ZoomInfo

Here’s an interesting test we just ran with some surprising results on verified email data: We tested what happens when you point an AI agent at 5 different data sources for contact enrichment. 450 runs… Same agent and same prompt, only the retrieval tool changed. At first, coverage looks strong and the tables are “complete”. But we dove into the one column that really matters if you're using AI agents for outbound: verified work email. Specialist data tools returned a verified email 94% of the time. Web search returned one 22% of the time. Same "complete" status. Wildly different data to hand a rep. Web search can't return a verified email. It guesses a pattern (first.last@domain) so a fill-rate score can't tell the difference between a guess and a real one. If you're building agent workflows for your sales team right now, verified email is the column to check before you trust anything else the agent hands back. ZoomInfo’s full benchmark, methodology, and our findings here: https://lnkd.in/gGSTdDFm

ZoomInfo MCP is now live inside Replit's Integrations marketplace, giving Replit users natural-language access to verified company and contact data through GTM.AI, no custom API integration required. Connect once, then prompt the app for company firmographics, funding history, or contact data the same way one would prompt for any other feature. Sales users can chat with the Replit Agent prior to a customer call to find out about the target company size, HQ, founding year, product news, and prepare call notes. Marketing users can build an app that pulls ZoomInfo’s data mapped to their ICP and auto-generates landing pages with messaging that appeals most to them. First-time MCP connections come with 100 free AI credits. Data shouldn't be the thing standing between an idea and a working prototype. Learn more: https://okt.to/kfx2eO Connect: https://lnkd.in/gdvJbgrB

This is the visual representation of Uber's Context Graph in ZoomInfo. The context graph is something that is coming up more and more but it's been hard to articulate what it actually is. Here you see Uber in our CRM. Around it. Every single: -Email -Call -Insight from Call/Email -Parent & Subsidiary -Person we've interacted with -Intent Signal / Web Visits -Job Posting -Funding Round -Employee that works there -Champion Move -Contract we have with them -Account Owners ...to name a few. Good luck trying to vibe code this. It's incredibly difficult to get this all merged into the same record (Entity Resolution). This allows a human or an AI agent to go and easily find any relevant information that is necessary and not try to find different puzzle pieces in different records. It's why investing in data foundations is key. Not having this in place is why your AI output sucks. I have to build a GTM Context Graph - and that graph, unlike the context graphs for support or engineering, requires data that CONSTANTLY changes. And this graph is self-updating in real-time. That's what we've been building.

Talent Autopilot is here. Everyone has an agent, but not everyone has nearly two decades of verified professional data behind it. Recruiting doesn’t have an AI problem. It has a data problem. AI can do more work than ever, but bad data means it can also be wrong faster than ever. Tell Talent Autopilot who you need. It does the sourcing work for you, finding qualified candidates your searches may never have uncovered. Better Data. Better Discovery. Better Candidates. See what’s possible with Talent Autopilot: https://okt.to/a7nwpo

That’s a wrap on Dreamforce 2026! Whether you stopped by our booth, joined us at the GTM Lounge, caught our social content, or spotted one of our billboards, you may have noticed ZoomInfo showed up a little differently this year. For us, Dreamforce was an opportunity to show we’re more than just contact data. The reality is, GTM is changing. Teams need better context to understand what’s happening, the ability to act on it, and a place where people and agents can work together. That’s what we’ve been building over the last 18 months. It took us vandalizing our own booth and San Francisco billboards to get that message across! And for a quick reminder of the people, moments, and energy that made the week what it was, here's a montage of the best bits from Dreamforce. Thanks to everyone who came by, joined a conversation, watched, shared, or simply took a fresh perspective on ZoomInfo. Until next year.

The hottest job in GTM right now doesn't have a job description. GTM Engineering is one of the fastest-growing roles in B2B tech, and companies are defining it as they hire for it. Ask five leaders what the job covers and you'll get five different answers. So we're putting the question on the Revolt! stage. On October 14th, Florin Tatulea, GTM Engineer in Residence, walks through: → What GTM Engineering is, and how to define it for your org → The trends shaping the role and where it's heading → Real examples of GTM Engineering work in the wild → The skills you need to break into it You'll leave knowing whether the role belongs on your team, and what it takes to do it well. Brought to you with our Revolt! sponsor ZoomInfo, fresh off launching GTM.AI and a Leader spot in the Forrester Wave. 📅 Wednesday, October 14th, 11:15 AM ET Free to attend. Link to register in the comments.

GTM conversations are happening everywhere right now, scattered across threads, comments, and a dozen different platforms. GTM Roundtable is our latest webinar series that brings the most frequently talked about topics to the table, with leaders across marketing, sales and ops sharing their take and experiences, live. For episode one, we have two marketing leaders who've run and scaled both ABM and demand gen: Alice de Courcy (SVP, Organic Content, ZoomInfo) and Jamie Skeels (Director of Strategy, Rocket SaaS), sharing what it takes to run both as one system, including the lessons behind a $700K ABM pipeline. Join us live on Sept 29, 3pm BST / 10am ET. Register now: https://okt.to/7i9YGu

Had over 100 convos at Dreamforce. Everyone's building an agent. Give them the best data & context so your email says more than "congrats on the fundraise".

This week at #Dreamforce, we're proud to be named a preferred data vendor for Salesforce’s Hunter by Sales Cloud. With ZoomInfo GTM data and context in Hunter, you can turn your revenue goals into a game plan. Tell Hunter what you need to achieve like building the right pipeline, engaging leads, progressing deals, or preparing the forecast. It maps the work ahead, drives approved actions, tracks progress, and adjusts the plan as buyers and priorities change. No separate contracts or setup required. Try it today: https://okt.to/34uB61

This is the visual representation of Uber's Context Graph in ZoomInfo - Lots of people talk about the "GTM Context Graph" but very few have been able to articulate or visualize it so it makes sense. At the Center of this one: Uber in the CRM - surrounding it - every call, every email, every insight from a call or email, every parent and subsidiary (Uber buys a lot of companies), every person we've ever interacted with, every Intent signal, every job posting, every funding round, every employee who works there, where they used to work, every champion move, every contract we have with them, the account owners, every person who has interacted with the account and on and on and on and on. Who is building that on your team? Yes, I can build a SICK, the SICKEST demand gen and outbound motion in Claude - row by row personalization, unique facts against every account, and do another one tomorrow and the next day and the next day, but how do I get the power of AI into the hands of every person on the GTM team? I have to build a GTM Context Graph - and that graph, unlike the context graphs for support or engineering, requires data that constantly changes. GTM AI needs a managed context graph for agents, for humans - it needs it to be portable into coding agents, accessible into CLIs, MCPs, APIs - that's what we've been building.