The blog · Author
Demand architect and RevOps operator who builds the revenue system himself, inside the client’s team. Founder of automate rev.ops., co-author of the book.
Creepy is the message naming the signal, not the data behind it; first-party sourcing, a quarantined identity match and schema-level deletion are what a compliance review actually checks.
Catch the event, qualify it before you enrich it, then the company, then the people, and only then send. Start with triggers about people, not industries.
Six jobs Clay does in a prospecting system, from finding leads where they talk to routing replies, with the names Clay gives each feature today.
Sort LinkedIn activity by readiness and awareness, comment before you connect, and keep nurturing the ones who are not ready instead of dropping them.
Clay launched an agent-first way to build, Workflows and an Inbound SDR Agent, with marketing as its new buyer. The operator matters more; the partner question stays open.
The Map is a live, account-level view of the whole market; the Radar is what sweeps every account and keeps that view honest.
Marketing scores what it can see, sales rejects what it knows, and both are right. The gap is everything neither can see, and no meeting closes a data gap.
It hands the whole deal to the final form fill and throws away the nine months of movement that made it possible. What a board can fund is the account's timeline, which shows cause instead of credit.
LinkedIn returned 121 percent on ad spend in the 2026 benchmark, Google Search 67 and Meta 51, while budgets stayed where they were. The gap between the two tables is the trade sitting in the open.
Three, then a clean ending and no breakup note. Cold email builds awareness, not meetings, so it runs like advertising: a short round, a pause, and a different angle next time.
A hundred triggers from our 2024 catalog, mapped to the scrapers that catch them, and the two rules that decide whether any of it pays: rent the scraping, and land every trigger on one account record.
The sensor to switch on first: it names the companies already reading your pricing and docs, on demand you paid to attract, and it is deployable this week.
Demand creation builds the awareness that makes buying signal appear; demand capture acts on signal that already exists. Most teams build only capture.
RevOps automation runs the market map, signal capture, scoring, CRM upkeep and routing on a system, not a person. The order to automate them.
The 125 terms on our 2024 spam list fall into four kinds, money, urgency, promises and protest, and a second AI column in the enrichment table strips them before the email leaves.
Cold requests get accepted around 21 percent of the time. The same outreach into an audience that knows you or is in motion runs two to three times higher, with the copy barely changed.
Most of a B2B evaluation happens where no attribution tool is pointed, and the account doing it is visible months before your funnel would ever know.
Binet and Field's 60/40 is a fair starting point, but in B2B the only brand share that survives a bad quarter is the one you can measure by account.
Not every buying trigger deserves the same response. A five-variable scoring framework from our own archive ranks them, so a team acts on the five that matter.
6sense is one strong sensor on the readiness axis. The Demand Compass is the two-axis score above it that turns the signal into a decision you own.
A topic surge feeds one axis at the company level. What it cannot see is whether the account knows you, or what its people do on surfaces you own.
Not another intent feed: six sensors you own, a vendor feed as one input, and a two-axis score that reads them all. Compared with what each vendor sells.
Two 0-to-10 scores built from fixed weights and decay, never a model's guess. Where AI reads a signal inside the engine, and the one line it never crosses.
A public admission of budget: a Clay pipeline scrapes new job posts, qualifies them, rolls them to the hiring company, and scores hiring intensity into a ranked outbound queue.
Only about five percent of your market is buying at any moment. The rule is right; the mistake is thinking it tells you to pick a half.
Our own deployment numbers by channel, from cold to aware to in motion, and why the audience and the timing move the rate ten times more than the copy.
Two axes, four quadrants, one move each. The instrument that replaces the MQL with a reading of where every account actually stands.
The axis almost everyone gave up on is measurable from data you already own, if you treat awareness as a behavioral footprint instead of a survey result.
Three signal levels, industry, company and lead, and why only a company event plus lead behavior on the same account means the window is open.
The MQL packed four separate questions into one score. What confused sales, why it collapsed, and the two-axis model that replaced it.
The sales-marketing alignment conversation has been happening for 20 years. It keeps failing because it diagnoses the wrong problem. The gap is almost never about communication — it's about data architecture.
Most B2B revenue teams describe their pipeline as unpredictable. The reason is almost always structural: a funnel that empties faster than it fills. Here's how to build for the cycle instead.
Campaign-based demand gen resets every quarter. Always-on demand gen compounds. Here’s the structural difference — and why most marketing leaders are diagnosing the wrong problem.
Most B2B teams spend significant budget on events then lose 80%+ of the leads in a follow-up process that never runs properly. Here’s what it costs and how to fix it.
Most B2B revenue teams think they know their market. Their active prospect list tells a different story. Here’s why the gap exists, what it’s costing you, and how to close it without hiring a researcher.
If your pipeline slows when one person is out, that’s not a personnel problem. It’s a systems problem. Here’s how to find the dependency before the board does.
Most CMOs we speak to aren't struggling with effort. Their teams are busy, campaigns are running, content is going out. On paper, everything looks right. And yet the pipeline tells a different story, inconsistent, hard to predict, and increasingly expensive to sustain.
