GTM Resources
For Revenue Operators, Investors, GTM Leaders & anyone willing to read this nonsense
TOPICS
KEYWORDS
Automation and AI in Enablement: When to Automate, When to Human-Touch
AI and automation belong in enablement, but only in the right places. This article breaks down what to automate, where human coaching matters most, and how to avoid confusing efficiency with effectiveness.
Why “Strong Pipeline” Is a Misleading Metric (and What Investors Should Ask Instead)
Pipeline volume alone is a weak signal of future revenue. This article breaks down why “strong pipeline” can be misleading, and the conversion, velocity, and ICP metrics that matter far more to investors and operators.
The Hidden Revenue Risk Most Investors Miss in Due Diligence: Go-To-Market Operations
ARR alone does not tell you if revenue is repeatable. This article breaks down the GTM operational risks investors often miss in diligence and how to spot them early.
From Manual Reporting to Real-Time Intelligence: Transitioning Your Ops Org
Manual reporting turns ops teams into reporting factories. This article breaks down how to move to real-time intelligence and why it is critical for scaling modern organizations.
Building a RevOps Culture: Metrics, Mindsets, and Behaviors that Drive Growth
RevOps success starts with culture, not tools. This resource breaks down the metrics, mindsets, and behaviors that turn revenue data into alignment, trust, and growth.
What Happens When Your Attribution Breaks? Signs, Root Causes, and Fixes
RevOps attribution doesn’t fail because of the model, it fails because the system underneath breaks. Learn how to diagnose attribution issues and fix them at the source.
Investors’ Guide to Evaluating RevOps Maturity in Startups
RevOps maturity is a leading indicator of whether a startup can scale with discipline. This investor-focused guide outlines the key signals that reveal if a company is built to turn capital into predictable growth.
Scaling RevOps: From 1-Person Ops to Embedded Ops Team: What Changes and What Stays
As companies grow, a one-person RevOps model breaks. This guide explains how RevOps scales into an embedded team, what fundamentally changes, and the core principles that remain critical at every stage.
Data Governance for RevOps: Ensuring Clean, Actionable Data Across Sales, Marketing and CS
Most GTM teams struggle with messy, unreliable data. This guide breaks down how RevOps can implement true data governance—shared definitions, CRM-driven guardrails, and an ongoing hygiene cadence—to create actionable insights across Sales, Marketing, and CS.
Deploying Agentic AI in Sales and Marketing: Use Cases for RevOps
Agentic AI is redefining how RevOps teams operate. This guide breaks down the most impactful use cases—automated funnel diagnostics, intelligent routing, dynamic capacity models, and outbound optimization—helping sales and marketing teams move faster with greater consistency.
Exploring Multi-Touch + Predictive Attribution: What’s Real vs Hype
Attribution tech is full of hype. This practical guide explains what’s real about multi-touch and predictive attribution, where the models fall short, and how RevOps and marketing teams can use them to inform smarter spend—not chase perfect credit.
Turning Enablement into a Revenue Lever: What That Looks Like in Practice
Modern enablement isn’t about onboarding decks—it’s a strategic revenue driver. This guide breaks down how proactive, data-informed enablement aligns teams, improves execution, and turns GTM strategy into measurable results across the funnel.
Leveraging AI to Predict Funnel Bottlenecks: A Practical Guide
AI is transforming funnel diagnosis from reactive troubleshooting to proactive prevention. This guide breaks down how RevOps teams can use predictive modeling, anomaly detection, and clean stage definitions to spot bottlenecks early and keep revenue flowing.
RevOps Masterclass: Capacity Planning in an AI World
Learn how to master capacity planning in the age of AI with RevOps leader Jeff Ignacio. This session explores how to align top-down board goals with bottom-up performance data, identify key dependencies, and leverage AI to boost GTM efficiency and revenue predictability. Discover practical ways to plan smarter, track progress, and accelerate your FY’26 success.
How to know which tool is right for your RevOps team
Tool sprawl drains efficiency and clouds data across RevOps teams. This guide outlines a 5-step framework—from defining the problem to building a governance model—to help you evaluate vendors intentionally, simplify your tech stack, and turn tools into a strategic advantage.
Building GTM Teams: Marketing + Sales + Customer Success - Empowered by RevOps
Traditional handoffs between Sales, Marketing, and CS slow growth and fracture the customer experience. This article explores how cross-functional GTM squads—powered by RevOps—create unified teams that share accountability, operate from the same data, and drive faster execution across the entire customer journey.
Optimizing the Middle Game: SQL → Opportunity → Closed Won — Metrics & Playbooks
Most revenue is lost in the middle of the funnel — not at the top. This guide reveals how to optimize your SQL-to-Closed Won process with the right metrics, playbooks, and cross-functional alignment, helping RevOps and sales leaders drive faster, more predictable revenue growth.
What Great RevOps Looks Like at Series B vs Series C vs Growth Stage
Revenue Operations isn’t a one-size-fits-all function — it matures alongside your business. This guide breaks down what “great RevOps” looks like at Series B, Series C, and Growth Stage, revealing how alignment, orchestration, and strategic insight drive scalable revenue performance.
Why Most Board Meetings Are Useless and How to Fix Them
Tired of board meetings that go nowhere? Discover how to turn them into decision-driving sessions with smarter decks, clear data storytelling, and focused discussions that align leadership and accelerate execution.
How to Implement a Scalable RevOps Framework in 90 Days
Most RevOps projects fail because they take too long or lack structure. This 90-day playbook shows how to plan, automate, and measure a scalable RevOps system using AI and clear go-to-market sequencing.