newsmode MarketNews
arrow_back К списку
rss_feedClay Blog ·07.05.2026 open_in_newОригинал

How We Built a GTM Engineering Function in 2026 - The GTM with Clay Blog

Claygent Builder: The easiest way to build, test, and deploy GTM Agents

Build production-ready Claygents in natural language with Sculptor. Test on real data for free, track versions, and deploy once across every workflow. All inside Clay.

How Clay Uses Clay Ads: From $250 to $25 CPL

See how Clay uses its own Ads feature to cut LinkedIn CPL from $250 to $25 and unlock Meta with enriched CRM audiences. No manual uploads needed.

HG Insights Corporate Hierarchy: GTM Precision in Clay

Use HG Insights corporate hierarchy data in Clay to clean CRMs, map parent-child accounts, and trigger expansion plays. See how it works.

Sales GTM Engineering: How Clay Built the Role From Scratch

Learn what sales GTM engineering is, how it collapses SDR, AE, and SE roles into one, and how Clay built and hires for this high-leverage function. See how it works.

How to Automate Inbound Lead Outreach: The Clay Playbook

Learn how to automate inbound lead outreach with enrichment, scoring, and personalized sequences. See the exact Clay workflow that runs without manual work.

demandDrive Joins Clay’s Partner Ecosystem as an Official Clay Studio Partner

demandDrive joins Clay’s partner ecosystem to help B2B teams turn account intelligence into pipeline and revenue with GTM engineering and automation.

B2B Sales Prospecting: 15 Strategies to Drive More Conversions

Master B2B sales prospecting with 15 proven strategies covering ICP building, multi-channel outreach, and list hygiene. Build a pipeline that converts.

AI Sales Assistants: 11 Ways to Accelerate Your Outbound

Discover 11 ways AI sales assistants automate lead research, enrichment, and email personalization. See how top B2B teams use them to accelerate outbound.

The Three Laws of GTM: How to Win in the AI Era

The three laws of GTM explain why uniqueness, saturation, and iteration speed determine who wins. Learn how AI changes the rules and what to do about it.

Best Work Email Finders by Segment: SMB vs. Enterprise

We tested 12 email finders across 4,700+ contacts to find the best work emails by segment. See accuracy, cost, and coverage winners for SMB and enterprise.

How Clay Converts Trial Users Into Customers With Automated Outreach

See how Clay uses automated outreach to convert trial users into customers, with enrichment, lead scoring, and personalized HubSpot campaigns. Learn how.

Best Mobile Phone Data Providers for B2B Sales Teams

We tested 9,806 numbers across 10 B2B mobile phone data providers. See which wins on accuracy, coverage, and cost for NAMER, EMEA, and APAC.

How to Build a Complete AI Outbound Sales Funnel

Learn how to build a complete AI outbound sales funnel—from account scoring to personalized outreach—using Clay waterfalls and automation. See how it works.

How to Get More Customers Using Outbound Sales: A Complete Guide

Learn how outbound sales works, who it's right for, and how to build a strategy from prospecting to closing. Covers cold calling, email, and more.

How to Automate 6 Cold Email Campaigns in One Clay Workflow

Learn how to automate 6 cold email campaigns from a single Clay table — with enrichment, AI classification, and deduplication built in. See how it works.

How Clay Identifies Tier 1 Accounts: A Three-Score System

See how Clay identifies tier 1 accounts using a three-score system: fit, engagement, and contract value. Learn how sales and marketing align on the same priorities.

Lead Scoring in Clay: A Step-by-Step Formula Guide

Learn how to build lead scoring formulas in Clay to prioritize your ICP leads by employee count, job postings, and more. See how it works.

How to Validate Cold Outbound Offers and Find Message-Market Fit

Learn how to validate cold outbound offers by finding message-market fit — from breaking down your value prop to testing with a phased email approach. See how it works.

Troubleshooting Outbound Sales and Prospecting: A Comprehensive Guide

Fix broken outbound sales campaigns with this guide. Diagnose open and reply rates, reduce no-shows, qualify prospects with MEDDIC, and optimize what's working.

Bulk Enrichment: Enrich Millions of CRM Records in Clay

Bulk enrichment lets Enterprise teams enrich millions of Salesforce records with firmographics, tech stack, and AI research — then write results back automatically.

Clay Templates: Automate, Customize, and Replicate Any GTM Workflow

Clay Templates let you replicate full GTM workflows in hours, not days. Automate prospecting from data scraping to AI messaging, free and fully customizable.

How to Optimize Your Credit Usage in Clay

Learn how to optimize your credit usage in Clay with conditional formulas, Clearbit waterfall lookups, and smarter enrichment workflows. Save credits fast.

AI for sales prospecting

Learn about how to use AI for sales prospecting in this comprehensive guide, including framework for creating AI prompts and examples of cold email templates using AI that real sales teams have used successfully to land clients. AI sales prospecting can save your team thousands of hours—and double or triple your positive response rates.

The Reverse Demo: How Clay Replaced Traditional B2B Sales Demos

A reverse demo lets prospects solve real problems live, guided by your rep. Learn how Clay used 100+ sessions to boost conversion, retention, and product quality.

Data Waterfalls: How to Maximize Contact Coverage with Clay

Data waterfalls query multiple providers in sequence so you only pay for matches. See how Clay pushes coverage from 30% to 80%+ without annual contracts.

How Clay Runs ABM Campaigns: A Step-by-Step Playbook

See how Clay runs ABM campaigns — scoring 300 accounts, personalizing mailers and landing pages, and automating SDR follow-up. Learn how.

How We Built Clay's GTM Engineering Function

See how Clay built its GTM engineering function with sprint-based delivery, founder-level reporting, and full sales automation. A practical inside look.

Best Personal Email Finder Tools: Tested and Ranked

We tested 5 personal email finder tools across 2,354 prospects. See accuracy, coverage, and pricing data — plus the waterfall order that hit 79% coverage.

How to Use OpenAI to Write Cold Emails from Scratch with Clay

Learn how to use OpenAI to write personalized cold emails at scale with Clay. Set up the integration, craft better prompts, and boost deliverability.

How to Run a Personalized Demo Play at Scale with Clay

Learn how to automate a personalized demo play using Clay, Claygent, and AI enrichment to build custom mockups at scale. See how it works.

Automated Slide Deck Creation: How Clay Builds QBRs from Your Data

Clay's automated slide deck creation pulls from Snowflake, Salesforce, and Gong to build QBRs in minutes. Save 90+ hours per quarter. See how it works.

HG Insights + Clay: B2B Technographic and Firmographic Data

HG Insights surfaces deep technographic and firmographic data from billions of documents. Use it in Clay workflows to enrich accounts and power GTM. See how it works.

B2B Cold Email Deliverability: 21 Best Practices

Master B2B cold email deliverability with 21 proven best practices: domain setup, inbox warmup, authentication, and copy tips that keep you out of spam. Learn how.

