Revenue Operations Leader

Scalable revenue engines for the next era of SaaS.

With two decades of experience scaling SaaS leaders from Series A to IPO, I specialize in the architecture of high-growth revenue engines. I align Finance, Sales, and Product through data-driven strategy and AI-enhanced workflows to ensure organizations stay agile in an evolving market.

San Francisco Bay Area, CA tracyolson.ops@gmail.com LinkedIn

Operating Philosophy

Engineering high-velocity revenue systems.

I build the “single source of truth” environments where data-driven strategy replaces reactive decision-making—transforming operational debt into a scalable engine for growth.

  • Fiscal Integrity

    Predictability at Scale

    I partner with CFOs to translate complex pipeline data into high-fidelity forecasting and board-ready reporting.

  • Lifecycle Architecture

    Frictionless GTM Alignment

    I design infrastructure where PLG and Sales-Led motions work in tandem, mirroring the modern customer journey from trial to renewal.

  • Human Velocity

    AI-Enhanced Productivity

    I leverage automation and AI workflows to slash AE ramp time and accelerate ‘Time to First Deal,’ allowing people to move at peak speed.

Expertise

Breadth across the executive table. Depth in the systems beneath it.

  • Finance Alignment

    Partnering with the CRO and CFO to translate pipeline activity into board-credible forecasts and predictable revenue.

  • GTM Strategy

    Designing the territory, segmentation, and motion that turn market opportunity into repeatable pipeline.

  • Product Integration

    Connecting product signals — usage, activation, and expansion — to the revenue motion so PLG and Sales work in tandem.

  • Systems Architecture

    Lead-to-cash design, deal desk, forecasting cadence, and the operating rhythm that holds the GTM engine together.

  • Revenue Intelligence

    Transforming raw data into actionable insights through AI-driven forecasting and pipeline health analytics.

  • Operational Governance

    Establishing the rules, data hygiene, and validation logic that keep the engine clean and the numbers trustworthy.

Case Studies

Engineered outcomes, not anecdotes.

Three representative engagements where strategy met systems — and the numbers moved.

Fiscal Integrity

Scaling Forecast Accuracy from 70% to 95%

A "lumpy" pipeline with no discernible patterns made revenue forecasting nearly impossible, creating friction between Sales and Finance.

Key Result95% Forecast Accuracy

Architectural Transformation

Compressing Deal Desk Velocity by 80%

Rapidly doubling field headcount led to a slow, manual quote-to-cash process where historical customer data lived in disconnected Google Drives.

Key Result80% Faster Deal Desk

Human Velocity

Slashing Rep On-Ramp Time via AI-Intelligence Signals

Scaling the sales org was "scaling the chaos," with inconsistent territory assignments and resistance to new forecasting tools.

Key Result100% Tool Adoption

Every result above was achieved by aligning technical architecture with cross-functional human strategy.

Experience

A career building revenue engines.

Currently exploring Revenue and Sales Operations leadership opportunities at growth-stage SaaS companies.

  1. runZero logo

    runZero

    VP, Revenue Operations

    2024 — 2026

    Remote

    • Built the RevOps function from zero at a Series-A cybersecurity company ($22M ARR, 400+ customers) with no inherited playbook, just a blank slate and a growth mandate.
    • Architected the full GTM tech stack: CRM, CPQ, lead routing, and forecasting, with policy definitions for 18 quota carriers across PLG and Enterprise motions.
    • Launched a performance analytics system that enabled data-driven territory management and grew new logos 40% year-over-year.
    • Overhauled a manual deal process handling 150+ monthly transactions, reducing Deal Desk and Finance reconciliation time by 65%.
  2. D2iQ logo

    D2iQ

    VP, Revenue Operations

    2020 — 2023

    Remote

    • Operational lead for a Series-D company ($25M+ ARR) through a full acquisition by Nutanix. I kept the GTM machine running while navigating organizational transformation.
    • Owned annual sales planning for 70+ sellers: hiring models, quota design, and compensation, optimizing budget allocation for a company with 10 years of operational debt.
    • Orchestrated GTM data integration across Sales, Finance, and Legal through M&A close, resolving blockers and ensuring data integrity post-acquisition.
  3. Visier logo

    Visier

    VP, Sales Operations

    2018 — 2020

    Hybrid. Sunnyvale, CA and Vancouver, BC

    • Led SalesOps, BDRs, Enablement, and Deal Desk for a 75+ person organization at a Series-D company.
    • Partnered with Finance on TAM and productivity analysis that enabled rapid adaptation to shifting market conditions, supporting ARR growth from $35M to $50M.
    • Scaled the BDR team 25% while improving margin efficiency through geographic optimization.
  4. ThoughtSpot logo

