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Edition #53 | Published Jan 12, 2026 Vibe coding, popularized by tech leaders in early 2025, describes using AI to generate software by simply describing the desired vibe or outcome, rather than writing code. Now, marketers have their own version of this trend: vibe marketing. Just as vibe coding lets developers create apps from natural-language prompts, vibe marketing uses AI and no-code tools to craft campaigns and programs. This approach is gaining serious traction. Even new startups are  hiring “Vibe Marketers”  with salaries up to $1 million. This week, there are also more signals that matter for GTM teams. I am tracking them so you can move fast without  breaking trust. Let’s get into them. 👉  🚀 The Pulse: Industry News You Can’t Afford to Miss We read the AI x ABM headlines so you don’t have to.  Tiny teams + AI agents are becoming a credible operating model  Business Insider ’s VC trend read: “ tiny teams ” enabled by personalized agents and automation are becoming the trend in 2026. More bloated and over-complicated marketing departments will be replaced by more lean, fast, AI-augmented individuals. Our take: This mirrors what we saw across our most-read insights in 2025: AI is now doing two distinct jobs in ABM — relevance for known accounts, and prioritization for in-market ones (recapped in Best of NextGenABM in 2025 ). Demandbase is getting more “programmable” (and more buying-group native) Their December 2025 Product Update  is a big one for ABM operators: Buying Group data via Export API , more BG intelligence fields for segmentation, plus multiple agent features (including an Email Agent  and an Intent Agent for keyword set generation).  Our take: It’s getting easier to push buying-group context into your CRM + ABM orchestrations.  The agent hype is real… but trust is the constraint Zapier recently released survey findings showing 84% of enterprise GTM leaders plan to increase AI agent investment , while still preferring human-in-the-loop  approaches - security + privacy remain the biggest adoption brakes.  Our take: This maps directly to ABM: autonomy is rising, but approvals + audit trails will decide what gets executed.  🎙 Voices of Influence: The Rise of Vibe Marketing (and why marketing leaders should care) Vibe coding let developers ship apps from prompts - now marketers are doing the same. Vibe marketing  is what happens when AI + no-code turns plain-English ideas into live campaigns  faster than traditional teams and stacks can keep up.  For Demand Gen / ABM marketers, this is implying a new operating model : Named accounts:  you can spin up hyper-relevant plays (ads, landing pages, sequences) in days — and iterate  weekly based on real account signals.  In-market accounts:  you can run more “micro-tests” (messaging, segments, offers) and let signals pick winners  before you scale.  The risk:  governance, data hygiene, and guardrails should be set up up front.  Below is an experiment I ran on Make - a well-known no-code automation platform . I created an automation to monitor a Facebook page’s social engagement. It sent email alerts using OpenAI GPT. I could automatically track updates and receive insights in my inbox. If you want the full breakdown (plus the tools I tested and what I’d change in your stack), I published the full POV on MarTech :  👉  https://martech.org/the-rise-of-vibe-marketing-and-what-it-means-for-marketers/ ABM is your go-to-market motion, not just a marketing function.  🧠 Ready to revamp your strategy? Check out our past editions  or let’s chat . 🎯 Until next time—stay bold, stay targeted.  📩 Subscribe here  | More insights for you

What This Year Taught Us About AI, ABM, and Modern GTM This year, the most-read and most-shared pieces on NextGenABM all pointed to the same shift: Using AI for hyper-personalization and relevance with known, named accounts, and using AI for smarter prioritization and targeting of new, in-market accounts. Below is a look back at the posts that resonated most with our community of B2B marketers, revenue leaders, and marketing practitioners. Consider this a tour through the year’s top insights , and a glimpse at how they’re setting the stage for marketing innovation in 2026. The Big Theme of 2025: AI Split ABM Into Two Main Jobs Across every high-performing article this year, a consistent pattern emerged: AI in ABM matured into two distinct (but connected) use cases: Hyper-relevance for named known accounts: Personalization/relevance, buying-group engagement, and contextual + multi-threads messaging at the account level. AI-powered prioritization for in-market new accounts : Using signals, intent, and behavior to decide who deserves focus, and pro-actively prioritize engagements. The posts below map directly to that evolution. 🔥 Top NextGenABM Insights of 2025 Below are the top NextGenABM Insights of 2025 From Automation to Agents: What Modern Marketing Is Doing Differently One standout theme was the shift from static automation to dynamic AI agents in marketing. Why it resonated: Many “AI marketing” tools still behaved like automation with better copy. This article drew a clear line between rule-based automation  and agentic systems  that can reason, decide, and act. For example, instead of waiting on weekly reports, an AI agent can flag underperforming accounts or ads mid-campaign and reallocate budget in real time. Key takeaway: This shift to AI-driven, always-on campaign agents was a huge talking point in 2025, marking the beginning of a more autonomous era for ABM. → See how agentic GTM is taking shape The Composable, AI-Ready Marketing Stack Another top post this year tackled the technology foundation needed for all this AI magic. “Is Your Marketing Stack Truly Composable – and AI-Ready?”  struck a chord with readers by addressing a critical behind-the-scenes trend: modular, composable tech stacks  became the backbone of next-gen GTM. Why it resonated: As AI accelerated, rigid “all-in-one” stacks started to crack. The most effective teams weren’t adding more tools, they were re-architecting around a composable, CRM-centric spine  that allowed signals to flow freely across systems. Key takeaway: AI doesn’t thrive in closed systems. Composability  is what makes AI usable in real GTM execution.→ Read the full post on building AI-ready stacks Relevance Beats Personalization: Key Playbook Takeaways from HubSpot INBOUND At HubSpot’s INBOUND 2025 conference, one message rang loud and clear: relevance is the new personalization . Our September recap, “Relevance Beats Personalization: Key Playbook & Takeaways from INBOUND ’25,” captured this strategic shift. Why it resonated: Personalization alone didn’t move deals. Relevance did. The strongest GTM programs in 2025 focused less on surface-level personalization and more on timing, context, and decision-stage alignment . Key takeaway: Being relevant at the right moment beats being personalized at the wrong one — every time.→ Explore the relevance-first ABM playbook Marketing in the Age of AEO: How to Become the Trusted Voice Buyers See First One of the most engaged posts of the year — especially among content and demand leaders. Why it resonated: Search behavior changed fast in 2025. Buyers increasingly encountered answers before brands. This article reframed content as something that must be quotable, citable, and credible , which is crucial for today's ABM (and marketing) successes. Key takeaway: ABM-effective content now competes to be the source that are visible and trusted , not just the page buyers land on.