Basics of Google Search Operators: A Practical Guide

Learn the basics of Google Search Operators and how to use them in Clay for prospecting, list building, and company research. See how it works.

AI Lead Generation: The Complete B2B Guide

Learn how AI lead generation automates list building, enrichment, and personalized outreach for B2B teams. Scale your pipeline without scaling headcount. See how it works.

Clay MCP: Ops-built workflows, consumable by reps

Clay MCP: Ops-built workflows, consumable by reps

How to Manage and Enrich Inbound Leads Automatically

Learn how to manage and enrich inbound leads automatically using a four-phase workflow that scores, segments, and triggers outreach from one email. See how it works.

GTM Alpha: How Winning Teams Build a Competitive Edge

GTM alpha is the edge winning teams build with unique data and signal-based plays. Learn how to find hidden signals, run better plays, and outpace competitors.

Why Good CRM Data Matters and How Clay Helps

Poor CRM data kills outreach. Learn why CRM data coverage fails and how Clay's waterfall enrichment lifts coverage rates from 20% to 80%. See how it works.

How to Use Formulas in Clay: AI Generator and Manual Entry

Learn how to use formulas in Clay with the AI Formula Generator or manual entry. Transform and clean your data faster. See how it works.

GTM Engineering: What It Is, How It Works, and How to Hire

GTM engineering turns ops teams into revenue builders using AI and automation. Learn what GTM engineers do, how to structure the role, and how to hire one.

Formulas in Clay: A Beginner's Intro for Non-Engineers

Learn how to use formulas in Clay without coding. This intro covers conditional statements, combining columns, and auto-qualifying leads. Start in 30 minutes.

How Clay Uses Clay for SEO and AEO: 3 Systems That Scale

See how Clay uses Clay for SEO and AEO: automated content refresh, video-to-page conversion, and a custom AI visibility dashboard. Learn how.

Turn Web Visitors into Leads: A Warm Outbound Play for B2B Sales

Learn how to turn web visitors into leads using a warm outbound play for B2B sales — with RB2B, Clay, and Lemlist. See how it works.

How to Use Web Scraping to Enrich Your Data with Clay

Learn how to use web scraping to enrich your data without code. Clay's Claygent answers deep GTM research questions at scale. See how it works.

How to Create a Sales Prospect List in Minutes

Learn how to create your own sales prospect list in minutes using Clay. Pull from 40+ sources, enrich with ICP data, and export to your CRM. See how it works.

Best B2B Email List Providers: Tested and Ranked (2026)

We tested 8 B2B email list providers head-to-head. See accuracy results, per-email pricing, and how to waterfall providers for maximum coverage.

Outbound Sales Automation: How to 10x Pipeline Without More SDRs

Learn how outbound sales automation replaces manual SDR work, cuts cost per email by 100x, and scales pipeline without growing headcount. See how it works.

The Wake the Dead Play: Reactivate Closed-Lost Deals with Clay

The wake the dead play uses Clay + ChatGPT to send automated, personalized emails to closed-lost prospects. Restart stalled deals in a few steps. Learn how.

Three Tips to Guarantee Email Deliverability for Cold Outbound

Split volume, verify contacts, and personalize copy to guarantee email deliverability for cold outbound. Three actionable tips that keep you out of spam.

How Clay Uses Clay for Customer Support: 3 Real Workflows

See how Clay's customer support team uses Clay to enrich Intercom tickets, automate QA, and draft help articles. Real workflows, real results.

B2B Cold Email Copywriting: The Complete Guide

Master B2B cold email copywriting with proven templates, a research framework, and a checklist used to send 800k+ emails a month. Start writing emails that get replies.

Introducing Clay Functions

Build Your GTM Logic Once, Apply It Everywhere

Clay and Apollo Integration: Enrichment, Sequencing, and More

The Clay and Apollo integration unlocks 5X faster enrichment and direct sequencer API access. See how joint customers go from data to booked meetings.

The Many Lives of Spreadsheets: A History and What Comes Next

Explore the many lives of spreadsheets — from VisiCalc in 1979 to self-filling automation tools today. See how the no-code vision keeps evolving.

AI recruiting strategies

Learn our top AI recruiting workflows to help you identify, research, and reach out to qualified candidates for open roles. AI can eliminate manual work and help you reach out to—and land—better employees for your clients.

How to Hire a GTM Engineer: The Complete Guide

Learn how to hire a GTM engineer: when to make the hire, what skills to screen for, red flags to avoid, and where to find the best candidates. See how it works.

Inside Clay's GTM Engineering Lab: Plays, Principles, and Automation

See how Clay's GTM engineering lab turns internal problems into revenue plays using AI, automation, and data-driven principles. Learn how it works.

How to Build the Most Targeted Account Lists Possible

Generic tools leave bad-fit companies in your account list. Learn how to build targeted account lists using AI enrichment and real workflow examples in Clay.

Personalized Direct Mail at Scale: The Gifting Play with Clay

Learn how to run personalized direct mail campaigns using Clay — validate contacts, generate AI gift copy, and export to email. See how it works.

How to Set Up Your Full Inbound Sales Process on Clay

Learn how to set up your full inbound sales process on Clay — enrich leads, tag MQLs, and automate email campaigns from form to demo. See how it works.

AI-Enabled GTM for Private Equity: The Value Creation Playbook

Learn how AI-enabled GTM for private equity drives value creation across portfolios—from data quality to agentic workflows. See how it works.

Do More With Your Data: Clay's Post-Data-Provider Approach

Clay's post-data-provider approach combines 150+ providers, waterfall enrichment, and AI scraping to maximize data coverage. See how it works.

Google Maps Lead Generation for Niche Local Businesses

Learn how to use Google Maps lead generation to find niche local businesses, enrich owner contacts, and send personalized outreach at scale with Clay.

24 AI Email Personalization Examples for Cold Outreach (With Prompts)

Get 24 AI email personalization examples for cold outreach, with ChatGPT prompts you can run at scale in Clay. Learn how to write emails that actually convert.

How to Ace Your Follow-Ups: A Practical Sales Guide

Learn how to ace your follow-ups with value-driven outreach, personalization tips, multi-channel tactics, and automation tools that keep deals moving. See how it works.

How to Prioritize Your Waitlist with Lead Enrichment

Learn how to prioritize your waitlist using lead enrichment. Turn raw signups into qualified leads by company, title, and role — no long forms needed. See how.

B2B Cold Email Templates: Frameworks That Get Replies

Learn how to write B2B cold email templates that convert with a proven 5-part framework, follow-up strategy, and real examples. See how it works.

Audiences: now in Enterprise beta

Clay Audiences unifies your CRM, product data, and intent signals into one layer — so reps and agents can run precise, personalized GTM plays at scale.

The thinking behind our new pricing: our internal memo

Clay pricing memo: INTERNAL

Introducing Clay’s new pricing

Today, we’re launching a pricing update that reduces data costs, and simplifies and improves the value of our plans. Our goal is to have Clay be your default tool for GTM Engineering.

