CJLConnor J. Laughlin
Chicago · VP Marketing & GTM (acting CMO) · 2026

I built the GTM infrastructure behind $159.4M in marketing-influenced pipeline at a roughly $460M PE-backed enterprise. The work spans positioning, demand generation, CRM and attribution, RevOps reporting, governed AI workflows, sales enablement, and executive operating cadence.

My edge is the combination: acting-CMO judgment, RevOps mechanics, and enough hands-on technical depth to build the systems myself.

  • $159.4Mmarketing-influenced pipeline FY25GTM infrastructure built from zero
  • $52.5Mnet-new revenue contribution FY25GTM strategy, demand generation, and sales enablement infrastructure
  • 22-agentAI GTM operating systemgoverned workflows, approvals, audit trails
  • 35+ KPIRevOps reporting frameworkfunnel, attribution, unit economics, pipeline movement
  • $2.5M+first-90-day BDR pipelinesignal-driven demand engine with 2-hour SLA
  • 5 verticalsregulated GTM operating scope7 acquisitions, 8 acquired brands, 3 web properties, international footprint
See the case studiesTalk about a role
Connor at his standing desk with Henry the dog, looking out a window onto Lincoln Park, Chicago. Hand-drawn ink illustration
[Fig. 01]Connor and Henry hard at work - Chicago, IL
What I build

GTM strategy is only as good as the system underneath it.

I work where marketing, sales, data, AI, and executive reporting collide. The output is not a campaign calendar. It is a revenue operating layer people can inspect, run, and improve.

  1. 01

    Revenue infrastructure

    Lifecycle definitions, attribution, CRM architecture, routing rules, funnel math, and pipeline inspection.

  2. 02

    Executive marketing leadership

    Budget cases, board-ready reporting, team design, agency and vendor leadership, and operating cadence.

  3. 03

    AI GTM systems

    Governed proposal workflows, answer libraries, agentic content operations, RAG, n8n, MCP-style tooling, and human review gates.

  4. 04

    Narrative and proof architecture

    ICP, positioning, competitive intelligence, claims governance, proof libraries, sales enablement, and executive POV.

  5. 05

    Digital growth systems

    Programmatic SEO and GEO, schema, content operations, conversion paths, analytics instrumentation, and technical web governance.

Impact ledger

The numbers behind the operating system.

Every metric below has a claim posture in source. Exact figures are shown with the context that earned them. Softened phrasing is used where the raw artifact remains private.

Revenue and pipeline

$159.4Mmarketing-influenced pipeline

GTM infrastructure built from zero

net-new revenue contribution
$52.5M
net-new revenue contributionGTM strategy, demand generation, and sales enablement contribution
margin contribution
$25M+
margin contributionrevenue infrastructure ROI with attribution discipline
marketing-sourced closed-won
Multi-million
marketing-sourced closed-wonclosed-won revenue from marketing-sourced accounts

Funnel and demand

+2,821%net-new prospect growth

from a near-zero baseline through three GTM cycles

MQL growth
+1,073%
MQL growthmarketing-qualified leads tracked through the CRM
SQL growth
+757%
SQL growthsales-qualified leads tracked through the CRM
first-90-day pipeline from signal BDR
$2.5M+
first-90-day pipeline from signal BDRsignal-based prospecting pod, 2-hour follow-up SLA
meeting-to-SQL conversion
40%
meeting-to-SQL conversionpost-discovery qualification rate from BDR-set meetings

AI and operating output

22-agentAI marketing operating system

research, content, RFP, competitive, executive reporting

productivity uplift
400%
productivity upliftteam output measured against pre-system baseline
RFP response-time reduction
96%
RFP response-time reductiongoverned RFP workflow with human approval
team time recaptured
24.5 hrs/wk
team time recapturedweekly hours redirected from manual work to strategy
strategic deliverables, 60-day sprint
115+
strategic deliverables, 60-day sprintinternal deliverable count across content, RFP, intel, enablement

RevOps and executive reporting

35+KPI revenue funnel framework

awareness through revenue with unit economics

CRM data completeness
+400%
CRM data completenesscompleteness lift after data governance program
executive marketing reporting
Board-ready
executive marketing reportingCEO, CRO, and PE sponsor reporting cadence
ghost-pipeline inspection
Pipeline truth
ghost-pipeline inspectionclose-date movement and stage aging visibility

Narrative, content, and market architecture

774-linemessaging architecture

regulated business lines; artifact size kept internal unless approved

master GTM brief
10,900 words
master GTM briefstakeholder interviews, ICP, positioning, and proof
stakeholder interviews
20+
stakeholder interviews8 alignment gates across executive, sales, and product
faster RFP turnaround
75%
faster RFP turnaroundgoverned AI proposal workflow with source-backed answer library
pSEO and GEO system
380-page
pSEO and GEO systemprogrammatic SEO and GEO content system architecture
Vintage analog control panel with labeled dials, rocker switches, and toggle banks
[Fig. 10]Control panel, the operating layer underneath the numbers
Signature systems

Six systems I built and ran.

