According to Gartner, 87% of CROs spend the majority of their time firefighting instead of executing on long-term strategic plans. Jose calls this the “growth guess gap”—the disconnect between the number revenue leaders commit to their boards and what’s actually achievable given the current state of their GTM systems.
The issue? Siloed data and disjointed planning processes. Marketing, sales, and customer success often work off entirely separate systems and dashboards. When RevOps tries to optimize one piece of the funnel in isolation, it often destabilizes another. Jose describes it as a three-legged stool—if you raise one leg without balancing the others, the whole system wobbles.
This is how operational blind spots form. For example:
If your GTM systems aren’t thinking systemically, you’re building a growth strategy on a cracked foundation.
Check out this blog post to see why solving RevOps is like solving a Rubik’s Cube—it takes systemic thinking and purpose-built tools to unlock growth.
The primary planning tool for most RevOps professionals is still Excel—and that’s a problem.
“Excel is older than most RevOps practitioners. It’s not designed to model interconnected systems,” Jose points out.
Spreadsheets are:
The result is a planning model that feels like building a Jenga tower—every change makes the whole thing shakier.
Jose reframes RevOps through the lens of lever-based decision making. In any GTM engine, there are dozens of variables—conversion rates, sales cycles, churn, expansion rates, headcount productivity, and more. RevOps professionals constantly ask: “Which one should we focus on to hit our number?”
These are the RevOps levers. The problem? Each lever is interconnected. Change one, and the others react. Traditional planning tools don’t account for these cascading effects.
Key lever categories include:
Jose’s challenge to the audience: Stop thinking in isolated KPIs. Start thinking like a systems engineer.
Jose introduces the idea of "context engineering”—the RevOps equivalent of "vibe coding" in software development.
In coding, AI models like GitHub Copilot have transformed developer workflows by taking contextual prompts and generating boilerplate code. Jose’s team at Xfactor is doing the same for RevOps planning. By connecting LLMs (like Claude or GPT-4) to a company’s CRM (e.g. Salesforce), you can generate advanced GTM models through simple prompts.
A single prompt can:
In other words, you go from “download data, clean it, build a model” to “ask a question, get an answer.”
This isn't just faster—it’s more flexible, more accurate, and infinitely repeatable.
Jose walks through an example prompt used by Xfactor customers:
“Analyze our closed-won opportunities from the past 12 months. Exclude outliers. What’s our average deal size, sales cycle, and conversion rates by segment? Based on this, how many new opportunities do we need to create this quarter to hit our $8M target?”
With this single prompt, the LLM returns:
All of this happens in <5 minutes, using live Salesforce data.
Rerun the same prompt next week and get updated results. This beats spreadsheet modeling by a mile—and your output is documented, transparent, and auditable.
Click here to discover how Xfactor’s AI-native architecture supports causal modeling and real-time simulation for GTM strategy.
Most forecasting tools rely on predictive AI. They analyze historical patterns and make future projections. That’s useful—but it doesn’t help you understand why something is happening or what will happen if you intervene.
“Predictive AI is like saying: People buy umbrellas when it rains. So if we sell more umbrellas, it must be raining.” – Jose Romero, VP of Product at Xfactor.io
This is correlation, not causation. What RevOps really needs is causal modeling: understanding how one lever impacts the entire system. That’s what Growth AI is designed for.
Click here to explore how GrowthAI enables you to move beyond manual RevOps and unlock the science of profitable growth.
Growth AI answers questions like:
It doesn’t just forecast—it simulates outcomes based on interconnected system dynamics.
Jose demos Xfactor’s simulation engine, which lets you test multiple “what if” scenarios across your GTM system. For example:
"What if I..."
The platform doesn’t just show the impact on bookings. It shows:
It’s like a flight simulator for revenue strategy. You’re no longer guessing. You’re experimenting—quickly, safely, and with real data.
A key concern with LLMs is hallucination: making up answers that sound plausible but are false. Jose addresses this head-on.
How to audit outputs:
This isn’t “take it on faith” automation. It’s explainable AI, customized for RevOps.
Too many RevOps leaders are stuck in tactical mode—managing leads, fixing dashboards, auditing pipeline.
Jose argues it’s time for a mindset shift.
“RevOps should think like a systems architect. You’re not managing data. You’re designing the engine that powers revenue growth.” – Jose Romero
Growth AI empowers RevOps to:
In short, you go from being a firefighter to being the one who builds the fire-resistant house.
Check out this blog post on three changes your sales team needs to make to business cases in 2025 to align with AI-powered growth strategy.
If your GTM planning still lives in spreadsheets, if your growth strategies are mostly best guesses, or if you feel like you’re reacting instead of driving—this webinar is your wake-up call.
AI is not here to replace RevOps. It’s here to elevate it.
When used strategically, Growth AI can help you:
This isn’t hype. It’s what best-in-class RevOps will look like in 2026. You just get to start now.
Join the RevOps Co-op to connect with 17,000+ revenue pros tackling the same challenges.
Explore more insights on our blog or sign up for an upcoming event.
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