Clay partners with Lusha and Beauhurst to expand European data coverage

Lusha adds lookalike prospecting, contact enrichment, and signals in EMEA. Beauhurst adds private funding and corporate structure data in the UK and Germany.

Source your precise TAM from lookalikes you can trust with Ocean.io and Clay

Clay + Ocean now enable preview-based B2B lookalike discovery. Preview leads before committing credits and expand your TAM with greater precision.

Clay doubles down on supporting European GTM teams

Clay's waterfall enrichment delivers 2–3x more mobile phone coverage than leading solo providers across Europe. Plus new data partnerships, a London office, and timezone-aligned support.

In Nigeria, she built a life where money wouldn’t decide

Clay blog | In Nigeria, she built a life where money wouldn’t decide

Sculptor Analyst Mode: Turning Context-Rich Data Into Actionable GTM Insights

Gather business intelligence and share documents of this analysis directly from Sculptor

In a place where girls often choose between career or marriage, she carved her own path 

Javeria Shah won the Clay Cup 2025 despite being denied a US visa and competing remotely from Pakistan. Learn how she transitioned from electronics engineering into GTM engineering and built her own business.

How we designed Sculpt

Our first conference, Sculpt, is where the analog soul of Clay met the digital mind of Clay.

Clay announces second employee tender offer in nine months at a $5B valuation

A rare repeat employee liquidity event, designed to give builders flexibility as Clay accelerates

Clay is now available as a connector in Claude

Bring Clay's contact databases, enrichment providers, and AI agents into your Claude workflow.

Sellers have a new AI edge: Clay in ChatGPT

Use Clay directly in ChatGPT to find the right buyers, research people and companies, and draft personalized outbound. One conversation, powered by live GTM data.

Clay reaches $100M ARR

Clay has crossed $100M ARR, growing from $1M to $100M in two years after six years of foundational product work. The milestone reflects durable customer adoption, efficient growth, and an ecosystem of GTM builders using Clay to power their business.

Clay Certifications: Turning mastery into credentials that matter

The Clay education team has built a certification program that runs entirely on Clay and gives users credentials that actually matter

Mobile Phone Verification Methodology

Clay has partnered with The Kiln to setup a series of large-scale data test across mobile phone, work email, personal email, email verification, and more. Below, we explain the approach to these tests.

Work Email Verification Methodology

Clay has partnered with The Kiln to setup a series of large-scale data test across mobile phone, work email, personal email, email verification, and more. Below, we explain the approach to these tests.

Stop Guessing, Start Analyzing: How Sculptor Turns Your GTM Data Into Your Competitive Advantage

Analyze your GTM data with Sculptor to turn fragmented information into actionable insight.

Find and outreach local businesses with Openmart and Clay Sequencer

Get the right contacts for local businesses without stitching together multiple tools or wasting valuable time on setup instead of selling.

Announcing Web Intent

Use Website Intent in Clay to see which companies visit your site, track engagement, and trigger personalized GTM plays. Turn website traffic into real buyer intent data.

How Clay Uses Clay: Conversational Data

How we use Clay to mine millions of pages of call transcripts to generate revenue, and how you can use it too.

Sculpting GTM’s future with six major launches

Today at Sculpt, we're launching six major features that will help teams turn any growth idea into reality faster.

Introducing Claygent Navigator

A new Claygent model that can use a browser to take actions and extract information from webpages.

Announcing the Clay Partner Program

The Clay Partner Program is to a partner, what a toolbox is to an artist. It keeps essential resources within reach and grows more sophisticated as your expertise develops. We've designed everything around one simple principle: helping you grow your business as Clay grows.

Introducing GPT-5 in Claygent: sharper research, stronger formulas, better outbound

GPT-5 is now a model option across Clay, bringing the best research and conversational writing we've ever shipped to your GTM workflows.

Clay Series C announcement. The GTM engineering era begins now

We raised a $100M Series C at a $3.1B valuation to power GTM engineering!

Claygent surpasses 1 billion runs

The world's most loved AI research agent in GTM has passes a huge milestone at 1 billion runs.

Announcing Sculpt: Clay’s first annual user conference

Join us for Sculpt, Clay’s first annual user conference on Sept 17 in San Francisco where GTM leaders build AI workflows, share creative tactics, and get early access to new features.

Announcing custom signals at Clay

Clay's new custom signals platform helps sales teams track unique data changes that indicate buying opportunities. Turn any data point into a sales signal, enrich with context, and automate personalized outreach to find GTM alpha your competitors miss.

Clay announces employee tender offer led by Sequoia at $1.5B valuation

Clay allows employees to sell vested shares for immediate liquidity through a $20M tender offer at a $1.5B valuation. With 10x revenue growth in 2022-2023 and serving 8,000+ customers including OpenAI and Hubspot, Clay continues to change how businesses approach go-to-market strategies with their AI agent Claygent.

Create personalized presentations at scale with Clay and Google Slides

Automate personalized sales decks with Clay’s Google Slides integration. Instantly generate tailored presentations for leads, customers, QBRs, and internal updates. Use one template to create hundreds of presentations at scale.

Turn Gong conversations into automated GTM workflows

Clay now integrates with Gong—turn messy call transcripts into powerful automations in Salesforce, HubSpot, Notion, Slack, Google Sheets, and 100+ other integrations.

Product

Use Cases

Solutions

Resources

Company

Pricing

Features

Additional

How Clay uses Clay

LinkedIn + Meta Ads on Autopilot

CRM enrichment

Keep your CRM clean with the highest quality data

BY TEAM

BY STAGE

BY CUSTOMERS

Mistral AI

Mistral AI

Link long form description will go in this slot here.

Merge

Merge

Link long form description will go in this slot here.

Verkada

Verkada

Link long form description will go in this slot here.

Figma

Figma

Link long form description will go in this slot here.

Hex

Hex

Link long form description will go in this slot here.

Intercom

Grew their outbound-sourced pipeline by +140%

START GROWING

DISCOVER

Community

PARTNER WITH US

Clay Commnity

In Nigeria, she built a life where money wouldn’t decide

OUR COMPANY

GET IN TOUCH

SOCIALS

Article – NY Times

Clay allows employees to sell shares at a $5b valuation.

How We Built Clay's GTM Engineering Function

Most companies treat GTM operations as a support function. Someone to clean up Salesforce data, set up sequences, maybe build a dashboard or two. At Clay, we took a different approach from the very beginning.

At Clay, GTM Engineering sits at the core of how we run go-to-market. The team reports directly to our co-founder Varun, alongside the first line of leadership below the founders. They operate like a product engineering team, with sprints, version control, and release notes. And they've automated large parts of our sales process while maintaining the systems that power both our self-serve and sales-led motions.

Thanks for reading The GTM Engineer by Clay! Subscribe for free to receive new posts and support my work.

Here's how we structured it, why it works, and what we've learned building GTM infrastructure at scale.

