8 Clay Plays Every Marketer Should Run
How Marketing teams are creating value in 2026
Dear GTM Strategist!
As a trained marketer and someone who spent 10 years working as Marketing Manager and CMO before ever having to learn RevOps/Sales for my own business, I have a hot take ♨️ on how nearly all cool technologies GTM technologies are tailored to “sales and RevOps” while marketing is massively lagging behind GTM AI transformation.
When Kyle Poyar and I launched The 2026 State of AI in GTM, I was shocked at how marketing GTM AI plays were mainly focused on productivity - how to do the exact same thing we were doing for the last 10 years faster, allegedly better, and in larger quantities. Some plays were more advanced, but so vendor-specific that I was gagged by how we lack imagination and ideas for reinventing the marketing process with the powerful AI tools we’ve had at our disposal for the last couple of years.
And I am not blaming marketing here for a sec - marketers are among the hardest working people in any organization. They run campaigns, take care of the brand, manage relationships with many stakeholders, organize events, manage advertising budgets, and handle the creative side of businesses. They were thrown AI at them and told: “Now be more productive and create better ROI.”
With increasing pressure on opex and an “adopt or die” mindset to AI, those people started to panic. FOMO on tools, feeling like their department is falling behind, and overselling on demos - best they could do was to create a couple of projects in ChatGPT/Claude to speed up content creation, bought some tools for mass generation of creatives, and at best started playing with some agents to be able to prove to their bosses that they too are AI-transformed now.
But that created problems - deeper problems that we’d expect. As a result of local AI implementations, new silos emerged within the organization. And it is even worse when you go out there and see them in person.
Mainstream B2B marketers are still sold on the idea that their job is to do “inbound marketing” - a concept HubSpot pioneered in 2006. People, that was exactly 20 years ago. This idea is dead. In 2026, we should be holistically thinking about integrated buyer experiences and ensuring that Marketing and “Sales” are elegantly aligned to drive demand toward business outcomes. And that means outbound, data enrichment, and the notion of redefining what we call Marketing Qualified Lead (MQL) with signals we have at our disposal beyond “downloaded an ebook”, “liked our LinkedIn post”, and “registered for a webinar”.
People don’t like it when I say that marketers should move into the role of business developers, sharing tools with RevOps, but that is exactly how we enable marketers to squeeze more out of the activities they are already putting so much time, money, and effort into. By working hand in hand with Marketing leaders in my clients’ orgs and running 50+ Clay tables for them, I put together a starter pack of 8 plays that show you how to use Clay across your entire marketing stack.
These aren’t edge cases or anything new to add to an already full to-do list. These are plays marketing teams are running right now, and this is how you squeeze more value out of them. People love them - I published an earlier version on LinkedIn, and the post went viral.
In this article, I’ll walk you through the concept behind each play and when to use it. For the full step-by-step implementation guide with prompts, scoring formulas, and integration details, grab the complete playbook here.
8 Marketing Clay Plays
Here’s what we’ll cover:
Play 1: Newsletter Audience Intelligence — Turn a flat email list into segmented, personalized content
Play 2: Competitive Ad Intelligence — Pull ad spend and messaging data across 50 competitors in one table
Play 3: Event & Conference Intelligence — Walk in prepared, walk out with scored follow-up lists
Play 4: Influencer & Creator Vetting — Vet 200 creators by content relevance, not follower count
Play 5: Community & Forum Intelligence — Capture competitor complaints and buying intent from Reddit, automatically
Play 6: Partnership & Co-Marketing Discovery — Replace “who should we partner with?” gut feelings with data
Play 7: Programmatic Personalized Landing Pages — Generate 1:1 pages per account at scale
Play 8: Podcast & Speaker Pitch Lists — Pitch 200 shows in the time it takes to manually research 10
Let’s dig in 🔎
Play 1: Newsletter Audience Intelligence and Segmentation
Marketing function: Email / Content Marketing
Difficulty: 2/5
You’re sending the same newsletter to everyone. Your VP of Marketing subscribers get the same content as your RevOps ICs. Your SaaS readers see the same topics as your e-commerce readers. And you have no idea who any of these people actually are — you have email addresses, maybe first names, and that’s it.