Each card states the business problem, what I built, the proof it produced, and the hire signal underneath.

  1. 01REVENUE OPERATING SYSTEM

    Revenue Operating System from Zero

    The GTM infrastructure behind $159.4M in influenced pipeline.

    The problem
    Marketing, sales, CRM, attribution, and reporting were not operating as one revenue system. Leadership needed pipeline truth, not activity summaries.
    What I built
    I built the operating layer: lifecycle definitions, attribution logic, 35+ KPI funnel architecture, reverse-funnel math, close-date movement tracking, CRM and data governance, executive dashboards, and a board-ready reporting cadence.
    • $159.4M marketing-influenced pipeline
    • $52.5M net-new revenue contribution
    • $25M+ margin contribution
    What it provesOpen

    I can operate at VP of Marketing & GTM and acting-CMO altitude while building the RevOps mechanics underneath the strategy.

  2. 0222-AGENT AI GTM OS

    22-Agent AI GTM Operating System

    A 4-person team needed the operating capacity of a much larger department.

    The problem
    A small team had to support content, demand generation, proposals, sales enablement, reporting, and brand work across 5 regulated verticals.
    What I built
    I self-taught Python, TypeScript, prompt engineering, and agentic workflow design to build a governed AI operating layer for GTM work: research, campaign briefing, content adaptation, RFP and RFX support, competitive intelligence, and executive reporting.
    • 22-agent AI marketing operating system
    • 400% productivity uplift
    • 96% RFP response-time reduction
    What it provesOpen

    I can lead the function and build the technical layer myself.

  3. 03GHOST PIPELINE DETECTOR

    Ghost Pipeline Detector

    Pipeline truth beats pipeline theater.

    The problem
    Executive reviews were full of optimism. Deal slippage, stage stalling, and rep activity gaps were hard to see until the quarter ended.
    What I built
    I built close-date movement tracking, stage aging, activity-to-opportunity ratios, rep accountability, and a weekly executive package that surfaced ghost pipeline in time to act.
    • 35+ KPI RevOps framework
    • Board-ready executive reporting cadence
    • +400% CRM data completeness
    What it provesOpen

    I can build the inspection layer that turns CRM data into accountability without crushing the team.

  4. 04SIGNAL DEMAND ENGINE

    Signal-Based Demand Engine

    I turned website and account intent into a sales-action workflow.

    The problem
    There was no clean outbound motion, no BDR budget, and no reliable way to decide which account signals deserved immediate sales action.
    What I built
    I built a signal-based BDR pod from existing resources, with fit scoring, WebSights and account intent, enrichment, routing, a 2-hour high-priority SLA, weekly signal review, playbooks, sequences, and a coaching cadence.
    • $2.5M+ first-90-day pipeline
    • 40% held-meeting-to-SQL conversion
    • 2 hours high-priority signal-to-touch SLA
    What it provesOpen

    I can build pipeline motion without waiting for perfect budget or headcount.

  5. 05PLATFORM NARRATIVE + ICP

    Platform Narrative and ICP Intelligence System

    Five regulated business lines needed one market story with proof behind it.

    The problem
    The company had multiple acquired brands, complex service lines, and commodity claims that made sales language inconsistent.
    What I built
    I built a master GTM narrative, ICP intelligence system, buyer trigger maps, competitive claims index, 5-pillar positioning framework, proof library, do and don't language guide, and a sales-ready messaging architecture.
    • 774-line messaging architecture
    • 10,900 words master GTM brief
    • 20+ stakeholder interviews
    What it provesOpen

    I can make a messy multi-line business commercially legible.

  6. 06POST-ACQUISITION SAAS

    Post-Acquisition SaaS GTM Bridge

    Acquired software needed a market story, cross-sell path, and sales motion.

    The problem
    A services business and an acquired SaaS capability had different sales motions, buyer expectations, and expansion paths.
    What I built
    I built a hybrid GTM architecture: product-led, sales-assist, and enterprise-services expansion, PQL scoring, customer-health logic, cross-sell triggers, named-account campaign strategy, and rep retraining.
    • $254M cross-sell whitespace
    • 73% CAC reduction
    • 112% NRR
    What it provesOpen

    I can translate M&A complexity into product marketing, revenue architecture, and sales enablement.