TL;DR

  • Clay splits GTM Engineering into two teams: forward-deployed engineers who work with customers, and internal engineers who build and maintain all GTM infrastructure.
  • The internal team operates in two-week sprints with version control and release notes, treating Clay tables and workflows like code.
  • GTM Engineering reports directly to a co-founder, not under a VP of Sales or RevOps, which gives the team authority to make architectural decisions without departmental politics.
  • The first GTM hire at any company should be a GTM Engineer, before the first AE, starting with building a clean "golden list" of target accounts.

Two types of GTM Engineers

We split GTM Engineering into two distinct teams:

  • Forward-deployed GTM Engineers work directly with customers. They help prospects evaluate Clay, scope implementations, and build out their specific use cases. Many came from rev ops or growth roles before joining Clay.
  • Internal GTM Engineers build and maintain all our internal operations. This team operates under Osman Sheikhnureldin and handles everything from deal automation to QBR generation to partnership workflows. They serve our customer experience team, marketing, growth, and partnerships. This is the team most people think of when they picture "ops."
  • Both teams could probably swap roles if needed. The main difference is temperament. The more engineering-minded people gravitate toward internal infrastructure. The folks who like podcasts and customer conversations end up forward-deployed.

    The GTM engineering tech stack

    Our internal team runs on four core tools: Clay, Snowflake, Salesforce, and Gong. Slack rounds out the stack as the actual interface our GTMEs use day-to-day.

    We built a Slack app that GTMEs interact with for most of their work. They can trigger campaigns, view signals, get pre-call research, access post-call meeting notes, and send follow-ups. All without opening another tab. The internal GTM Engineering team maintains this application using Clay's human-in-the-loop workflows deployed to our Slack instance.

    The simplicity matters. Most companies end up with 15+ tools in their GTM stack. We've kept it tight, which means less integration work and fewer places for things to break.

    The philosophy: flexibility within standards

    We let GTMEs use whatever meeting tools work for them. Some people run Gong and Granola simultaneously. Some use Attention for their personal notes. The meeting tool space moves fast, and different people have different preferences that will shift and evolve over time. We find that dictating exactly how people should work ends up leaving potential advantages on the sidelines.

    We do have one hard requirement: the data has to flow into Clay.

    For example, Gong always runs because it pipes into our automation infrastructure. But if someone wants to layer Granola on top for their own note-taking workflow, that's totally fine, as long as the transcript and key information ends up where our internal GTM Engineering team can transform it in Clay, people have flexibility to experiment.

    If you do nothing outside the core tools, you should have a great experience. But since we're Clay, you should also be able to experiment with new tools that you find interesting.

    Operating like an engineering team

    The internal GTM Engineering team works in two-week sprints. Other teams across Clay submit tickets for things like automation requests, data quality fixes, or new workflow needs. The team triages these tickets, bundles them into releases, and ships twice a month with full release notes.

    They version control their work. The Clay tables and workflows themselves get treated like code. They maintain documentation. When evaluating new vendors (we're looking at AI sales coaching tools right now), they run the technical evaluation and handle integration.

    This structure solves a problem most ops teams face: the endless queue of one-off requests. By batching work into sprints, the team can focus on larger infrastructure projects while still handling the daily asks. And by publishing release notes, the rest of the company knows what's shipping and when.

    What GTM engineers actually build

    The automation we've shipped falls into a few categories:

  • Content generation: Our growth strategy team (post-sales) gets handoff decks automatically generated when a deal closes. We pull data credit consumption data from Snowflake, call recordings from Gong, and account information from Salesforce. All of that gets formatted into a Google Slide deck that publishes itself before the kickoff call. We do the same thing for QBRs now. The deck builds itself from usage data and conversation history. The growth team just shows up and presents.
  • Follow-up automation: After discovery calls, the system drafts follow-up emails based on the call transcript. We've mostly solved this problem at this point.
  • Signal-based workflows: External GTMEs get notifications in Slack when accounts hit certain triggers. Product usage patterns, intent signals, contract milestones. The Slack app surfaces these moments and prompts the right action.
  • Pipeline operations: All the standard stuff around lead routing, data enrichment, territory assignment. But because the team operates in sprints with clear prioritization, this work doesn't crowd out the higher-value automation.
  • The next frontier is harder. Moving from a pretty good follow-up email to a great follow-up email, and doing that consistently over a multi-month sales process while building a comprehensive deck as you go is a 90th-to-95th percentile problem. So is doing something like taking information from multiple calls and turning it into proposals, one-pagers, case study drafts that actually sound like they came from a human who understands the customer's business. We're working on all of that right now.

    Why this structure works for Clay

    Clay is roughly 50/50 self-serve and sales-led. That split creates complexity.

    On the self-serve side, everything runs through pure automation. No human touches these deals until they're ready to expand. On the sales-led side, we have a traditional enterprise motion with forward-deployed GTMEs, discovery calls, multi-threading.

    A lot of top-of-funnel activity for our sales-led business actually happens in our self-serve customer base. Someone starts using Clay on their own, gets value, then brings it to their company. The internal GTM Engineering team owns the systems that identify these expansion opportunities and route them appropriately.

    This means they can't just focus on supporting the sales team or the growth team. They need to maintain infrastructure across both motions and build the connective tissue between them.

    Right now, moving customers from self-serve to sales-led isn't as smooth as we'd like. That's a major company priority. The fact that one team owns the systems on both sides makes that transition easier to improve.

    Applicability outside tech

    People assume Clay only works for tech companies doing PLG motions, but consider this: Waste Management uses Clay. They're completely outside our usual world of SaaS and tech buyers. But the use case was rock solid. The flexibility of the platform means GTM Engineering as a discipline can work across different industries and sales models. You're not locked into one type of motion or one type of buyer.

    The reporting structure

    Internal GTM Engineering reports to Varun, our co-founder and head of ops. They sit alongside executives running major functions, not buried under a VP of Sales or inside a rev ops org.

    This matters for prioritization. When the team that builds your GTM infrastructure has a direct line to founder-level leadership, they can make architectural decisions without getting stuck in departmental politics.

    We don't have a traditional CRO structure at Clay. There's no single leader with sales, marketing, post-sales, and ops all reporting up through them. Revenue ownership is more distributed. The growth team owns self-serve. The sales team owns sales-led. GTM Engineering facilitates both.

    That structure works at our current scale (around $100M in revenue). As we grow into a couple hundred million, we'll probably need to consolidate under a CRO or adopt something like Stripe's multiple-CRO model. But the GTM Engineering function will likely stay close to the top of the org chart regardless of how we restructure around it.

    RevOps vs GTM Engineering

    We still have a RevOps function, but it's split between GTM Engineering and finance.

    Finance handles forecasting, sets pipeline targets, and owns quarter-over-quarter sales planning. They work with GTM Engineering to align on the numbers and set targets across the organization.

    Anything involving systems, data quality, or automation lives with GTM Engineering. Territory carving, sequence deployment, dashboard creation, tool evaluation.