The play: Import your subscriber list into Clay, enrich every subscriber with firmographic and professional data (company, title, seniority, industry, revenue band), then use an AI column to cluster your audience into meaningful segments — not by demographics, but by content needs.
Think segments like “SaaS Leaders” (VP+ at SaaS companies, cares about strategy), “Startup Operators” (any role at sub-50-person companies, needs tactical how-tos), or “Agency/Consultants” (needs frameworks they can apply to clients).
Three outputs from one table:
Segmented email lists synced back to your email platform — different content for different audiences
Content intelligence — you know exactly which topics each segment cares about, so your editorial calendar is driven by data, not guesses
Sales-ready leads — subscribers who match your ICP, already warm, exported to CRM with full context
The marketers getting this right are seeing 45%+ open rates on segmented sends. Same list. Same effort. Different results — because they know who’s reading.
Bonus: If you sell sponsorships, the enriched data is a goldmine for pricing. “38% of our subscribers are VP+ at SaaS companies doing $50M+ in revenue” justifies 2-3x higher CPMs than “we have 10,000 marketers on our list.”
Play 2: Competitive Ad Intelligence
Marketing function: Advertising / Competitive Intel
Difficulty: 2/5
Be honest — here’s how most marketing teams do competitive ad research: Check Facebook Ad Library. Screenshot a few ads. Check LinkedIn. Maybe Google Ads Transparency Center if you’re thorough. Do that for competitor #2, #3... and by #4 you’re bored and skipping. You end up with a folder of screenshots and zero pattern analysis.
The play: Build a Clay table with 50 competitors and pull structured ad data using Clay’s native integrations — Adbeat for display and video ads across 80+ networks, Semrush for paid search intelligence and traffic sources. Then use an AI column to classify messaging themes across the entire landscape.
This is where it gets interesting. Instead of knowing what one competitor’s latest ad looks like, you can answer questions like:
What messaging themes are overused in our space? (If everyone says “Scale faster with AI,” maybe don’t.)
What pain points are under-addressed? (Nobody’s talking about implementation pain? That’s your angle.)
What offer types dominate? (If everyone offers demos, maybe a free trial stands out.)
Who’s spending the most and where? (Actual budget benchmarks, not guesses.)
Output: A competitive positioning brief with real spend data, messaging pattern analysis, and 3 specific recommendations for how to differentiate. Updated whenever you want — not once a quarter.
Good news - Clay just launched an Ads feature so you can build ad audiences directly in Clay, enrich them, and with that achieve a much better match rate (up to 90%, compared with standard 30% if you work only with firmographics) - and drastically lower your cost-per-lead. Then you can push them directly to LinkedIn Ads or Meta Ads using the Clay integration.
Watch my Clay Ads demo:
Play 3: Event and Conference Intelligence
Marketing function: Events / Field Marketing
Difficulty: 3/5
Events are the biggest line item in most marketing budgets. And the follow-up is always the weakest link.
Pre-event, you LinkedIn-stalk 20 people the night before and hope for serendipity. Post-event, badge scans sit in a spreadsheet and someone sends a generic “Great meeting you!” email two weeks later. You spent $30,000 on a booth and can’t prove ROI.
The play has two halves:
Before the event: Import the attendee/speaker list into Clay, enrich with company data, then — and this is the key step most people skip — define your trigger signals and scoring priorities. Not generic firmographics. Your signals. Are they hiring a RevOps person (signal: building the team that buys your tool)? Using a competitor’s product? Recently raised Series B? New CMO in the last 90 days?
Use a Claygent column to research each attendee against your custom triggers. Then generate personalized talking points that reference their actual situation.
Instead of walking up with generic “How’s your team scaling?”, you get “I saw you’re hiring a RevOps lead and just moved off [Competitor] — how’s the transition going?” That starts a real conversation.
After the event: Import engagement data (badge scans, conversations, demo requests) and score attendees by interaction depth. A badge scan gets a generic nurture. A demo request gets AE handoff the same day. Everyone in between gets follow-up matched to their engagement level, with messaging that references their specific situation.