See all case studies
[Fig. 40] · Edge+1,400 words

Taste applied at velocity.

I build GTM systems where judgment is part of the architecture. That means clear specs, source-backed proof, human approval gates, trust calibration, and narrative discipline, on top of automation. In an AI-native GTM org, the leader's job is recognition. Knowing what is worth generating, what is worth trusting, and what is worth shipping.

  1. 01Taste applied at velocity
  2. 03Decision quality under uncertainty
  3. 07Trust calibration
  4. 11Operator empathy and adoption design
Read the edge
Abstract ASCII grid pattern with varying density across the field
[Fig. 09]The grid, what the work runs on
About

Connor J. Laughlin.

Chicago · VP of Marketing & GTM (acting CMO)

Santa Clara Finance taught me how to build the model. Northwestern Journalism taught me how to tell the story. Together they let me design revenue architectures that hold up under analytical pressure and read well to a buyer.

The path was not a straight line. Business development at the Vatican Museums. Executive search at Reilly Partners. Content at Brad's Deals when it had 10 million monthly visitors. Then more than a decade at TSI inside a roughly $460M PE-backed enterprise, building the GTM operating layer from first digital hire to VP of Marketing & GTM (acting CMO).

The personal version lives here. Kristin. Three dogs. A big family. Football, golf, cooking, travel.

Education

  • Santa Clara University

    B.S., Finance · Leavey School of Business

    2006 to 2009

  • Northwestern University

    Medill School of Journalism · coursework

  • English (native)
  • Italian
  • Spanish
Career timeline
  1. 012009 to 2012BD & MarketingVatican Museums
  2. 022012 to 2014Executive Search AssociateReilly Partners
  3. 032013 to 2015Content CreatorBrad's Deals
  4. 042015 to PresentDigital Marketing Manager to VP, Marketing & GTM (acting CMO)TSI
Now

What I am building and reading right now.

The case studies are the past tense. This is the present. New entries show up here when something ships or starts.

  1. Shipped

    Released the RevOps capacity planner

    A reverse-funnel tool that turns a revenue target into the leads, MQLs, SQLs, and opps required. Same math I ran at TSI to size demand mix.

    Open
  2. Building

    Governed RAG over the proof library

    Wiring the proof library to a small RAG endpoint so RFP responses can cite the exact claim, posture, and source without leaking the artifact.

  3. Building

    22-agent GTM OS rewrite in TypeScript

    Porting the Python orchestration to TypeScript + MCP-style tools so the audit trail and approval gates are easier to reason about.

  4. Reading

    Welcome to the Era of Experience

    Silver and Sutton on agent learning. Reading it next to the playbooks I drafted for the AI GTM OS.

  5. Learning

    Inference-time optimization for agentic workflows

    Practicing prompt routing and tool-call planning patterns that make 22-agent systems cheaper without losing review discipline.

Hire signal

What I am open to right now.

Available

Open to conversations now. Targeting first-half 2026 start, with flexibility for a standout role.

  • Open now

    VP, Marketing

    AI-native B2B SaaS, enterprise software, or PE-backed where growth depends on building the operating layer.

  • Open now

    CMO

    Acting-CMO scope I already run. Best fit where marketing is being built into a revenue function.

  • Open now

    Head of GTM

    Marketing plus RevOps plus sales enablement under one leader.

  • Warm fit

    VP, Revenue Operations

    If the org needs the RevOps mechanics first and the narrative second.

  • Warm fit

    GTM Engineer

    AI-native company that wants the build and the leadership wired together.

  • Selective

    Advisory

    Tightly scoped: GTM systems, AI workflow design, or revenue infrastructure.

  • AI-native B2B SaaS, enterprise software, vertical SaaS, PE-backed.
  • Building the operating layer, not managing a campaign calendar.
  • Seriousness about RevOps mechanics, claims governance, and executive cadence.
Get in touch

If you need the strategy and the system, let's talk.

I am focused on VP of Marketing & GTM, CMO, Head of GTM, VP Revenue Operations, Head of Growth, and GTM Engineer roles. Best fit: AI-native B2B SaaS, enterprise software, vertical SaaS, and PE-backed companies where growth depends on building the operating layer, not managing a campaign calendar.

Email Connor about a roleView case studies

I also take selective advisory conversations when the problem is tightly tied to GTM systems, AI workflow design, or revenue infrastructure.

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