    It's a matrix structure. Pipeline targets are set by finance but delivered through combined efforts from growth, marketing, and GTM Engineering. The internal GTM Engineering team facilitates the execution. This setup works because both teams have clear swim lanes. Finance focuses on what the numbers should be. GTM Engineering focuses on the infrastructure that delivers those numbers.

    Tools beyond the core stack

    The internal team uses Clay, Snowflake, Salesforce, Gong, and Slack for most of their work. But we've layered in some AI tools that have proven valuable:

  • Dust acts as an agent layer on top of our company information. Notion, Gong, Salesforce, all of Slack. People use it for Q&A about internal processes, past conversations, and customer context. The feature we use most is Slack search with references to other conversations. We've started migrating some common Dust queries into Clay workflows. Once we see patterns in what people ask, we'll automate those specific questions. But there's still a long tail of ad-hoc questions where Dust shines.

  • Crosby handles our contract redlines. They do the first pass on every legal negotiation. In many cases, deals close without ever escalating to our legal team. We've cut redline response time from days to hours. The Crosby team has done impressive work making LLMs reliable for black-and-white legal language. No hallucinations, no made-up clauses. Getting that level of reliability for legal documents is harder than it looks.

  • Granola and Gong both run on calls, depending on what team members prefer. Gong is standard across the company (it feeds into all our automation). Some people layer Granola on top for personal note-taking. We've given teams flexibility to use what works for them, as long as the data ends up in Clay where the internal GTM Engineering team can transform it.
  • The sequencing challenge

    We're experimenting with Clay's native Sequencer for lower-volume, high-touch messaging. It's not ready for 50,000+ emails per month yet, but for the messages that matter (strategic outreach, expansion plays, partnership development) having everything end-to-end in Clay removes a lot of friction.

    For high-volume outbound, we use Gong Engage. Their new API changed how we think about sequences.

    The new Gong Engage API lets you customize every message and subject line in a multi-step sequence with a single API call. You can create a fully custom sequence per contact. Not template-with-variables custom. Actually custom.

    For GTM engineers, this is a step function improvement. You can pull data from anywhere, generate fully personalized messaging using LLMs, and deploy multi-touch sequences without template constraints. We use this API internally at Clay, and it's available as an action in Clay for customers building their own workflows.

    Where deals actually happen

    Here's something that doesn't show up in Salesforce: most of our executive-level sales happen over iMessage.

    Our sales process is designed to find the executive buyer and get their phone number. Then someone from leadership (myself, our sales lead Becca Lindquist, or our co-founders Kareem and Varun) texts them directly. We schedule calls, negotiate terms, and close deals over text. One of our largest deals this year happened entirely over Slack DMs. Also not synced to Salesforce.

    This creates a gap between our automation infrastructure and where work actually happens. The systems are built around email, Salesforce, and Gong. But real conversations happen in iMessage, WhatsApp, Slack DMs.

    We haven't solved this yet. It's manual. I add contacts to my phone, copy in their number, send texts from iMessage on my laptop. None of it syncs back to our systems.

    The same thing happens with Slack. Slack is a Salesforce product, but Slack DM conversations don't flow into Salesforce records. There's infrastructure work to be done here, and whoever figures out the DM channel problem will unlock a meaningful advantage.

    When to hire a GTM Engineer

    If we were starting from scratch today, the first GTM hire would be a GTM Engineer. Before the first AE. Definitely before building out a full rev ops team. (And if you're curious, we have an entire guide on how to hire a GTM engineer here.)

    You'd pair them with a founding AE and either a solutions engineer or a former customer who knows the problem space. Then you'd hire an outbound agency to handle volume. That team could do real damage finding early signal and building the foundation for scale.

    The first project for that GTM Engineer: build the golden list.

    This is the set of accounts where, if you got a magical intro tomorrow, you'd be thrilled. Each account has the right contacts, with up-to-date information, and clear reasoning for why it made the cut.

    Most companies don't have this. They start selling, build up a messy account list, and then six months later when they need to do territory carving, they realize they don't actually know how to structure their market. You end up with duplicate accounts, unclear segmentation, and territories that make no sense.

    Starting with clean account architecture makes everything easier as you scale. You know your segments. You know your ideal customer profile. You can build territories logically because you understand the shape of your market.

    The iterative nature of GTM Engineering is most valuable early. You can try different approaches every day without fighting through tech debt or organizational inertia. Later, the function is still critical, but you're engineering around constraints instead of building in a green field.

    What's next

    We announced several new products at our Sculpt conference. Sculptor, the native Sequencer, Audiences. A lot of that functionality is still rolling out to customers, which means the internal GTM Engineering team is actively building the workflows that take advantage of these new capabilities.

    Content generation is the current frontier. The gap between a good follow-up and a great proposal that synthesizes months of conversation is where we're pushing.

    And we're watching the sales interface space closely. The world of external GTMEs toggling between eight Chrome tabs is ending. What replaces it will probably be some single pane of glass that agents and ops teams can orchestrate behind the scenes. We're building toward that future, even if we don't know exactly what the final interface looks like.

    GTM Engineering works at Clay because we treat it like engineering. Clear ownership, sprint-based delivery, version control, release notes. The team has space to build real infrastructure instead of fighting fires.

    The reporting structure gives them authority to make architectural decisions. The tech stack stays simple enough that they can actually understand the full system. And the work they do (generating decks, automating follow-ups, routing signals) directly impacts revenue in ways everyone can measure.

    You don't need to be a data platform company to run this playbook. You need to believe that GTM infrastructure deserves the same rigor you'd apply to product engineering. And you need to hire people who can build, not just administer.

    Start early. Keep the stack tight. Give the team real engineering practices. Let them sit close to the top of the org chart.

    That's how you build GTM infrastructure that scales.

    Frequently Asked Questions

    Where should GTM Engineering report in the org?

    At Clay, internal GTM Engineering reports directly to a co-founder, sitting alongside other executive functions rather than under a VP of Sales or inside a RevOps org. That direct line to founder-level leadership lets the team make architectural decisions without getting stuck in departmental politics.

    What is GTM Engineering?

    GTM Engineering is the practice of building and maintaining the systems, automations, and data infrastructure that power go-to-market motions. At Clay, it covers everything from deal automation and signal-based workflows to QBR deck generation and pipeline operations, all treated with the same rigor as product engineering.

    How does GTM Engineering relate to RevOps?

    At Clay, RevOps responsibilities are split between GTM Engineering and finance. Finance owns forecasting and pipeline targets. GTM Engineering owns systems, data quality, automation, tool evaluation, and execution infrastructure. The two functions have clear swim lanes and work together to align on numbers and delivery.

    When should you hire your first GTM Engineer?

    Before your first AE. The first GTM Engineer's job is to build clean account architecture (the "golden list"), establish ICP segmentation, and lay the infrastructure foundation before sales volume makes it harder to fix. The iterative nature of GTM Engineering is most valuable when you're building in a green field, not engineering around existing constraints.