→ Read how AEO and ABM intersect How AI and Silent Buyers Are Reshaping ABM This one reframed the game: you’re not only influencing humans — you’re influencing the systems they trust. Why it resonated: Because “dark funnel” isn’t a buzzword anymore. Buyers self-educate through communities, reviews, and AI summaries long before sales gets a signal.   Key takeaway: Modern ABM = algorithmic influence + trust infrastructure (reviews, peer proof, AI-readable content),  not just targeting.  → Read about our research on Silent Buyers   Mastering Full-Funnel ABM in an AI-Led Buyer Journey A strong “systems > campaigns” piece — built for people running real pipeline. Why it resonated: Because buying groups don’t convert from one touch. Teams need always-on influence across channels, not one-off bursts. Key takeaway: Full-funnel ABM is orchestration: the right message, distributed well, at the right moment — repeatedly. → Read Full-Funnel ABM Next Gen ABM Speed vs. Context: The Pitfalls of Over-AI in B2B Marketing One of the most “needed” reality-check posts of the year — especially for teams racing to automate everything. Why it resonated: Because AI speed is seductive, but “fast + generic” can quietly kill relevance, trust, and reply rates. Key takeaway: Let AI do the heavy lifting (research, drafts, scoring) — but keep humans accountable for nuance, compliance, and the final “should we push send?” decision. → Read Speed vs. Context  Gated or Ungated? Your Content Strategy Could Make or Break Pipeline A surprisingly strategic topic and super relevant in an AI-shaped buyer journey. Why it resonated: Because gating isn’t just conversion math anymore, it’s a discoverability + authority decision when AI can’t “see” what’s behind forms. Key takeaway: Gate fewer assets, but make them count. Optimize the rest for reach, credibility, and “quotable” value that travels. → Read more insighnts about Gated vs. Ungated  CustomGPTs in the Wild: Real-World Lessons from the AI x GTM Frontier A “show me the receipts” post on what GPTs look like when they actually ship into GTM. Why it resonated: Because everyone talks about Custom GPTs — fewer talk about GTM logic, guardrails, and operational deployment in real marketing. Key takeaway: The unlock isn’t “build a GPT.” It’s “teach it your GTM rules,” then manage it like a junior teammate with tight feedback loops. → Read CustomGPTs in the Wild From Ghosted to Closed: Your Year-End Pipeline Revival Playbook Every revenue team knows the end-of-year scramble to revive stalled deals, and this playbook injected fresh ideas fueled by AI and creativity. The core message was optimistic: those deals that “ghosted” you over the year aren’t dead; they’re just waiting for a smarter re-entry. Why it resonated: Instead of chasing net-new leads late in the year, teams focused on reviving stalled but high-intent accounts using AI signals, exec thought leadership, and lightweight pilots. Key takeaway: Stalled opportunities aren’t dead. With the right signal and re-entry, they’re often the fastest path to revenue.→ Read the scrappy revival playbook A Pattern Worth Noticing Looking across the most-read posts of 2025, a few truths stand out: AI changed the operating model Buyers changed how they discover and decide ABM evolved into prioritization + relevance Execution became signal-driven and human-amplified This is where ABM quietly evolved from a framework into an operating system . Looking Ahead to 2026: Enter the Era of “Vibe Marketing” in ABM In 2026, expect to see: ABM programs powered by agents Fewer named accounts - but deeper buying-group coverage and influence Signal-driven orchestration replacing static nurture tracks Vibe marketing becoming the default : more micro-campaigns on the fly , fast experiments, human POVs, AI-assisted execution. If 2025 was the year AI reshaped ABM, 2026 will be the year teams separate signal from noise. Founder's Closing Thoughts Thank you for learning and innovating with us through this transformative year. Here’s to staying bold, staying targeted, and embracing the next wave of marketing evolution. Stay tuned for fresh insights and strategies in the new year – and if you haven’t already, subscribe to NextGenABM to ride the forefront of the marketing innovation.

I recently published an article on  HubSpot’s marketing blog  — and the response has been energizing. For those of you who follow my work in AI x ABM/GTM Brief and Insights, this piece ( HubSpot Blog )  dives into one of the biggest questions I’m hearing from enterprise B2B teams:  Can you still run effective ABM for complex, multi-product Fortune 500 IT buyers - without breaking your ops team or budget? My answer? Yes —  if  you plan intentionally and automate intelligently. In my new article featured on  HubSpot , I shared what  modern ABM orchestration  looks like when powered by  real-time data and AI . Traditional firmographic- and technographic- based ABM falls short in today’s landscape, because:  🧩 Budgets are shifting constantly 🧩 Buying committees are across LOBs 🧩 Speed of signal processing matters more than just static “ICPs" That’s why my latest work focuses on  signal-layer orchestration , not just persona targeting. The Framework I Cover in the HubSpot Article - From Manual to AI-Powered ABM Orchestration Account intelligence & unified view   Buying‑committee mapping   Multi‑channel orchestration   Personalized engagement & content   Unified analytics   Plus, some practical extensions I’m testing:  signal‑layer orchestration, composable tool stacks, etc. 👉  Read the full article on HubSpot Blog Bonus Insight (not in the article) What I’m seeing in marketing is a shift toward: Programmatic intent-based tiering GTM signals as triggers  (not just filters) AI-based orchestration and contextualized personalization at scale All of these above require a  solid data and tracking foundation .  Rome wasn't built in a day.  I’m running these playbooks across live campaigns right now. The best results come when marketing  don’t just run campaigns - they build systems that solve buyer problems and scale growth . ABM is your go-to-market motion, not a marketing function. 🧠 Ready to revamp your strategy? Check out our  past editions  or let’s  chat . 🎯 Until next time—stay bold, stay targeted. 📩  Subscribe here  |  More insights for you

I recently contributed an article to the HubSpot Blog exploring how workflow automation has evolved — and why it’s becoming a core capability for modern marketing, RevOps, and GTM teams. The piece, “Modern Marketing Workflow Automation Explained: What It Is and the Best Workflow Software to Use,” breaks down: What workflow automation really means in today’s B2B environment How it differs from traditional marketing automation Common workflow use cases across marketing, sales, and operations A practical overview of leading workflow automation tools The goal of the article is to help teams move beyond manual, one-off processes and understand how workflows can be used to orchestrate actions, improve prioritization, and support scalable growth . 👉 Read the full article on HubSpot: Modern Workflow Automation Explained: What It Is and the Best Workflow Software to Use At NextGenABM , workflow automation is a foundational layer of how I help B2B teams operationalize GTM strategy — whether that’s enabling faster speed-to-lead, cleaner lifecycle management, or more coordinated account-based execution. Being featured on HubSpot reflects the growing importance of workflow automation as not just an efficiency tool, but a strategic lever for modern revenue teams .

