pattern: audit → foundation → execution → handoff.
Once systems are in place, every hour invested in prospecting becomes 3-5x more effective. Founder frees up 30+ hours per week. SDRs shift from data entry to relationship building. This multiplier compounds every month.
Focusing on high-intent prospects, decision-makers, and companies showing buying signals gets 2-3x the reply rates and conversion. This means you generate more pipeline with fewer touches, not more touches to more people.
Cost per meeting drops from $1000+ to $100-200. This isn't just nice—it means you can scale profitably. You generate more pipeline, faster, at lower cost. Every additional campaign compounds, not diminishes.
The goal is always handoff. Your team owns the system, understands how it works, and can evolve it. You don't become dependent on external support. The infrastructure becomes your competitive advantage—harder to replicate than any one person.
These are real results from actual engagements across 10+ companies generating $100M+ in pipeline. Company names and specific details have been anonymized to protect client confidentiality, but the numbers, timelines, and methodologies are real. Every metric mentioned—pipeline value, conversion rates, cost per meeting, timeline—is based on actual results achieved.
Most engagements show initial momentum in 30-60 days. The first 30 days focuses on infrastructure setup, CRM architecture, and launching initial enrichment and sequencing. By day 60, you typically have 10-30 qualified opportunities in motion. By day 90, you have a fully documented, repeatable system. Results depend on commitment to implementation, CRM access, team participation, and decision-making velocity.
The case studies span pre-Series A startups through Series B companies, bootstrapped operators through well-funded teams, and multiple industries (B2B SaaS, enterprise software, B2B services). The core principles—infrastructure automation, enrichment waterfalls, AI personalization, signal-based targeting—work across all these stages. Your specific results depend on starting point, sales motion, and execution, but the methodology is proven across diverse markets.
Three challenges consistently emerge: First, most founders/sales leaders are buried in manual work and don't have time to build infrastructure. Second, teams lack a clear ICP and targeting strategy, leading to waste. Third, current CRM and tooling is a mess, making data-driven decisions impossible. A GTM engineer fixes all three by building systems that work without constant manual feeding.
Fractional GTM engineering costs $3K-$9K per month. In Case Study 1, $2.4M pipeline was generated in 90 days on a Core engagement ($5.5K/mo), so 90 days of cost was roughly $16.5K for $2.4M pipeline—a 145x ROI. In Case Study 2, 3x pipeline scaling on a $9K/mo Embedded engagement generated millions. The infrastructure built compounds over time, multiplying ROI in subsequent months and years.
GTM engineering is designed for handoff. Every engagement produces documented playbooks, architecture diagrams, training sessions, and dashboards so your team owns the system long-term. Most clients either keep the system running independently or maintain a small advisory engagement to evolve the system as the company scales. Some scale to embedded or full-time, but the infrastructure becomes self-service for your team.
Yes. These case studies start with small teams (8-30 people), but the same infrastructure scales to 50+ person sales organizations. The difference is complexity: larger orgs have multiple segments, longer sales cycles, and more tool integration. A GTM engineer scales the playbook, automates signal-based workflows, and builds AI agents to handle increasing volume without proportional headcount growth.
Cost per qualified meeting is the north star. Every other metric (pipeline value, reply rate, conversion) is a derivative of this. If you can lower cost per meeting from $1K to $100 while maintaining quality, you've won. That's what the infrastructure does—it automates the expensive manual work (research, list building, enrichment, initial outreach) so your sales team focuses on the human part (discovery, objection handling, closing).
Every company starts with a different challenge, but the approach is the same: audit your current GTM infrastructure, identify the biggest blockers, and build a system that compounds. Let's talk about where you are and what's possible.