    Most companies treat GTM operations as a support function. Someone to clean up Salesforce data, set up sequences, maybe build a dashboard or two. At Clay, we took a different approach from the very beginning.

    At Clay, GTM Engineering sits at the core of how we run go-to-market. The team reports directly to our co-founder Varun, alongside the first line of leadership below the founders. They operate like a product engineering team, with sprints, version control, and release notes. And they've automated large parts of our sales process while maintaining the systems that power both our self-serve and sales-led motions.

    Thanks for reading The GTM Engineer by Clay! Subscribe for free to receive new posts and support my work.

    Here's how we structured it, why it works, and what we've learned building GTM infrastructure at scale.

    TL;DR

    • Clay splits GTM Engineering into two teams: forward-deployed engineers who work with customers, and internal engineers who build and maintain all GTM infrastructure.
    • The internal team operates in two-week sprints with version control and release notes, treating Clay tables and workflows like code.
    • GTM Engineering reports directly to a co-founder, not under a VP of Sales or RevOps, which gives the team authority to make architectural decisions without departmental politics.
    • The first GTM hire at any company should be a GTM Engineer, before the first AE, starting with building a clean "golden list" of target accounts.

    Two types of GTM Engineers

    We split GTM Engineering into two distinct teams:

  • Forward-deployed GTM Engineers work directly with customers. They help prospects evaluate Clay, scope implementations, and build out their specific use cases. Many came from rev ops or growth roles before joining Clay.
  • Internal GTM Engineers build and maintain all our internal operations. This team operates under Osman Sheikhnureldin and handles everything from deal automation to QBR generation to partnership workflows. They serve our customer experience team, marketing, growth, and partnerships. This is the team most people think of when they picture "ops."
  • Both teams could probably swap roles if needed. The main difference is temperament. The more engineering-minded people gravitate toward internal infrastructure. The folks who like podcasts and customer conversations end up forward-deployed.

    The GTM engineering tech stack

    Our internal team runs on four core tools: Clay, Snowflake, Salesforce, and Gong. Slack rounds out the stack as the actual interface our GTMEs use day-to-day.

    We built a Slack app that GTMEs interact with for most of their work. They can trigger campaigns, view signals, get pre-call research, access post-call meeting notes, and send follow-ups. All without opening another tab. The internal GTM Engineering team maintains this application using Clay's human-in-the-loop workflows deployed to our Slack instance.

    The simplicity matters. Most companies end up with 15+ tools in their GTM stack. We've kept it tight, which means less integration work and fewer places for things to break.

    The philosophy: flexibility within standards

    We let GTMEs use whatever meeting tools work for them. Some people run Gong and Granola simultaneously. Some use Attention for their personal notes. The meeting tool space moves fast, and different people have different preferences that will shift and evolve over time. We find that dictating exactly how people should work ends up leaving potential advantages on the sidelines.

    We do have one hard requirement: the data has to flow into Clay.

    For example, Gong always runs because it pipes into our automation infrastructure. But if someone wants to layer Granola on top for their own note-taking workflow, that's totally fine, as long as the transcript and key information ends up where our internal GTM Engineering team can transform it in Clay, people have flexibility to experiment.

    If you do nothing outside the core tools, you should have a great experience. But since we're Clay, you should also be able to experiment with new tools that you find interesting.

    Operating like an engineering team

    The internal GTM Engineering team works in two-week sprints. Other teams across Clay submit tickets for things like automation requests, data quality fixes, or new workflow needs. The team triages these tickets, bundles them into releases, and ships twice a month with full release notes.

    They version control their work. The Clay tables and workflows themselves get treated like code. They maintain documentation. When evaluating new vendors (we're looking at AI sales coaching tools right now), they run the technical evaluation and handle integration.

    This structure solves a problem most ops teams face: the endless queue of one-off requests. By batching work into sprints, the team can focus on larger infrastructure projects while still handling the daily asks. And by publishing release notes, the rest of the company knows what's shipping and when.

    What GTM engineers actually build

    The automation we've shipped falls into a few categories:

  • Content generation: Our growth strategy team (post-sales) gets handoff decks automatically generated when a deal closes. We pull data credit consumption data from Snowflake, call recordings from Gong, and account information from Salesforce. All of that gets formatted into a Google Slide deck that publishes itself before the kickoff call. We do the same thing for QBRs now. The deck builds itself from usage data and conversation history. The growth team just shows up and presents.
  • Follow-up automation: After discovery calls, the system drafts follow-up emails based on the call transcript. We've mostly solved this problem at this point.
  • Signal-based workflows: External GTMEs get notifications in Slack when accounts hit certain triggers. Product usage patterns, intent signals, contract milestones. The Slack app surfaces these moments and prompts the right action.
  • Pipeline operations: All the standard stuff around lead routing, data enrichment, territory assignment. But because the team operates in sprints with clear prioritization, this work doesn't crowd out the higher-value automation.
  • The next frontier is harder. Moving from a pretty good follow-up email to a great follow-up email, and doing that consistently over a multi-month sales process while building a comprehensive deck as you go is a 90th-to-95th percentile problem. So is doing something like taking information from multiple calls and turning it into proposals, one-pagers, case study drafts that actually sound like they came from a human who understands the customer's business. We're working on all of that right now.

    Why this structure works for Clay

    Clay is roughly 50/50 self-serve and sales-led. That split creates complexity.

    On the self-serve side, everything runs through pure automation. No human touches these deals until they're ready to expand. On the sales-led side, we have a traditional enterprise motion with forward-deployed GTMEs, discovery calls, multi-threading.

    A lot of top-of-funnel activity for our sales-led business actually happens in our self-serve customer base. Someone starts using Clay on their own, gets value, then brings it to their company. The internal GTM Engineering team owns the systems that identify these expansion opportunities and route them appropriately.

    This means they can't just focus on supporting the sales team or the growth team. They need to maintain infrastructure across both motions and build the connective tissue between them.

    Right now, moving customers from self-serve to sales-led isn't as smooth as we'd like. That's a major company priority. The fact that one team owns the systems on both sides makes that transition easier to improve.

    Applicability outside tech

    People assume Clay only works for tech companies doing PLG motions, but consider this: Waste Management uses Clay. They're completely outside our usual world of SaaS and tech buyers. But the use case was rock solid. The flexibility of the platform means GTM Engineering as a discipline can work across different industries and sales models. You're not locked into one type of motion or one type of buyer.

    The reporting structure

    Internal GTM Engineering reports to Varun, our co-founder and head of ops. They sit alongside executives running major functions, not buried under a VP of Sales or inside a rev ops org.

    This matters for prioritization. When the team that builds your GTM infrastructure has a direct line to founder-level leadership, they can make architectural decisions without getting stuck in departmental politics.

    We don't have a traditional CRO structure at Clay. There's no single leader with sales, marketing, post-sales, and ops all reporting up through them. Revenue ownership is more distributed. The growth team owns self-serve. The sales team owns sales-led. GTM Engineering facilitates both.