Edition #51 | Published Nov 5, 2025 Deals that ghosted you aren’t dead — they’re just waiting for a smarter re-entry . This issue unpacks how top GTM teams are reviving stalled opps before year-end using signals, exec thought leadership, and lightweight pilots. Let’s get into it. 👉  🎙 Voices of Influence: Year End Pipeline Revival Strategy 🚀 The Pulse: Industry News You Can’t Afford to Miss We read the AI x ABM headlines so you don’t have to.  Bulk Email Crackdown = Full-funnel ABM Opportunity Cold email is getting even more headwinds in this upcoming  holiday season - new sender rules  are pushing marketers and SDRs to adopt multi-channel full-funnel ABM strategies. As Natalie Jackson (Director of Demand Gen at CBIZ) notes, "Email can’t live in a silo anymore. If marketers don’t have visibility into sales engagement, we’re limiting our ability to drive revenue." HubSpot Release New Research on Prospecting  New research  reveals a crucial shift in late-funnel behavior: when buyers say, “We need to think about it,”  only 11%  of leaders recommend more social proof — instead, 52%  advise probing directly for the real concern - "What specific aspects do you need to think through?".  Strategy:  move social proof upstream  (intent-based storytelling), and use AI orchestration mid-funnel to detect hesitation drivers, before “We’ll think about it” stalls your pipeline. Founder’s Insights - SaaS Benchmark Report by High Alpha High Alpah’s newly released Saas-benchmarks  highlighted a few interesting founder insights -  time to raise for the vast majority of respondents was between 1-6 months while a significant portion of founders spoke with fewer than 50 investors. Having more founders boosts early momentum, but solo founder companies tend to operate more efficiently, based on their survey.  Founder’s Insights - SaaS Prices Are Surging, and It’s Reshaping GTM From HubSpot to 6sense, many major GTM vendors are hiking prices. Budget constraints are now a core objection that renewal is facing. Brands can expect stronger pushback in late-stage cycles and more demand for ROI justification. SaaStr Breakdown → Zapier Drops “Human-in-the-Loop” Framework Zapier’s latest “ Human in the Loop ” puts AI agents on the frontline but with a controlled fallback to human review . Think of it as smart automation with a safety net. I believe this is a compelling model for GTM teams experimenting with AI agents without risking rogue outreach Clay Launches Web Intent: Watch Buyer Research in Real-Time Real-time website intent is becoming the new gold standard for programmatic ABM. Clay's new Web Intent  feature lets you monitor which pages (on your site or competitors’) are visited by target accounts . Signals are enriched and matched to contacts  within your CRM. HubSpot to Acquire XFunnel XFunnel’s cross-channel data stitching + HubSpot’s AI push = the makings of a serious ABM signal orchestration  contender. Official Announcement → 🎙 Voices of Influence: EOY Pipeline Revival Playbook Many B2B deals stall mid-journey (timing, budget, internal friction). Here’s the good news — those accounts aren’t dead. And with the right nudge, they’re your warmest path to Q4 quick wins. This week, I’m sharing a quick, practical play to bring high-intent (but stalled) opps back to life.You ’ve already done the hard part — discovery, alignment, access. Now it’s about reconnecting with the right signal at the right moment . Scroll for the EOY Pipeline Revival Playbook 👇 Why this works Most B2B deals stall mid-journey (timing, budget, internal friction). Q4 is prime time to revisit with fresh proof and a simpler ROI story. Buying groups are big (often 10+ contacts for large deals). Revival means re-engaging across roles  with relevance. Phase What  Tools 1 Pull stalled & closed-lost opps, enrich contacts & recent signals, rank by Fit × Signal Recency × Deal Size  (>$ is tie-breaker), top 50-100 only  CRM, Clay, Sheet 2 Identify the “why now”  reasons per account (exec or super user changes, current competitor contract up for renewal, market news, competitor M & A, engagement surge, etc. ) Claygent, Sales Nav, analytics 3 Draft Thought Leader Ads  from an exec + two emails using the Claygent “why-now” signals + HubSpot’s AI emails tools   E1 “What changed”  (using ““why now” signals”)  E2 “here’s the exact piece that fixes X”  (30s short video)   This play pairs well with our earlier edition on becoming the trusted voice buyers cite first  — the foundation for any revival strategy. Claygent → HubSpot  4 Pick one offer : micro-pilot | exec briefing | audit/diagnose, depending on the reasons why they get stalled / closed lost  5 Validate the routing is working: [defined engagement actions] → Slack alert + task  Zapier/Make, HubSpot, Slack 6 Launch E1  + exec post; optional LinkedIn Thought Leadership Ads to boost the exec post to the “Matched Audiences”  Email, LinkedIn 7 SDR/AE calls to signaled  accts; open with “why now + objection + outcome” Sales Engagement Tool, CRM  8 Send E2  only to engaged ones; include single, specific CTA Email  9 Branch: Move “hot” to Revival Live for sales actions; park silent ones to a light January nurture Re-engaged accts ≥ 35%  | Meetings per acct 10–15%   CRM views, Sheet 🔥 What’s Trending in AI Shifts  Engineering headcount reductions due to AI  are significantly higher than any other department. Back office functions like Finance, HR, and IT have been less impacted by reductions at this point. Other top impacted functions are customer success & support, and marketing.  SaaStr reports that SaaS pricing is up about 11.4% year-over-year  - nearly five times general inflation —> budget pressure and vendor leverage is increasingly high.  🚀 GTM Startups to Watch AirOps  ( $40M Series B in November ): help brands to compete in AI Search 🛠 Martech Spotlight: Cool Tools & Innovations Nimo  (unifies all your AI workflows in one infinite canvas) - I have personally signed up for using it and find its your “AI Orchestrator” value prop really compelling to me 📚 Knowledge Vault: Must-Reads for ABM Operators “ Doing B2B Account Scoring the Right Way ” from Demandbase outlines how to build actionable account‑scoring models that tie directly to sales workflows B2B and AI Trends for 2026 and Beyond  - Webinar from DemandGenReports is available on-demand ⚡ Execution Tips & Tricks https://martech.org/how-to-turn-internal-docs-into-content-that-converts/  - When your company’s Slack channels were full of sharp debates about industry trends and best practices, consider turning them into content that can convert  by Stephanie Trovato Create a smart customer support chatbot that retrieves knowledge from your documentation using Apify and stores it in Zapier Tables connected to Zapier’s chatbot, instead of expensive third-party apps.  Revisit our INBOUND edition for practical ways to boost message-market fit through relevance-first sequencing . 🎤 AI x Marketing Insider: Events We’re Attending This Week Zapier x Apify: Building AI Agents Webinar 6sense Breakthrough MarTech Fall Virtual Conference 💬 Quote of the Week “If you want more replies, stop asking, ‘Have you heard of us?’ Start asking, ‘What would make spending time with us valuable  — even if they don’t buy?’” – Seen in B2B Whales Need more credibility in your revival plays? Our earlier edition on Voices That Convert   explores how expert proof drives late-stage confidence.  ABM is your go-to-market motion, not a marketing function.  🧠 Ready to revamp your strategy? Check out our past editions  or let’s chat . 🎯 Until next time—stay bold, stay targeted.  📩 Subscribe here  | More insights for you

