David Moreira and Marcos Stu are the founders of Automate RevOps. Their book, The Demand Compass, launches next week, and this session is the framework inside it.
Every team has watched sales and marketing argue about lead quality. This episode is why that argument never resolves, and the fix.
Building the agent-native revenue organization
Our partners at Airspeed are hosting a live roundtable on September 8th.
AI is no longer just reporting on revenue teams. It's starting to do the work. Three operators get into what to automate now, what to build,
and what needs a rethink:
Chris Reisig on how AI is redesigning the way revenue teams perform, Cliff Simon (CRO, Polaris Ops) on the systems, workflows, and the build-versus-buy call, and Devang Agrawal (Co-founder, Airspeed) on what agent-driven execution can do today. Plus live Q&A.
Free to attend, and they'll send the recording even if you can't make it live.
What you’ll learn
Why 81% of the buying journey finishes before anyone becomes an MQL, and what that means for who you prioritize
The two axes that replace the single score, and why one has to be developed while the other has to be detected
How stacking signals with timing moves cold LinkedIn reply rates from 5-8% to 18-22%
Why scoring the individual throws away your earliest evidence of a deal
The four quadrants, and the one play and one owner each of them gets
Episode Highlights
00:00 - The 81% number, and what the MQL misses
05:46 - The Demand Compass, and why a map needs a compass
07:26 - Awareness is developed, readiness is detected
08:47 - Cold reply rates at 5-8% versus 18-22% with stacked signals
10:30 - Score the account, not the person
13:15 - Fine-tuning signal weights per client
15:55 - When a champion forks your repo but the VP signs
17:27 - Build your own signal detection, or use Clay
21:14 - Tracking readiness and awareness in one system
25:08 - A score a rep doesn't trust is worth nothing
27:51 - One play per quadrant, one owner
31:57 - Running this alongside your existing MQL
Key Takeaways
1. The MQL is one number doing two jobs
The supporting numbers are worse. 95% of your market is not buying at any given time, so only 5% is in play. Of that 5%, the MQL surfaces the fifth who reach out. And 10% of the buying journey happens on a call with a rep.
"81% of the buying journey happens before the MQL. If you're actually using MQL as the only indicator that prioritizes who you should reach out to, you're missing a lot of leads."
David's read on why the lead quality argument never ends: two teams using one number to mean two different things.
2. Split the score into awareness and readiness
Awareness has to be developed. Readiness has to be detected. Those are separate jobs, and the MQL mashes them into one figure, so sales reads it as intent while marketing reads it as reach.
Plot them against each other and you get four types of account instead of one queue.
3. Score behavior, not hand raises
Form fills are the last 5%, and most of that is noise. The signals worth tracking sit where buyers behave: your pricing page, GitHub repos, G2, communities, reactions to your posts and your competitors' posts, following complementary solutions.
Cold LinkedIn outreach replies at 5-8%. Stack signals with timing and it goes to 18-22%. Same team, same product. The only variable is how much signal sits behind the message.
4. Score the account, not the person
The engineer reads your docs. The VP owns the budget. Procurement prices it. Whoever leaves the trail rarely signs, so scoring individuals throws away your earliest evidence.
Marcos gave the sharpest version: a champion forking your repo tells you something the decision-maker's inactivity never will. Roll every signal up to the account, then look at the individual inside it.
5. Make the score explain itself
A score a rep does not trust gets ignored, and the work behind it counts for nothing. Every score should read back in plain language:
"An EVP of sales started working for that company 12 days ago. They visited our pricing page three times this week, our docs page twice, and that's why they are eight on readiness and four on awareness."
A rep can act on that in four seconds.
6. One play per quadrant, one owner
Cold. Doesn't know you, no readiness. Build awareness with cold email, ads, content, any top-funnel move.
Nurture. Knows you, not ready. Stay useful. One of their leads had been on the newsletter two years before he needed them.
In market. Doesn't know you, showing intent. Posting about the problem, hiring for the tool, following competitors. Prioritize and move fast with SDRs.
Sales ready. Knows you and ready to buy. Assign a full-cycle rep and respond in minutes.
You can run this in parallel with your existing MQL rather than ripping it out. Marcos points out you keep the MQL count for reporting while the quadrants drive the actual work.
If you're enjoying these episodes, reply and let me know what you'd love to learn more about: RevOps, signals, AI workflows, GTM strategy, anything.
Catch you next week,
Jared
P.S. The Demand Compass launches next week. Also, always growing our RevGenius community; you can join here to follow along.
Upcoming events
Your Pipeline Runs on Something You Can’t Forecast
Tuesday, 15th September | 11 AM EST | 8 AM PT
Predictable revenue comes down to rep execution, the part no dashboard shows you.
David Ashe of Allego gets into how AI roleplays prep reps for the objections nobody scripts for, and how real-time call signals become coaching that lands while the deal's still alive.
Signal Rich, Action Poor: What AI-Native Revenue Teams Do After the Insight
(Thursday, 17th September | 12 PM EST | 9 AM PT)
Your CRM knows what happened and your intelligence layer knows why, but the work still lands on a person at 6pm on a Thursday. Leaders from Airspeed, Clay, HubSpot, and Apollo map the third layer that closes the gap, where a signal becomes a finished action without anyone relaying it. You'll leave knowing which layer of your own stack is doing the least work.
From Workflow Chaos to Operational AI: Real RevOps Use Cases
Thursday 22 September, 1 PM EST
AI agents built specifically for the event, deployed against real broken RevOps workflows: lead routing, onboarding, forecasting, handoffs. Live builds, not generic hype.
Revolt! 2026 (Digital Conference)
14-15 October, 11 AM to 5 PM ET
Two days, dozens of sessions, 9,000+ leaders.
Last year drew registrants from 3,400+ companies across 40+ countries.
Want to get your brand in front of 60,000+ revenue leaders?
Partner with us and put your name at the center of the conversation.
