automate rev.ops.

Every quarter-end, the same three questions land on my desk. Why should sales work this account. What actually moved it. What is the spend producing. Nobody can answer them cleanly. Not for lack of effort. Because the signal that mattered got lost somewhere in a six-month buying journey. The MQL was built to compress all of that into one question. In a complex sale, that question breaks. This is the problem 🧭 Marcos Stu and I spent two years on. The result is The Demand Compass, and we're launching it September 3rd with four operators who live this problem daily to pressure-test the framework live. → Patrick Spychalski → ☁️ Cliff Simon → Jérémy Grandillon → Matthew Volm Thursday September 3rd · 11:30 AM ET · Free · Live only Link to register in the first comment. — David Moreira Founder automate rev.ops. Clay Solutions Partner, Advanced Artisan

Every quarter-end I used to guess. Campaigns running. Intent data flowing in. And when someone asked "why is this account moving," I had no real answer. The MQL was never built for this. Ten people in the buying journey, and the one who cared most six months ago isn't the one signing today. That's the gap David Emanuel Moreira and I wrote the book to close. Two axes, tracked separately: how aware is this account, and how ready are they to buy. Never the same axis. September 3rd we're going live, and the part I'm most excited about is the panel. Four practitioners coming to tell us exactly where the framework falls apart. → Patrick Spychalski, Founder The Kiln → ☁️ Cliff Simon, Founder PolarisOps → Jérémy Grandillon, Founder TC9 → Matthew Volm, Founder RevOps Coop Thursday, September 3rd · 11:30 AM ET · Free · Live only Link in the first comment. — Hey I'm Marcos Stu Founder automate rev.ops. Clay Solutions Partner, Advanced Artisan

Nobody talks about the real reason most outbound lists stall. It's not the script. It's not the sequence. It's not the subject line. 30 sales-ready leads sitting in HubSpot. Zero phone numbers between them. Not junk leads either, right title, right company size, already scored and ready. Reps just couldn't call a single one. We run every enrichment through a waterfall now, Prospeo first, whenever a contact record is missing a phone. Sent those 30 through it. All 30 came back with a working mobile, pushed straight into HubSpot. Reps were dialing that same afternoon. What made me trust the numbers enough to actually work them: most B2B mobile data is guessed at from patterns. Prospeo pulls close to 80% of its mobile data from real sources, email signatures, CRM records, not inference. The numbers also get tested against real call outcomes, so the ones that stop connecting get downgraded instead of sitting in the database forever looking valid. The lesson wasn't "write better copy." The bottleneck was never the messaging. It was whether the number in the field actually rang. If you've got a sales-ready list full of dead numbers, worth running it through Prospeo.io and seeing what comes back. — Hey I'm Marcos Stu Founder automaterevops.ai Clay Solutions Partner, Advanced Artisan

🔜 We have a date. The Demand Compass launches September 3rd. 🧭 Marcos Stu and I have spent the last year and a half building demand systems for B2B teams, watching the same pipeline problems show up over and over, and writing down everything we figured out along the way. This is that book. The core idea is simple but it changes how you think about everything: awareness and readiness are not the same axis. Every account in your market sits somewhere across both. Where they sit tells you the one move that fits. Not a campaign. Not a sequence. One move. If you want a free extract before launch, request one in the first comment 👇🏻 — David Moreira Founder automate rev.ops. Clay Solutions Partner, Advanced Artisan

Most B2B teams are flying blind and calling it a pipeline strategy. David Emanuel Moreira and I watched the same scene repeat for three years: Marketing defending lead quality. Sales rejecting every list. Both sides right. Both sides losing. The problem was never the people. It was the model. So we built a different one. And then we wrote it down. The 🧭 Demand Compass is the framework we've used with a lot of teams to answer the one question the MQL never could: → Why awareness and readiness live on two separate axes → Why your scoring model can't tell you who's ready right now → The four account states and the one play that fits each → How to build a system that produces pipeline without you holding it together This is the first book we have ever written. We'd love for you to read the extract and tell us honestly what you think. What landed. What didn't. That kind of feedback means a lot right now. Extract in the first comment 👇 — Hey I'm Marcos Stu Founder automate rev.ops. Clay Solutions Partner, Advanced Artisan

The moment we handed scoring to an AI model, trust collapsed. Not because the scores were wrong. Because nobody could explain why they were right. A rep would look at a score and ask: where did that come from? And the honest answer was: the model thought it looked right. That's not something you can take into a pipeline review. So we drew a hard line. AI researches the account. It reads job posts, summarizes hiring patterns, tags the buying stage. It does the work that used to cost an hour per account. But it never decides the score. The score is deterministic arithmetic. Same signals, same number, every time. Every input is named and dated. A rep can read the case in seconds and understand exactly why an account is there. That's a score that survives contact with a skeptical sales team. AI at the edge means it's an input to the score, never the score itself. The moment AI becomes the score, auditability disappears, and a score nobody can audit is a score nobody trusts. This is one of the core rules we built our scoring systems around, and it's all in The Demand Compass, launching September 3rd. 📕 If you want to read the first chapters before launch, grab a free extract at demandcompass.ai — David Moreira Founder automate rev.ops. Clay Solutions Partner, Advanced Artisan