Edition #49 | Published October 20, 2025 What truly separates agentic marketing from traditional marketing automation?  While many AI tools today feel like smarter versions of automation: automating workflows, scheduling messages, or scoring leads/accounts, the real shift is deeper. In automation , rules are predefined, and the system reacts based on your setup. In agentic marketing , your AI agent thinks, proactively decides what to do next, and drives the next steps, without needing every action scripted in advance. This week’s edition explores the shift from reactive automation to proactive AI agents that co-pilot campaigns, qualify buying groups, and personalize engagement in real-time.  You’ll see how Clay  is unlocking signal-based conversations, how Zapier’s AI teammates  are automating next-step logic, and why more teams are adopting agent-led growth. Let’s get into it. 👉  🚀 The Pulse: Industry News You Can’t Afford to Miss We read the AI x ABM headlines so you don’t have to.  🌟 ZapConnect 2025: AI Agents Go Mainstream Zapier's recently resumed flagship conference ZapConnect 2025  made it clear: AI is an embedded teammate. Top 5 AI takeaways from ZapConnect: AI is a Connector : AI wins when it's integrated across your CRM, email, and ops. No-code AI building  is now table stakes for marketers.  Human-in-the-loop governance  is critical for bot adoption. Watch the session: Create AI Teammates in Minutes with Zapier Agents 📊 New from Demandbase: AI x ABM - The Marketer’s AI Playbook At DemandGenReports’s recent "AI Meets ABM," Demandbase laid out how AI assistants can: Real-Time Campaign Optimization : AI-powered analytics can identify underperforming campaign elements in real-time , allowing marketers to adjust budgets and focus on high-performing channels and segments mid-campaign , reducing waste and improving ROI. AI as a Marketer's Sidekick : Marketers can leverage AI assistants to automate daily tasks, answer questions, and provide support, freeing them to focus on strategic and creative work. Watch on demand: AI Meets ABM: The Marketer's Playbook 🔊 Clay: Turn Conversations Into Competitive Intelligence Clay's new playbook  unlocks structured insights  from unstructured conversations. Think: buyer objections, decision signals, and competitor mentions pulled from call transcripts and routed directly into your GTM workflows. 🔄 MarTech x Snowflake: Why Data Gravity Now Shapes Martech Stacks Per Snowflake’s newly published Modern Marketing Data Stack , the marketing landscape is being reshaped by three powerful forces: AI, data gravity, and privacy . A composable, privacy-forward, AI-enabled stack is a strategic moat.  🎙 Voices of Influence: From Automation to Agents: What Modern Marketing Looks Like Now Most marketers still think of AI as advanced automation - segmenting leads, scoring accounts, alerting sales, etc. But that’s only the first inning. The real transformation begins when AI stops simply automating tasks and starts acting as an agent  — making decisions, prioritizing efforts, and driving actions autonomously, in real time.  Here are 3 key shifts that are happening in modern marketing:  1. From Reactive Automation → Proactive Agents  Instead of waiting for quarterly reports to adjust spend, AI agents can flag underperforming audiences or accounts in your campaign mid-flight . Imagine knowing by Tuesday which accounts to pause targeting on — before wasting another cent in programmatic or paid social. This is campaign optimization that thinks ahead .  2. From Lead Volume → Pipeline Precision The best teams are already moving from generic MQLs to AI-prioritized buying groups. Using intent signals, firmographics , and behavioral context , agents can surface net-new lookalike accounts   and  rank existing ones based on true revenue potential.  3. From “Personalized” Content → Truly Contextual Touchpoints The word “personalization” is overused, until you see what AI agents can actually do. From auto-generating asset variants  for different roles and industries, to creating contextualized personalized emails at scale today, to producing low friction video intros at scale.  Thus, the central differentiator of an AI agent vs. automation is autonomy,  the ability to make decisions and take action 🔥 What’s Trending in AI Shifts  OpenAI Introduces Apps in ChatGPT : Native apps now flow within ChatGPT conversations .My previous breakdown: How ChatGPT Search Reshapes the B2B Buyer’s Journey   Paid AI Adoption in Startups Drops Again in September : September marked the second decline in paid AI adoption among startups, per Ramp AI Index .  Why AI Agents Will Be The Death of the B Player.  In almost every category, according to SaaStr  founder  🚀 GTM Startups to Watch Dreamdata  raised US $55 million Series B  on October 14, 2025 , to scale its B2B marketing analytics platform that unifies ads, website, CRM and email data into actionable workflows. 🛠 Martech Spotlight: Cool Tools & Innovations BlackBox AI :  Originally built for devs, now expanding into marketing. Their AI autocomplete helps teams repurpose past content and generate net-new assets  with context retention. Check it out!  Clay’s Sculptor and Web Intent  tools: Sculptor  lets you build workflows via natural language prompts Web Intent  tracks anonymous web visits, scores them, and alerts reps when the timing's right 📚 Knowledge Vault: Must-Reads for ABM Operators AI Meets ABM: What's Actually Working vs. What's Hype :   Insight into how Demandbase’s SVP of Demand Gen is turning AI into a force multiplier of ABM  SaaStr’s Agentic GTM Playbook : Practical sessions on building AI SDRs, GTM co-pilots, and orchestration layers. My favorite one is How to Build AI SDRs to Convert More Inbound Pipeline. Watch the GTM replays Zapier: Building an AI-first GTM Team  Read the blueprint .  ⚡ Execution Tips & Tricks Best-in-class teams start with a clear use case before sourcing AI tools. Once an addressable use case has been identified, only then have they started evaluating and sourcing different AI tools. - Source: Alicia Hale (SVP of Growth Marketing), Demandbase .  To get AI to help identify and remove bias , provide clear context about its role, perspective, and specific lens to analyze content, allowing it to flag potential inconsistencies and create more objective evaluation frameworks. By doing so, you can leverage AI's analytical power to uncover blind spots and mitigate bias in decision-making processes. - Source: Inclusive marketer — and former master in marketing  — Sonia Thompson 🎤 AI x Marketing Insider: Events We’re Attending AI Decisioning 101: 1:1 Personalization at Scale TechWeek LA Harnessing AI to Drive Go-to-Market Impact  💬 Quote of the Week “85% of what you do should be templatized, refined — checking the boxes of your strategic marketing plan,” she says. “And if you're a marketing leader, you should give your team 15% of that work to play with.” - Bryetta Calloway, Founder and CEO, Stories Seen , first seen in Hubspot Marketing Blog ABM is your go-to-market motion, not a marketing function.  🧠 Ready to revamp your strategy? Check out our past editions  or let’s chat . 🎯 Until next time—stay bold, stay targeted.  📩 Subscribe here  | More insights for you

