ZoomInfo

Most AI agents in GTM fail at the exact same step. It isn't the thinking. It's the handoff. Plug the smartest model in the world into a CRM and it still fails, because the CRM only ever held one slice of the story. The call notes live in one tool, the intent data in another, the pipeline in a third. The agent is reasoning off whichever fragment it can reach. And when we asked 50 senior GTM leaders what's breaking their AI... → 72% pointed at the way data moves between their tools and the CRM. → 60% said their agents can't reason across systems. So the teams getting AI to actually work have stopped asking a smarter question of one agent, and started asking a better question of their stack: what does a clean handoff look like? Because one agent doing one task inside one tool isn't the play. The play is a sequence of agents, each picking up clean context from the last, none of them copying between tools. Florin Tatulea and John Lloyd, MBA broke the whole workflow down, slide by slide. Three agents. One shared layer. And the reason most versions of this fail at step one. Swipe through, then subscribe to The Context Layer Digest for the next play as soon as it publishes. Link in the comments.

Your forecast is confident. Your CRO is not. Buyer behavior keeps shifting. Coverage math that worked last year does not hold anymore. Capacity plans built on old assumptions are quietly falling apart, and CROs feel it before anyone else does. Heading into 2027, CROs are raising the bar for what they expect from RevOps. Not more dashboards. Real planning precision, faster adaptability, and AI readiness built into the infrastructure, not bolted on after the fact. James Roth, Chief Revenue Officer at ZoomInfo, breaks down exactly what that shift looks like in our next live session, Inside the CRO's Mind: The New Realities of Architecting Revenue Growth, presented in partnership with Forma.ai. He'll cover: → How CRO expectations for sales planning are evolving → Why traditional planning assumptions are becoming less reliable → How the relationship between CROs, RevOps, and Finance is changing → What AI readiness actually looks like in modern planning infrastructure → How to build planning and decision-making processes that move faster than the market does July 20 at 2 PM ET with James Roth. Save your seat: https://bit.ly/4fgAhyO

What if you could pull call transcripts, email history, CRM data, and third party data into a single list using just one prompt in Claude? With ZoomInfo MCP in Claude, now you can. Watch this video from ZoomInfo Founder and CEO Henry Schuck to see exactly how it works. Ready to try it yourself? Sign up for free: https://bit.ly/44ywqsb

Some of the best buying signals might never show up in a traditional database—you have to go find them. In this video, ZoomInfo’s Florin Tatulea walks through one example of this: A company that sells pre-cut potatoes and fries to restaurants had a very manual problem. Reps were handed lists of restaurants by territory and had to work through them one at a time to figure out who was worth pursuing. No system existed to tell them, at scale, who actually sold fries. Using GTM Studio, we built a custom AI agent that solves this. It: 👉 Reads the live menu for every restaurant in a list 👉 Detects whether fries appear on the menu and counts related menu items 👉 Matches that against each location's footprint to estimate deal size 👉 Adds Google ratings so reps have a natural, relevant way to open the conversation The output? An account list built around a highly specific signal, matched against ZoomInfo's verified entity data and combined with first- and third-party sources for real context. The underlying idea applies far beyond fries: if there's a specific, unusual signal that indicates someone is a good fit for what you sell, GTM Studio's custom signals can go find it, verify it, and turn it into a prioritized account list your team can act on immediately. Learn more about custom signals in GTM Studio: https://lnkd.in/gmcRfW7S

Pretty much every company is pouring money into AI for their GTM teams. Question is, if you had a blank cheque... what would you build? We expected a long wish list from the 50 senior GTM leaders we asked. We got something very different. 62% gave the exact same answer: a unified data layer that connects every GTM tool. Then asked what's actually missing today and the answer lines up perfectly: -60% say they don't have a single view of the account.  -54% say they can't trust their CRM data.  -50% say they don't have real-time signals. So why doesn't everyone just build it? Because it's more than just a purchase, it's a full program. 1. Months of identity resolution and tech integration 2. No clear owner between RevOps, data and marketing 3. It never fits a quarterly budget cycle. ...So understandably, it stalls. But it’s very important to remember that you don't need to build the whole layer in one go. Try this instead: Pick one deal that stalled or got lost and then walk it backwards. Find the exact point where the information existed somewhere in your stack but never reached the person making the decision. That single missing connection is a great first build to tackle. You’ll already be able to prove what that deal would have been worth. That's how you get the second connection funded, and the third. Hear more from me and John lloyd in episode 4 of The Context Layer Tapes. Link in the comments.

Most GTM teams aren't unifying their product usage data, and it's costing them their best signals. In our latest leadership survey, we asked 50 senior GTM leaders one question: if budget wasn't a constraint, what's the one thing you'd build in your GTM stack? 62% gave the same answer. A unified data layer connecting every GTM tool, not a flashier model or more agents. Florin Tatulea and John Lloyd, MBA break down why on the latest episode of the Context Layer Tapes, including a real example: engineering teams building in GitHub repos, and why that signal only becomes useful once it's tied to website activity, intent spikes and CRM history. A signal in isolation tells you nothing. Connected, it's a play. Link in the comments.

I’m back with my FAVORITE GTM PLAY of the week. EVERYONE should be running this, THIS WEEK! It’s… Champion tracking! A champion who bought from you, went to bat for you internally AND already knows why you are better than your competitors, just left for a new company. The average CRM is sitting on 10,200 champion job changes that you could find with CRM enrichment. New seat, new budget, and a buyer you already won once! That's the warmest pipeline you'll find ALL YEAR. Here's how you run this play: 1) Drop your list of past champions into GTM Studio. The people who bought from you. Drop in a CSV or pull it from Salesforce, HubSpot or Microsoft Dynamics. 2) GTM Studio maps every champion to their current company, automatically. If they are at a new company, it will flag their new company, new title and new email. 3) Enrich the list with the signals you need to prioritize. How recently they joined, revenue, headcount, company structure, ultimate parent etc. Add as many columns as you want. 4) Now you've got a fully enriched, segmented list of past champions at new companies. You can then immediately route them to the right rep, while the move is still FRESH. Then set up auto-refresh, so the next time a champion moves, you already know. 5) Use AI to help with the outreach itself “Saw you started somewhere new - congrats. [We were a good fit last time, want to see if we can help here too? - this feels like generic slop]”