    That structure works at our current scale (around $100M in revenue). As we grow into a couple hundred million, we'll probably need to consolidate under a CRO or adopt something like Stripe's multiple-CRO model. But the GTM Engineering function will likely stay close to the top of the org chart regardless of how we restructure around it.

    RevOps vs GTM Engineering

    We still have a RevOps function, but it's split between GTM Engineering and finance.

    Finance handles forecasting, sets pipeline targets, and owns quarter-over-quarter sales planning. They work with GTM Engineering to align on the numbers and set targets across the organization.

    Anything involving systems, data quality, or automation lives with GTM Engineering. Territory carving, sequence deployment, dashboard creation, tool evaluation.

    It's a matrix structure. Pipeline targets are set by finance but delivered through combined efforts from growth, marketing, and GTM Engineering. The internal GTM Engineering team facilitates the execution. This setup works because both teams have clear swim lanes. Finance focuses on what the numbers should be. GTM Engineering focuses on the infrastructure that delivers those numbers.

    Tools beyond the core stack

    The internal team uses Clay, Snowflake, Salesforce, Gong, and Slack for most of their work. But we've layered in some AI tools that have proven valuable:

  • Dust acts as an agent layer on top of our company information. Notion, Gong, Salesforce, all of Slack. People use it for Q&A about internal processes, past conversations, and customer context. The feature we use most is Slack search with references to other conversations. We've started migrating some common Dust queries into Clay workflows. Once we see patterns in what people ask, we'll automate those specific questions. But there's still a long tail of ad-hoc questions where Dust shines.

  • Crosby handles our contract redlines. They do the first pass on every legal negotiation. In many cases, deals close without ever escalating to our legal team. We've cut redline response time from days to hours. The Crosby team has done impressive work making LLMs reliable for black-and-white legal language. No hallucinations, no made-up clauses. Getting that level of reliability for legal documents is harder than it looks.

  • Granola and Gong both run on calls, depending on what team members prefer. Gong is standard across the company (it feeds into all our automation). Some people layer Granola on top for personal note-taking. We've given teams flexibility to use what works for them, as long as the data ends up in Clay where the internal GTM Engineering team can transform it.
  • The sequencing challenge

    We're experimenting with Clay's native Sequencer for lower-volume, high-touch messaging. It's not ready for 50,000+ emails per month yet, but for the messages that matter (strategic outreach, expansion plays, partnership development) having everything end-to-end in Clay removes a lot of friction.

    For high-volume outbound, we use Gong Engage. Their new API changed how we think about sequences.

    The new Gong Engage API lets you customize every message and subject line in a multi-step sequence with a single API call. You can create a fully custom sequence per contact. Not template-with-variables custom. Actually custom.

    For GTM engineers, this is a step function improvement. You can pull data from anywhere, generate fully personalized messaging using LLMs, and deploy multi-touch sequences without template constraints. We use this API internally at Clay, and it's available as an action in Clay for customers building their own workflows.

    Where deals actually happen

    Here's something that doesn't show up in Salesforce: most of our executive-level sales happen over iMessage.

    Our sales process is designed to find the executive buyer and get their phone number. Then someone from leadership (myself, our sales lead Becca Lindquist, or our co-founders Kareem and Varun) texts them directly. We schedule calls, negotiate terms, and close deals over text. One of our largest deals this year happened entirely over Slack DMs. Also not synced to Salesforce.

    This creates a gap between our automation infrastructure and where work actually happens. The systems are built around email, Salesforce, and Gong. But real conversations happen in iMessage, WhatsApp, Slack DMs.

    We haven't solved this yet. It's manual. I add contacts to my phone, copy in their number, send texts from iMessage on my laptop. None of it syncs back to our systems.

    The same thing happens with Slack. Slack is a Salesforce product, but Slack DM conversations don't flow into Salesforce records. There's infrastructure work to be done here, and whoever figures out the DM channel problem will unlock a meaningful advantage.

    When to hire a GTM Engineer

    If we were starting from scratch today, the first GTM hire would be a GTM Engineer. Before the first AE. Definitely before building out a full rev ops team. (And if you're curious, we have an entire guide on how to hire a GTM engineer here.)

    You'd pair them with a founding AE and either a solutions engineer or a former customer who knows the problem space. Then you'd hire an outbound agency to handle volume. That team could do real damage finding early signal and building the foundation for scale.

    The first project for that GTM Engineer: build the golden list.

    This is the set of accounts where, if you got a magical intro tomorrow, you'd be thrilled. Each account has the right contacts, with up-to-date information, and clear reasoning for why it made the cut.

    Most companies don't have this. They start selling, build up a messy account list, and then six months later when they need to do territory carving, they realize they don't actually know how to structure their market. You end up with duplicate accounts, unclear segmentation, and territories that make no sense.

    Starting with clean account architecture makes everything easier as you scale. You know your segments. You know your ideal customer profile. You can build territories logically because you understand the shape of your market.

    The iterative nature of GTM Engineering is most valuable early. You can try different approaches every day without fighting through tech debt or organizational inertia. Later, the function is still critical, but you're engineering around constraints instead of building in a green field.

    What's next

    We announced several new products at our Sculpt conference. Sculptor, the native Sequencer, Audiences. A lot of that functionality is still rolling out to customers, which means the internal GTM Engineering team is actively building the workflows that take advantage of these new capabilities.

    Content generation is the current frontier. The gap between a good follow-up and a great proposal that synthesizes months of conversation is where we're pushing.

    And we're watching the sales interface space closely. The world of external GTMEs toggling between eight Chrome tabs is ending. What replaces it will probably be some single pane of glass that agents and ops teams can orchestrate behind the scenes. We're building toward that future, even if we don't know exactly what the final interface looks like.

    GTM Engineering works at Clay because we treat it like engineering. Clear ownership, sprint-based delivery, version control, release notes. The team has space to build real infrastructure instead of fighting fires.

    The reporting structure gives them authority to make architectural decisions. The tech stack stays simple enough that they can actually understand the full system. And the work they do (generating decks, automating follow-ups, routing signals) directly impacts revenue in ways everyone can measure.

    You don't need to be a data platform company to run this playbook. You need to believe that GTM infrastructure deserves the same rigor you'd apply to product engineering. And you need to hire people who can build, not just administer.

    Start early. Keep the stack tight. Give the team real engineering practices. Let them sit close to the top of the org chart.

    That's how you build GTM infrastructure that scales.

    Frequently Asked Questions

    Where should GTM Engineering report in the org?

    At Clay, internal GTM Engineering reports directly to a co-founder, sitting alongside other executive functions rather than under a VP of Sales or inside a RevOps org. That direct line to founder-level leadership lets the team make architectural decisions without getting stuck in departmental politics.

    What is GTM Engineering?

    GTM Engineering is the practice of building and maintaining the systems, automations, and data infrastructure that power go-to-market motions. At Clay, it covers everything from deal automation and signal-based workflows to QBR deck generation and pipeline operations, all treated with the same rigor as product engineering.