Edition #48 | Published October 6, 2025 The way B2B buyers discover, evaluate, and trust vendors has changed in the AI-powered GTM landscape. Brands are competing to be the source of truth and mentions  AI engines cite and decision-makers trust. To meet this moment, modern GTM teams are embracing a new mindset: Answer Engine Optimization (AEO) :  Lead with clarity (your TL;DR and FAQs are your new SEO). Publish data, tools, and PoV opinions AI can’t fake. Prioritize decision-stage frameworks over generic “what is” content. And activate your most powerful visibility engine : executive voices on LinkedIn . Because in an AI-shaped buyer journey, trust is earned by being useful, human, and everywhere that matters — especially in zero-click moments. 👉 In this week’s issue, we break down how leading GTM teams are adapting their content, campaigns, and leadership messaging to win in this new era, plus all the latest AI, Marketing, ABM news, tools, and strategy shifts you can’t afford to miss. 🚀 The Pulse: Industry News You Can’t Afford to Miss We read the AI x ABM headlines so you don’t have to. G2’s 2025 Buyer Behavior Report: AI chatbots now #1 influence on vendor shortlists In a survey of 1,100 decision-makers, chatbots have overtaken traditional channels  in shortlisting influence. Also, 50% of enterprise buyers report having switched vendors for superior AI functionality. Demandbase Joins Salesforce Agentforce with Native AI Prospecting Agent Demandbase just launched its first Salesforce-native agent inside the Agentforce ecosystem  — the Demandbase Agentforce Prospecting Agent . It brings Prescriptive Sales Dashboard insights directly into rep workflows to reduce tool-switching and with guided workflows to prioritize high-fit accounts. Clay Announces Sculptor – Its New AI GTM Copilot At its annual conference, Clay launched Sculptor  — an AI copilot  designed to streamline everything from table builds to GTM play creation. It builds and refines Clay tables, recommends enrichments, answers questions like “Which ICP segments are underperforming?”, and provides instant insights, all via natural language prompts .  (Image Credits: Clay Website) DemandWorks × 6sense: New Native Integration for ABM  This newly announced partnership  connects 6sense buyer intelligence  (segments) with DemandWorks’ activation engine  for real-time, full-funnel execution (Trigger display ads, syndication, and 1:1 emails across verified buying committees).  (Image Credits: DemandWorks Website) Aviatrix CMO on automating 80% of marketing work using AI At Aviatrix, the marketing team has delegated 80% of their tasks  (content, video, analytics) to AI, freeing humans for strategic & creative work. This is a bold real-world test case of scale, featured by Business Insider in September.  🎙 Voices of Influence: Full Funnel Marketing in the Age of AEO Playbook For marketing in the Age of AEO, the next frontier of ABM is going to be about building authority and influence in the modern buyers journey powered by AI. Here’s how I’m helping clients adapt AEO for marketing: Strategy 1 - Win Zero‑click Moments Leading with clarity : start every high-value asset with a bold, quotable takeaway. Adding context : include FAQs, POVs, and data-backed statements AI can extract and summarize. Strategy 2 - Be the Sources  Generic "what is XYZ?" posts are now table stakes. AI can generate those in seconds. So instead, we focus on more expert level content that AI can’t hallucinate or invent easily:  Vendor selection frameworks Comparison guides with POV validated by SMEs Interactive tools (e.g., TCO calculators, maturity assessments work great!) Benchmarks that are created by 3rd party consultancies  Strategy 3 - Optimize for Intent  AI summaries are cutting traffic, so every click matters more  than ever. That’s why we place: Every high‑intent page leads with one clear CTA at the top (e.g. calculator, free audit, etc.)  Make sure the CTA is matching the buying stage of the prospect account (e.g. using HubSpot + Demandbase to personalize the experience at scale)  Strategy 4 - Executive Voice = ABM Amplifier The amplifier that often gets overlooked is the executive presence on LinkedIn . In the AI era, human voices still cut through. When doing it right, Executives’ posts tend to outperform brand posts in reach and trust, and they extend the life of your content far beyond search.  When working with founder-led sales teams, I align leadership posts with our broader content themes , encouraging leaders to share authentic, thought leader style insights once or twice a month. I also use tools like Clay and HubSpot’s new Data AI agent to monitor engagement from target accounts, making executive visibility and posts engagements a powerful GTM signals engine.  🔥 What’s Trending in AI Shifts  OpenAI : AI systems hallucinate because they're trained to always answer , even when they should just say “I don’t know”.  Executives on LinkedIn : It’s not optional anymore. Voice = Visibility 🚀 GTM Startups to Watch Centari  (an AI deal intelligence startup ) raised $14M Series A  on September, 2025 .  🛠 Martech Spotlight: Cool Tools & Innovations Latitude  – The 1st agent that builds agents. Your prompt -> Create the agents -> Connecting them to 2,500+ tools -> Deploying them into production.  HubSpot’s new Marketing Studio  (AI-powered campaign planning workspace) brings a Canva-style experience to B2B campaign planning. Build marketing campaigns in days, not months. I’m really excited about it!  📚 Knowledge Vault: Must-Reads for ABM Operators [Recorded] AI Meets ABM: What’s Working vs. What’s Hype Watch the ON24 session → Why AI Content Sounds the Same — and How to Fix It HubSpot’s breakdown → The Arrival of AI Browsers & the Future of Content Discovery for Demand Marketers MarTech.org report → ⚡ Execution Tips & Tricks Inspired by INsidea’s “ Top 7 RevOps Plays ”, here’s one I love: Build a cross-functional Customer Journey Map. It shows where deals stall, reveals what info buyers need and aligns campaigns to actual friction points.  Action Tips:  Map every key touchpoint: ad → SDR email → call → follow-up Overlay it with CRM data + VOC feedback Create micro-campaigns to unblock stuck roles (e.g., ROI tools for finance) 🎤 AI x Marketing Insider: Events We’re Attending Demandbase GO NYC – October 6 & 7 2025 Demand Gen Report: 2025 Strategy & Planning Series - Oct 27 - 29 HubSpot <> Claude Connector Webinar - Oct 16 To-Do List Summit - AI in GTM for Early Stage Founders - Nov 8 💬 Quote of the Week “Don’t mistake action for progress. Process beats panic. Diagnose systematically, change sparingly, and communicate clearly. Most turnarounds come from a steady core and a few small, well-aimed tests - not a total rebuild.” — Jonathan Bland , Co-founder at Omni Lab, 🎧 Source → Spotify ABM is your go-to-market motion, not a marketing function.  🧠 Ready to revamp your strategy? Check out our past editions  or let’s chat . 🎯 Until next time—stay bold, stay targeted.  📩 Subscribe here  | More insights for you

NextGenABM is excited to announce our official certification as a Salesloft Solution Partner , reinforcing our commitment to helping startups and scaling teams bridge the gap between marketing and sales. Salesloft is a leading platform for modern revenue orchestration, empowering teams to engage buyers with precision and consistency. As a certified partner, NextGenABM integrates Salesloft’s signal-based engagement capabilities into our fractional GTM programs - helping clients move from scattered outreach to synchronized, data-driven buyer journeys. “Many startups underutilize sales engagement tools in their demand generation mix,” said Océane Li, Founder of NextGenABM. “Our goal is to help them unlock Salesloft’s full potential — connecting outbound, inbound, and ABM plays into one seamless motion that drives measurable pipeline impact.” This partnership expands NextGenABM’s ability to deliver AI-powered, account-focused GTM execution for clients seeking to scale beyond founder-led sales. 📍 Explore our Salesloft Partner Listing: https://marketplace.salesloft.com/partners/nextgen-abm