Output: Walk in prepared with a ranked “who to meet” list. Walk out with prioritized follow-up that hits within 24 hours.
Play 4: Influencer and Creator Vetting at Scale
Marketing function: Influencer Marketing
Difficulty: 3/5
B2B influencer marketing is exploding, and vetting is 90% of the work. Find a creator. Go to their LinkedIn. Scroll through posts. Check engagement. Are the comments real? Do they actually post about relevant topics? Now do that 50 times.
Most teams vet 5-10 creators manually and pick based on gut feel and follower count. Follower count is a vanity metric. A creator with 5,000 engaged ICP followers beats one with 100,000 random ones every time.
The play: Feed 200 potential influencers into Clay. Use enrichment providers (Apollo, Clearbit, Modash) for structured profile data — title, employer, follower counts, engagement rates. Then use Claygent for thought leadership research — searching the open web for their articles, podcast appearances, conference talks, and blog posts.
Score by content relevance (do they write about your topics?), professional credibility (what’s their background?), content volume (are they actually active?), and platform reach (weighted last, not first). Add a red flag detection layer — are they employed at a competitor? Have they gone inactive?
For everyone scoring above threshold, generate personalized pitches that reference their specific content. Not “we’d love to leverage your audience” but “Your article on signal-based selling aligns with what we’re building — here’s a specific collab idea.”
Output: A data-driven influencer selection in hours, not weeks. Decisions based on what creators have actually published, not their follower count.
Play 5: Community and Forum Intelligence
Marketing function: Community / Competitive Intel
Difficulty: 1/5
Reddit threads, industry forums, public community discussions — people are literally typing out their problems, frustrations with competitors, buying criteria, and feature requests. In public. For free. And nobody monitors them systematically.
The play: Use Clay Signals (a free, native feature) to automatically monitor Reddit for mentions that match your criteria — competitor names, pain-point phrases (”looking for a tool that…”, “frustrated with…”, “alternative to…”), and buying intent signals. When Signals flags a relevant discussion, use Claygent to visit the specific thread and extract deeper intelligence.
Each mention gets classified by signal type:
Competitor complaint → Feeds your battle cards and competitive positioning
Pain signal → Becomes your next blog topic or ad angle
Feature request → Goes to the product team
Buying intent → Alerts your content team or community manager to engage (with a helpful comment, not a sales pitch)
Market insight → Monthly intelligence digest for the team
This is a market intelligence play, not a lead generation play. You’re capturing what the market is saying to inform your marketing — not identifying individuals behind anonymous posts.
Output: A continuously updated competitive and market intelligence feed that runs on autopilot. Monthly digests with top competitor complaints, trending pain points, and content topics the market is actively asking about.
Play 6: Partnership and Co-Marketing Discovery
Marketing function: Partnerships / BD
Difficulty: 3/5
“Who should we partner with?” is a question every marketer asks. Nobody has a system to answer it. You scroll LinkedIn, think of companies your customers also use, ask around, and hope someone has a warm intro. You end up partnering with whoever said yes, not whoever would be the best fit.
The real question isn’t “who should we partner with?” — it’s “who has our audience but doesn’t compete with us?” That’s a data question.
The play: Start with a real data source — account overlap from Crossbeam (which companies share customers with you?), AI lookalikes from Ocean.io (which companies serve the same buyer in adjacent categories?), or tech stack matches from BuiltWith (whose customers use similar tools?).
Import candidates into Clay and enrich with compatibility signals: Are they actively marketing (blog, newsletter, webinars)? What’s their audience size and social presence? Are they a similar company stage? Use Claygent to visit their website and assess their marketing activity level.
Score by partnership compatibility — audience overlap, complementary offering, size match, marketing activity level — and generate personalized co-marketing pitches for the top-scoring candidates. Not “let’s partner” but a specific idea: “Let’s co-create a benchmark report on [shared topic] — your analytics audience and our automation audience would both benefit.”
Output: A scored partner list built from real data, not guesswork, with pitches ready to send.
Play 7: Programmatic Personalized Landing Pages
Marketing function: Content / ABM
Difficulty: 4/5
“Personalized landing pages” has become meaningless. Most teams swap the company name and logo on a template and call it personalization. “Welcome, Acme Corp!” and then the same page for every visitor. Nobody falls for it.