    How does GTM Engineering relate to RevOps?

    At Clay, RevOps responsibilities are split between GTM Engineering and finance. Finance owns forecasting and pipeline targets. GTM Engineering owns systems, data quality, automation, tool evaluation, and execution infrastructure. The two functions have clear swim lanes and work together to align on numbers and delivery.

    When should you hire your first GTM Engineer?

    Before your first AE. The first GTM Engineer's job is to build clean account architecture (the "golden list"), establish ICP segmentation, and lay the infrastructure foundation before sales volume makes it harder to fix. The iterative nature of GTM Engineering is most valuable when you're building in a green field, not engineering around existing constraints.

    More Articles

    Claygent Builder: The easiest way to build, test, and deploy GTM Agents

    How Clay Uses Clay Ads: From $250 to $25 CPL

    HG Insights Corporate Hierarchy: GTM Precision in Clay

    Sales GTM Engineering: How Clay Built the Role From Scratch

    How to Automate Inbound Lead Outreach: The Clay Playbook

    demandDrive Joins Clay’s Partner Ecosystem as an Official Clay Studio Partner

    B2B Sales Prospecting: 15 Strategies to Drive More Conversions

    AI Sales Assistants: 11 Ways to Accelerate Your Outbound

    The Three Laws of GTM: How to Win in the AI Era

    Best Work Email Finders by Segment: SMB vs. Enterprise

    How Clay Converts Trial Users Into Customers With Automated Outreach

    Best Mobile Phone Data Providers for B2B Sales Teams

    How to Build a Complete AI Outbound Sales Funnel

    How to Get More Customers Using Outbound Sales: A Complete Guide

    How to Automate 6 Cold Email Campaigns in One Clay Workflow

    How Clay Identifies Tier 1 Accounts: A Three-Score System

    Lead Scoring in Clay: A Step-by-Step Formula Guide

    How to Validate Cold Outbound Offers and Find Message-Market Fit

    Troubleshooting Outbound Sales and Prospecting: A Comprehensive Guide

    Bulk Enrichment: Enrich Millions of CRM Records in Clay

    Clay Templates: Automate, Customize, and Replicate Any GTM Workflow

    How to Optimize Your Credit Usage in Clay

    AI for sales prospecting

    The Reverse Demo: How Clay Replaced Traditional B2B Sales Demos

    Data Waterfalls: How to Maximize Contact Coverage with Clay

    How Clay Runs ABM Campaigns: A Step-by-Step Playbook

    Best Personal Email Finder Tools: Tested and Ranked

    How to Use OpenAI to Write Cold Emails from Scratch with Clay

    How to Run a Personalized Demo Play at Scale with Clay

    Automated Slide Deck Creation: How Clay Builds QBRs from Your Data

    HG Insights + Clay: B2B Technographic and Firmographic Data

    B2B Cold Email Deliverability: 21 Best Practices

    Basics of Google Search Operators: A Practical Guide

    AI Lead Generation: The Complete B2B Guide

    Clay MCP: Ops-built workflows, consumable by reps

    How to Manage and Enrich Inbound Leads Automatically

    GTM Alpha: How Winning Teams Build a Competitive Edge

    Why Good CRM Data Matters and How Clay Helps

    How to Use Formulas in Clay: AI Generator and Manual Entry

    GTM Engineering: What It Is, How It Works, and How to Hire

    Formulas in Clay: A Beginner's Intro for Non-Engineers

    How Clay Uses Clay for SEO and AEO: 3 Systems That Scale

    Turn Web Visitors into Leads: A Warm Outbound Play for B2B Sales

    How to Use Web Scraping to Enrich Your Data with Clay

    How to Create a Sales Prospect List in Minutes

    Best B2B Email List Providers: Tested and Ranked (2026)

    Outbound Sales Automation: How to 10x Pipeline Without More SDRs

    The Wake the Dead Play: Reactivate Closed-Lost Deals with Clay

    Three Tips to Guarantee Email Deliverability for Cold Outbound

    How Clay Uses Clay for Customer Support: 3 Real Workflows

    B2B Cold Email Copywriting: The Complete Guide

    Introducing Clay Functions

    Clay and Apollo Integration: Enrichment, Sequencing, and More

    The Many Lives of Spreadsheets: A History and What Comes Next

    AI recruiting strategies

    How to Hire a GTM Engineer: The Complete Guide

    Inside Clay's GTM Engineering Lab: Plays, Principles, and Automation

    How to Build the Most Targeted Account Lists Possible

    Personalized Direct Mail at Scale: The Gifting Play with Clay

    How to Set Up Your Full Inbound Sales Process on Clay

    AI-Enabled GTM for Private Equity: The Value Creation Playbook

    Do More With Your Data: Clay's Post-Data-Provider Approach

    Google Maps Lead Generation for Niche Local Businesses

    24 AI Email Personalization Examples for Cold Outreach (With Prompts)

    How to Ace Your Follow-Ups: A Practical Sales Guide

    How to Prioritize Your Waitlist with Lead Enrichment

    B2B Cold Email Templates: Frameworks That Get Replies

    Audiences: now in Enterprise beta

    The thinking behind our new pricing: our internal memo

    Introducing Clay’s new pricing

    Clay partners with Lusha and Beauhurst to expand European data coverage

    Source your precise TAM from lookalikes you can trust with Ocean.io and Clay

    Clay doubles down on supporting European GTM teams

    In Nigeria, she built a life where money wouldn’t decide

    Sculptor Analyst Mode: Turning Context-Rich Data Into Actionable GTM Insights

    In a place where girls often choose between career or marriage, she carved her own path 

    How we designed Sculpt

    Clay announces second employee tender offer in nine months at a $5B valuation

    Clay is now available as a connector in Claude

    Sellers have a new AI edge: Clay in ChatGPT

    Clay reaches $100M ARR

    Clay Certifications: Turning mastery into credentials that matter

    Mobile Phone Verification Methodology

    Work Email Verification Methodology

    Stop Guessing, Start Analyzing: How Sculptor Turns Your GTM Data Into Your Competitive Advantage

    Find and outreach local businesses with Openmart and Clay Sequencer

    Announcing Web Intent

    How Clay Uses Clay: Conversational Data

    Sculpting GTM’s future with six major launches

    Introducing Claygent Navigator

    Announcing the Clay Partner Program

    Introducing GPT-5 in Claygent: sharper research, stronger formulas, better outbound

    Clay Series C announcement. The GTM engineering era begins now

    Claygent surpasses 1 billion runs

    Announcing Sculpt: Clay’s first annual user conference

    Announcing custom signals at Clay

    Clay announces employee tender offer led by Sequoia at $1.5B valuation

    Create personalized presentations at scale with Clay and Google Slides

    Turn Gong conversations into automated GTM workflows

    Clay integrates with Webflow, unlocking scalable website personalization for GTM teams