By Océane Li | Founder, NextGenABM Edition #4 7  | Published September 15, 2025 After spending a week immersed in HubSpot’s INBOUND 25 , I left with a clear takeaway: in the age of AI-era go-to-market motions, relevance is the new personalization. If your idea of personalization is “Hi {FirstName},”"{CompanyName}", or similar, you’re already behind. Relevance today means building systems that anticipate intent and activate real-time context - before your team ever hits send. Let’s dive into how that played out across this year's INBOUND’s biggest stages, key sessions, and product reveals. 🧠 From Personalization to Contextual Relevance at Scale Why “just personalize it” no longer cuts it In my opinion, one of the sharpest strategic pivots at INBOUND 25 came from the concept of 1:1 relevance > personalization. In theory, anyone can personalize - drop in a first name, tweak a job title, feed in a static ICP, etc. But does that personalization really convert? Are they truly relevant to your buyers? Relevance requires DYNAMIC context, behavioral cues, and real-time buyer signals. In the session “ From Signals to Revenue , ” EJ Cho, the Co-founder and CEO of TOFU made the case for signal-based GTM : not just who your buyers are, but what they’re doing, when, and why it matters. ⚡ Some   real-life plays showed the difference: A job change + past power user = high-converting combo trigger High-intent web visitor de-anonymized → instant enrichment → agentic SDR outreach That theme continued in the “ AI Emails That Convert ” session, where HubSpot's Global Email Automation Director Ari Echt-Wilson, unveiled how it’s evolving beyond basic email personalization. ⚡ AI-Powered Email in HubSpot uses first-party data to craft contextual, behaviorally aware emails at scale. 🧬 How it works: Enroll a contact → Crawl their website → Ingest CRM + MAP signals → Send inputs to LLM → Output a personalized, relevant message. What stood out was not just the workflow, but the fact that it’s been tested for 18 months inside HubSpot’s own teams , resulting in deeper engagement, improved conversion, and more scalable outbound. Instead of “Hi {FirstName}, saw you work at {Company}...,” these AI-crafted emails reference recent behaviors, intent actions, CRM activity , and adjust the value prop accordingly. 🤖 Self-Generating Data: The Backbone of AI-Ready GTM You can’t scale relevance without signal-rich systems HubSpot’s product evolution this year centered on a major thesis: Loop-powered GTM = dynamic data context + AI orchestration + multi-channel activation. But none of that works if your CRM is dirty, fragmented, or blind to buyer signals. During the HubSpot Spotlight , Smart CRM stack - now infused with what they called “self-generating data" (captures the movement from data collection to dynamic enrichment ) was highlighted b y Karen Ng, EVP of Product at HubSpot. I consider this another major shift in this year's growth playbook in the AI-era. Why? Because AI may be everywhere now, but what distinguishes top-performing marketers isn’t how much AI they use but how well they train it  with first-party inputs, smart segmentation, and evolving ICP clarity. The marketers winning today are increasingly leveraging AI and tools to self-generate their own signal-rich data , activating it across every channel, and training their AI tools on brand voice, triggers, and workflows that scale relevance. 🧩 Some notable innovations that support this shift are: Smart CRM: Auto-enrich company + contact data, self-generating data using AI powered prompts using Data Agents or Smart Columns Data Hub (formerly Ops Hub): Connects data warehouse (e.g. Snowflack) / 1st-party product usage data, continuous dedupe, AI-powered continous enrichment without costing credits (yes, this one is pretty HUGE), etc. AI-Powered Email: 1:1 contextual emails built using CRM behaviors. Key takeaways: Your CRM needs to generate relevance signals, not just store records. First-party data is the fuel for relevance and orchestration, and marketers who own their signal pipelines will dominate . 📥 Agentic Funnels: When AI Doesn’t Just Assist From human capacity caused bottlenecks to always-on agents One of the boldest visions came from the " Agentic Funnel " track, which posed a provocative question: What if we have a SDR agent (that can do reasoning and act independently) working for marketing 24 hours 7 days? Maura Rivera, CMO of Qualified, showcased how agentic marketing workflows, powered by Breeze Agents - now qualify, enrich, and outreach without human intervention. 🔥 Key inspired use cases High-intent demo requests → AI books meetings instantly Follow up on leads who fills out high intent forms → invite for sales meeting Post-event leads → personalized 1:1 email follow-up via AI AI Agents for BDRs: Combine CRM + external data → detect GTM signals → trigger outreach Key reflections: This agentic model doesn’t replace human SDRs. Quite differently, it redefines capacity of your SDR team. It also changes the role of your demand generation and marketing ops - they are no longer just a workflow planner + builder, they become the trainer of agents. 🎯 From CRM Inputs to Full-Funnel Impact Your GTM flywheel is only as smart as the data you give it Several sessions stressed the same point: the AI GTM flywheel only spins when every part of your system is built for signal-based action. In “ Zero to Pipeline ,” we saw how Robyn Winner, CMO of Loop (an early stage AI supply chain startup), used HubSpot’s automation + enrichment + Slack integrations to successfully turn lean GTM teams into scalable revenue engines. In “Segmentation: Data + Marketing Hub United,” we saw how smart columns and spreadsheet-style workflows inside Data Hub made it easy to build segment views on the fly . And in “HubSpot Intent” teams could define their own intent thresholds, e.g., 3+ visits to a pricing page = MQL, feeding back into workflows and ad targeting. This signals a future where your marketing team owns the signal system end-to-end , not just relies on external vendors and endless external API calls. 🔁 HubSpot’s “Loop” GTM Framework: A New Growth Model Emerges Why the funnel is leaking—and how to build a LOOP instead At the heart of INBOUND was a transformative shift: the traditional funnel is leaking; the future is a LOOP. Instead of obsessing over conversion stages, marketers need to: Express who you are – define ICP, brand voice, and tone (train AI on this). Tailor messages – relevance (beyond just personalization) at scale, powered by CRM signals + AI. Amplify across channels – where buyers spend time (social, podcasts, newsletters, emails, etc.), not just on your website. Evolve in real-time – know what to measure and use AI to act faster (campaigns that adapt, re-engage, and surface across your buyer’s journey repeatedly) 🛠 Product updates supporting the LOOP: Marketing Studio (Beta): Drag-and-drop GTM asset orchestration. Content Hub AEO strategy: Optimized for AI discoverability + citations. AI Remix Tools: Take one video/image and repurpose it across channels. Breeze Marketplace: Deploy specialized AI agents for different GTM tasks. 🧭 Final INBOUND 25 Takeaway : Relevance Is the Real Differentiator After spending an intensive week in San Francisco with more than thousands of AI savvy marketers and sales leaders, I deeply believe what sets modern marketers apart isn’t whether they use AI, it’s how intentionally they train it, what data and signals they feed it, and how fast they evolve. Don’t just personalize - strategize your signals and operationalize true relevance. This is my top 1 actionable INBOUND 25 takeaway for you. ABM is your go-to-market motion, not a marketing function.  🧠 Ready to revamp your strategy? Check out our past editions  or let’s chat . 🎯 Until next time—stay bold, stay targeted.  📩 Subscribe here  | More insights for you