    ThoughtSpot

    VP, Sales Operations

    2017 — 2018

    Palo Alto, CA

    • Directed Sales Ops, BDRs, Enablement, and Deal Desk for a 70+ person org at a high-growth Series-D company.
    • Revised forecasting models and sales processes that contributed to 270%+ customer growth in a single year.
    • Reorganized the Sales Development team and opened a Plano, TX satellite office, driving 20% year-over-year pipeline growth.
  5. Castlight Health logo

    Castlight Health

    VP, Field & Sales Operations

    2011 — 2017

    San Francisco, CA

    • Key operational leader through three distinct phases: hyper-growth, IPO, and acquisition — each requiring a different operational posture.
    • Built Deal and Renewal Desk functions supporting $123M in bookings, 75+ annual renewals, and 10 channel partner agreements.
    • Managed a proposal team responding to ~140 RFPs annually for complex healthcare buying committees involving Legal, Product, and Finance stakeholders.
    • Led IPO readiness: centralized systems, ensured data integrity, and built compliance infrastructure for post-IPO reporting requirements.

Selected Projects

Systems shipped, outcomes earned.

Built This Site with AI — No Developer Required

I designed and shipped this site using Claude (Anthropic) and Lovable, an AI-native web builder. No agency, no developer, no months-long project. I wrote the strategy, drafted the copy, and iterated on the design through prompts, treating the AI as a junior team member I was directing. It's live and it took days not months. And I will continue to iterate and release as I work on it. It's also a live demonstration of how I approach any new operational tool: start with the outcome, prompt toward it, and iterate until it's right.

What this shows

That's how I approach operational tooling: find the right leverage, move fast, own the output.

How I Run RevOps with an AI-Augmented Stack

I've replaced manual overhead with AI workflows across my day-to-day: Granola captures meeting notes automatically so nothing falls through the cracks. Whispr Flow handles transcription and action extraction. Claude handles analysis and GTM decision-making. Gong surfaces deal risk without manual review. The result: the cognitive overhead of tracking everything is largely gone. I spend time on judgment calls, not information management.

What this shows

The best RevOps leaders today aren't just operators. They're systems designers who use AI to multiply their own output.

Automating the Forecast So the CRO Stops Being Surprised

I built automated pipeline inspection workflows that ran before every weekly forecast call, flagging deals at risk of slipping based on activity signals, stage age, and close date movement. Instead of waiting for a rep to self-report a problem on Thursday, the system surfaced it on Monday. The result: fewer surprises, more productive forecast calls, and a culture shift from reactive firefighting to proactive deal management.

What this shows

Forecast accuracy isn't a one-time fix. It's an ongoing system. I build the infrastructure that keeps it honest.

Replacing Gut Feel with a Model — 30% Better SDR Connect Rates in 90 Days

Static lead scoring was sending SDRs after the wrong accounts — high firmographic scores, low actual buying intent. I replaced it with an AI-assisted model that combined firmographic data with behavioral signals: product usage patterns, content engagement, and historical conversion data by segment. SDRs stopped chasing cold leads and started working accounts already showing intent signals. Within 90 days, connect rates improved by 30%+, and time-to-pipeline dropped meaningfully.

What this shows

AI is most powerful when it removes the guesswork from high-volume, high-stakes decisions — like which accounts a seller should call today.

Skills

The tools and disciplines behind the work.

Leadership & Strategy

  • GTM Strategy & Architecture
  • Strategic Planning & Executive Partnering
  • Sales Performance & Forecast Rigor
  • IPO & M&A Readiness
  • Deal Desk & Contract Architecture
  • Sales Compensation & Quota Design
  • Pipeline Acceleration
  • Sales Enablement & Methodology
  • Cross-functional Alignment & Change Management
  • Cybersecurity GTM Strategy
  • Healthcare/Digital Health Scaling

Tech Stack

  • Salesforce
  • HubSpot
  • LeanData
  • Clari
  • Gong
  • Outreach
  • Salesloft
  • Tableau
  • Looker
  • ThoughtSpot
  • Conga
  • DocuSign
  • Cloudingo
  • LinkedIn Sales Navigator
  • Jira
  • Asana
  • Slack Enterprise
  • Granola
  • Whispr Flow
  • Claude
  • Gemini
  • ChatGPT

This list is not exhaustive — I’m continuously adding tools and capabilities as the landscape evolves.

Let’s talk

Let’s build something that scales.

I’m currently available for full-time, fractional, and consulting engagements. If you’re scaling a GTM motion and need an operator who’s done it before — let’s talk.