Real personalization means different messaging for different accounts — industry-specific value props, relevant case studies, company-specific challenges, tailored CTAs. But creating truly personalized pages is brutal at scale. 50 target accounts × 1 custom page each = 50 pages nobody has time to write.
The play: Start with your target account list in Clay. Enrich with company data and use Claygent to research each account’s likely business challenge (from job postings, recent news, public strategy signals). Then generate page copy per account — headline, value proposition, case study match, and CTA — all tailored to that account’s situation.
Push everything to Webflow’s CMS using Clay’s native integration. One page template in Webflow with dynamic fields. Clay populates the fields differently per account. Each gets a unique URL: yoursite.com/for/[company-name].
Use these pages across channels — ABM campaigns, event invitations, partnership proposals, outbound sequences. Track per-page engagement and alert your team when accounts show high interest.
Output: 50+ landing pages where the content actually IS different. Not “Hello {company_name}” mail merge. Real relevance — a fintech company sees a compliance-focused value prop and a finserv case study, while a SaaS company sees a scaling-focused message with a matching case study.
Play 8: Podcast and Speaker Pitch Lists
Marketing function: PR / Business Development
Difficulty: 2/5
Podcast guesting is one of the most underrated marketing channels. One good appearance puts you in front of a captive audience for 30-60 minutes. No other channel gives you that kind of attention.
But podcast outreach is 95% research and 5% pitching. Find a podcast. Check if it’s still active. Find the host. Find their email. Listen to an episode. Write a pitch. At that pace, you pitch 5 podcasts a week if you’re dedicated.
The play: Start with a real podcast database — Listen Notes has 3.7M+ indexed shows searchable by topic, with structured data on host, episode count, and popularity. Export to CSV and import into Clay. Then use Claygent to research each podcast’s website — host names, guest booking pages, recent episode topics, typical guest caliber. Use enrichment providers (Apollo, Hunter, Findymail) to find host emails.
Score by topic relevance, guest caliber match (do they host people at your level?), recency (active vs. dormant), audience signal, and contact availability. For every podcast above threshold, generate a personalized pitch that references their specific recent episodes and proposes 2-3 concrete topic ideas.
Output: 200 podcasts researched, scored, and pitched in the time it takes to manually research 10. Each pitch references the host’s actual content, not a generic “I’d love to be on your show.”
Where to Start
Unlike ABM plays that build on each other, these marketing plays are independent. You don’t need Play 1 to run Play 4. Pick the ones that match your biggest pain:
Spending too much on events with weak follow-up? Start with Play 3.
Newsletter engagement is flat? Start with Play 1.
No idea what competitors are saying in their ads? Start with Play 2.
Need influencers but can’t find the right ones? Start with Play 4.
My recommended order: Start with Newsletter Intelligence + Competitive Ads (week 1 — fastest to build, you already have the data). Then move to Event Intelligence + Influencer Vetting (week 2-3 — high-ROI plays affecting big budget lines). Add Community Intel + Partnerships (week 4-5 — signal plays that compound over time). Then tackle Landing Pages + Podcasts when you’re ready for more complex builds.
There are also natural synergies between the plays — community intelligence (Play 5) reveals pain points that inform your competitive positioning (Play 2), which feeds your personalized landing pages (Play 7). Event attendees (Play 3) enrich your newsletter intelligence (Play 1). Influencer vetting (Play 4) surfaces creators who also make great podcast guests (Play 8).
Start with 2-3 plays. Build the muscle. Add more as you see results.
And do it with patience and love. Some marketers might be a bit overwhelmed at first - set them up for success - double down on what is already working well for them and extract leads from that. Help them help you should be the guiding principle here. They are not “less likely to understand our tools” - they are just 2 years behind in adopting them, and they can catch up really fast. I’ve seen it work. Hope you’ll do it too
For the full implementation guide with step-by-step instructions, Clay prompts, scoring formulas, and integration details for all 8 plays, grab the complete playbook here.
If you like what I do, you can find more of such assets, playbooks, workshops, and awesome examples on my 100-Step GTM checklist.