Edition #46 | Published September 2, 2025 Last week, we explored how peer reviews and SME voices are creating competitive advantages in AI-led GTM. This week, we zoom out to reveal a broader market shift: the move toward composable, AI-enabled GTM stacks  in marketing. Is Your Marketing Stack Truly Composable, and AI-Ready ?   We’re unpacking why this matters, how to lead with composable tools, and what’s powering high-performing GTM teams today.  🚀 The Pulse: Industry News You Shouldn’t Miss We read the latest AI x ABM news so you don’t have to. New Playbook Published: AI Meets ABM Demand Gen Report published a practical guide on weaving GenAI into targeting, orchestration, and personalization, which reveals the shift from static personas to behavior-driven signals . Worth a bookmark as you update your 2026 GTM plan.  Macro shift: AI search keeps gaining A fresh MarTech.org  research  shows Google’s share of general searches fell from 73% (Feb) to 66.9% (Aug) , while ChatGPT use nearly tripled. Pro  tips:  Optimize for Q&A and summaries  (clear headings, structured takeaways) and repurpose pillar posts into AI-friendly snippets. 6sense launches AI Email Agents to Personalize Outreach at Scale 6sense rolled out AI-generated, data-grounded emails  that pull from CRM + intent to personalize at scale, aimed at speeding first touch while staying on-brand.  LinkedIn expands Thought Leader Ads to Events You can now sponsor member posts  that link directly to a LinkedIn Event . This is a big step forward to blend more B2C strategies into B2B marketing. Pro tips:  Put your SME’s event post  in front of in-market accounts; pair with retargeting to boost lead gen leveraging LinkedIn influencer’s audiences.  LinkedIn doubles down on video for B2B Separately, LinkedIn expanded its BrandLink  video program with new creator-led series and sponsor slots, another push toward video as a demand channel  for decision-maker reach.  Demandbase Doubles Down on Custom APIs Big additions: Custom Actions  (HTTPS calls to any partner), Custom Integrations , LeanData routing automation from engagement signals, are highlighted in Demandbase’s newest release. 🎙 Voices of Influence: Is Your Marketing Stack Truly Composable—and AI-Ready? If AI is powering your GTM engine, composability is the chassis .  Industry leaders are moving away from “one-vendor does it all” toward modular, best-of-breed stacks  that stay flexible as AI evolves. Source   The teams winning now build around the CRM relationship graph  (accounts ↔ people ↔ opportunities), layer AI to interpret signals , and use orchestration  to turn those signals into actions - automatically and intelligently across channels. What leaders are saying:  Demandbase’s recent insights/updates  from Umberto Milletti ( Chief R&D Officer) also emphasize the importance of an open, composable  stack, so GTM signals can flow across tools in real time securely. That’s the architecture you want AI riding on.  Our Takeaways from an AI x Marketing perspective:  Your CRM capability is your moat.  Consider mapping power centers, influence paths, and white space in buying committee coverage, not just contacts and obvious titles.  Signals, signals, signals.  Use AI to turn messy multi-source data (intent, product usage, web, email, ads) into structured GTM signals, then use those signals to derive the next-best actions. Orchestration > channels.  Momentum comes from entry/exit criteria  and suppression logic—not blasting everything everywhere. Composable stacks make that sequencing possible.  Quick Self-Check: Is Your Stack “Composable Enough”? Can you swap parts  (e.g., enrichment or routing) without a rebuild?  Do signals travel quickly ? (Intent → CRM → routing → seller alert in minutes, not hours.)  Do you have open connectors  (APIs/webhooks) to push/pull account & people data across tools?  Do shared definitions  (fit × intent × engagement) drive one set of automations across systems?  Is CRM truly the spine ? (Clean associations: account ↔ buying group ↔ opportunity.) Here’s one example of a composable AI-ready B2B marketing stack: Layer Why it’s critical for AI-ready CRM Houses the relationship graph (accounts↔people↔opps) and the unique keys AI needs to join, trust, and act on data. CDP / Warehouse Centralizes clean, timestamped events for modeling and historical context for AI scoring and forecasting. Identity & Enrichment Adds firmographic/technographic precision so AI can judge fit and prioritize the right accounts/personas. Reverse ETL Operationalizes AI features/segments by pushing them back into tools in near-real time. Signal Scoring Converts noisy intent/behavior into fit × intent × engagement  scores Orchestration Turns scores into actions with entry/exit criteria, suppressions, and conflict rules—automation AI can trust. Activation (paid + owned + human) Delivers the right message/channel/seller step on trigger, where AI insights create revenue. AI / LLM Layer Summarizes context, drafts 1:1 outreach, and assists decisions via RAG/guardrails + human-in-the-loop. Measurement & Guardrails 🔦 Case Study We will be back next week 🔥 What’s Trending This Week 🎥 Meta just rolled out multi-language AI dubbing for video content , aiming to globalize creator reach, useful for repurposing expert videos across regions.This is great news for digital marketers!  🚀 Notable Funding Rounds in AI-Powered GTM Startups  Clay Raises $100M Series C at $3.1B Valuation Clay, a leading AI-powered GTM platform, secured $100M to scale its “GTM engineering” playbook across 10K+ customers. Source Cognition AI Scores $500M in Series C Cognition raised half a billion to advance its autonomous AI engineer agent "Devin." Source 🛠 Martech Spotlight: Cool Tools & Innovations 🚀 Claygent Navigator : Clay just released Navigator, a browser-based AI agent for “nested” data tasks: from prospect research to workflow assembly across CRM, LinkedIn, and more. ⚡ Trace.so : A no-code orchestration engine that routes GTM tasks to the right AI or human agent, based on tool integrations and context. Think Slack + Notion + JIRA meets RevOps automation. 📚 Knowledge Vault: Must-Reads for ABM Operators 🎧 Top ways to use Zapier MCP server and LLMs  by  Constance Chen 🎥 Zapier’s Guide to Vibe-Coded Revenue Ops 📊 Reddit’s B2B Webinar on Community-Led GTM ⚡ Execution Tips & Tricks Zapier + LLMs: Use Zapier’s MCP and local LLMs  to build modular GTM workflows, e.g. automating intent to action triggers across your tools. AI SDRs + CRM = Smart First Contact and Know When to Hand Off Seamless handoff to human SDRs  when conversations reach complexity thresholds. Salesforce CEO shares their practices  on how AI SDRs as the 1st qualification layer.  🎤 ABM Insider: Events We’re Attending AI Meets ABM: What’s Actually Working vs. What’s Hype: Wed, September 24, 2025 A straight-talk session on what to keep, cut, and re-compose in your stack so AI actually moves pipeline—not just decks. Register here → GTM Hot Takes Show — “No More MQLs”, Thu, September 4, 2025: Hot take meets hard data: if your stack’s composable and signal-driven, do you still need MQLs? We’ll dig in, live. Register → 💬 Quote of the Week We will be back next week ABM is your go-to-market motion, not a marketing function.  🧠 Ready to revamp your strategy? Check out our past editions  or let’s chat . 🎯 Until next time—stay bold, stay targeted.  📩 Subscribe here  | More insights for you

Edition #45 | Published August 18, 2025 Last week, we explored the balance between AI speed and human judgment  in marketing. This week, we’re zooming in on a lever that elevates both: peer reviews and SME-level voices / expert influences embedded across GTM motions. In a world increasingly driven by AI, gaining buyer trust still starts with human connection, and those authentic validation points are becoming distinct competitive assets.  This edition breaks down why that matters, how to plug it into AI x Marketing, and what we’re seeing in the field.  🚀 The Pulse: Industry News You Shouldn’t Miss We read the latest AI x ABM News so you don’t have to.  Demand Gen Report: 2025 Demand Generation Benchmark According to this newly released research, demand gen budgets are expanding - with 45%  of teams prioritizing ABM/ABX  and 41%  increasing spend on personalization . Teams are re-centering on lead quality , ops maturity , and revenue attribution . The top metrics remain as Opportunities generated, MQL/SAL conversion, and pipeline influence. Download the Survey G2: 2025 Buyer Behavior Report A massive shift is happening in SaaS buyer behavior . According to G2’s newly published research, 79% of enterprise buyers  now rely on AI or review platforms  as primary research sources, overshadowing traditional search. This underscores how vital third-party validation  and digital trust-building  have become. For SMB buyers, site reviews (38%) and AI (35%) are also key research sources.  HG Insights Launches Agentic GTM Ecosystem The new “ Revenue Growth Agentic Ecosystem ” blends AI agents with enriched market data (via TrustRadius) and relies on MadKubu ( an agentic GTM solution provider)  integration. This means teams can now activate GTM strategies automatically based on real-time signals. Madison Logic × ZoomInfo: ABM Meets Activation This new partnership bridges audience planning, contact intelligence, and activation  into one connected workflow.  The integration enables teams to identify in-market accounts faster and coordinate outreach across owned and paid channels — a strong signal of where modern ABM is heading. Demandbase Expands MAP Integration with Data Integrity Demandbase’s Data Integrity  is now available in Marketo, bringing real-time deduplication, enrichment, and data hygiene  directly into your MAP workflows. Powered by its MTV ( multi-sourced, triangulated, validated ) data approach, this update supports cleaner segmentation, more accurate scoring, and tighter downstream conversion.  🎙 Voices of Influence: How Expert Influence Still Win in 2025 AI-led GTM In a world where AI can churn out “content” faster than we can scroll, influence still comes from people. Trusted voices with a point of view build credibility, move markets, and open doors AI alone can’t. LinkedIn’s Thought Leader Ads put your execs, experts, and even customers at the center  of your paid + owned  strategy — then scale their reach with the precision targeting LinkedIn is known for. 🔦 Case Study: The Operational Reality of Building AI-First Revenue Team at SaaStr Jason Lemkin’s team at SaaStr have operationalized 10 AI agents  as core members of the revenue and operations engine - and the lessons are telling. AI agents excel in top-of-funnel lead handling, support, and scale, but human orchestration  is the real force multiplier. My key takeaways: AI agents aren’t “set‑and‑forget.” Every agent demands regular human oversight. Each morning, Jason’s team reviews performance metrics, edge‑case failures, and fine‑tunes training data.  These agents deliver what humans can’t, like zero turnover, weekend consistency, instant product knowledge, and uptime without burnout. In this case study, their lead qualification accuracy climbed by 67% , leading to $340K in sponsor pipeline generated in Q3 alone, which is pretty impressive!  Winners invest in AI‑Ops talent .  🔥 What’s Trending This Week “Vibe Coding” with GPT-5 is Ready for Marketers? Prototyping full-stack apps from a single prompt is promised by the launch , but mileage varies. Early hands-on reports show impressive speed  with uneven reliability for non-coders .  MIT’s study  flags neural, linguistic, and behavioral underperformance  with constant AI assistance. Also, see Zac Stucki ’s take on resisting “ disposable thinking. ” published on MarTech.  🚀Notable Funding Rounds in AI-Powered GTM Startups  (No additional updates in this cycle.) 🛠 Martech Spotlight: Cool Tools & Innovations Claygent + GPT-5 : GPT-5 becomes Clay’s default pick for messy web research , long docs, and nested navigation.  📚 Knowledge Vault: Must-Reads for ABM Operators Why AI Still Needs a Human Co-Pilot  - A Hubspot x GPT Case Study How to use vibe-coding to scale revenue teams  by Zapier (prompts that sound like you; consistent GTM messaging).  Video marketing assets  every SaaS needs - explainer hook, product demo, social proof  - to accelerate buying groups AI for Revenue Teams - Zapier’s Case Study on agentic workflows. ⚡ Execution Tips & Tricks for AI x ABM Success  Leaning on what you know may not get you what you need . Melissa Reeve ’s deep-research workflow  pulled non-obvious sources (Reddit, forums, review sites) that shaped sharper messaging and segmentation.   Over relying on job titles could be costly, instead of building buying persona based on titles and levels, segment them based on decision making roles . Like, Instead of building a persona for “VP of IT”, build one for the technical evaluator, the risk manager, and the champion.  🎤 ABM Insider: Events We’re Attending  📊 Data-Driven GTM Planning for 2026 Hosted by Demandbase🗓️ August 22, 2025 Register here → 🌐 Reddit Pro: Go-to-Market Tactics for B2B🗓️ August 21, 2025 Register here → 💡 RevGenius Live: AI + Community-Driven GTM🗓️ August 23, 2025 RSVP here → 💬 Quote of the Week “Visibility is the new north star. Content teams need to act like publishers—show up in more places, not just rank.” — Tom Mansell , VP Organic Performance, Crowd (Source: Marketing Dilemmas podcast ) ABM is your go-to-market motion, not a marketing function.  📩 Subscribe here  | More insights for you   🧠 Ready to revamp your strategy? Check out our past editions  or let’s chat . 🎯 Until next time—stay bold, stay targeted.

I tried HubSpot’s new GPT Deep Research integration this week — here’s what I found 👇 I’ve been curious how this would work in a real marketing workflow (and how it could benefit my clients), so last weekend, I ran tests in a sandbox version of my own HubSpot setup — side‑by‑side with GPT and Claude, to separate hype from reality. What I Tested Connected HubSpot → GPT for prospecting insights, predictive scoring, personalized follow‑ups, and dynamic campaign ideas. What I Liked (and where I’m Stuck) 1. Real-Time Data Insights Real‑time insights were 🤯 — surfaced micro‑segments and intent patterns we’d been blind to, making audience refinement almost effortless. 2. Automation that still needs a human hand Sequences ran smoothly, but I kept tweaking copy/timing to avoid “robotic follow‑ups.” 💭 Which customer signals does GPT actually read well — and what still needs prompt tweaking to feel human? 3. Privacy + compliance is still the Elephant in the Room Cool features, but I kept wondering. 💭 What guardrails keep data fully compliant? 4. Powerful… but not an exactly “plug and play” for everyone The power is real but I think many marketers may still hit friction. They know the questions to ask, but not how to phrase them so GPT understands.   💭 Will this evolve into a true no‑code tool, or keep staying ops‑heavy? 5. Dashboard + testing gaps Strong MVP, but I miss native marketing dashboards to experiment before pushing live. 6. "Deep Research" mode only Right now it only runs in "Deep Research" mode, which is great for depth, but not ideal when you just need quick questions or tweaks.   My Overall Impression: This could cut out so much those pains in “export → clean → then re‑import" and finally put GPT’s power inside a CRM marketers already know. But strong   data governance   and team readiness   for prompt‑driven workflows is key before scaling. What's your takeaways from this new Hubspot <-> ChatGPT connector? DM me at https://www.linkedin.com/in/oceaneli .