Ryan Batter

Outbound in SaaS is shifting from volume to signal-led, AI-assisted, and broader focus across the buying group. The teams winning today aren’t blasting to the masses. They’re able to be laser-focused by leveraging better data, informed timing, and centralized collaboration across the entire GTM organization. Here are 5 outbound trends I’m seeing in SaaS right now: 1️⃣ Signal‑Led Buying groups are larger (10+ stakeholders in many enterprise deals), so reps are mapping the full committee, prioritizing accounts based on intent, engagement, and firmographic fit, rather than just ICP target personas. 2️⃣ AI Augmented SDR Motions AI is qualifying and enriching leads, drafting first-touch and follow-up emails, and monitoring deliverability, so reps can spend more time in conversations and less time in spreadsheets and research tabs. 3️⃣ Hyper Personalization at Scale Generic sequences are dying. Outbound engines are pulling in company news, tech stack, hiring, and even social posts to generate contextual emails and multi-touch sequences that feel researched and thoughtful. 4️⃣ True Multi-Threading Across the Buying Group Relying on a single “champion” is now seen as a risk, not a strategy. Best-in-class teams design plays that engage economic buyers, power users, and adjacent stakeholders in parallel to de-risk deals and shorten sales cycles. 5️⃣ RevOps Orchestrated, Multi-Channel Plays Outbound is no longer just cold email plus smilin' and dialin'. Revenue teams are orchestrating LinkedIn, email, phone, and targeted ads into one coordinated experience, resulting in outreach that feels like a continuation of a conversation, not a cold interruption. Which of these trends are you already leaning into, and where are you still experimenting?

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💰 Revenue leaders 💰 take note! Seth Marrs and Jared Houghton sit down to talk AI for sales leaders and maximizing GTM team performance 🚨 🚨

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Spot on. Deepinder Singh Dhingra summarizes it well. You need a system for action and actual revenue impact. We have to take back control of the multiverse that is GTM. 😎 🦾 We all struggle with it. Modern GTM motions are super powerful, but insanely complex and overloaded. RevSure AI tames that noise, gives action to data and gives control to the agent tsunami. Check it out!

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Go-to-market doesn’t control everything, but it has to influence almost everything. In our latest Tip of the Spear interview, we sat down with Erin Felton, Fractional GTM Operator and former Wayfair and Shopify leader, to unpack what actually drives revenue alignment at scale. A few highlights that stood out for me: 〜 Poor inputs create chaos, even when teams are talented and well intentioned 〜 If marketing isn’t thinking about sales as a key channel, and vice versa, you’re missing the point 〜 Empathy between sales and marketing leaders is a measurable growth driver 〜 Resilient GTM leaders are willing to try new things, upskill and reskill, fail fast when something isn’t working, learn from it, and move on Erin’s perspective is deeply operator-led. From scaling Wayfair’s B2B business to driving ~27% incremental attributed revenue through tighter sales and marketing alignment, the through line is discipline before speed. If you’re building a revenue engine or considering when and how to bring in senior GTM leadership, this one is a great read. Full interview linked in the comments.

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Ryan Walsh is spot on. OTE and comp structure matter, but they’re actually secondary. What really determines AE earnings potential is the competitive advantage of the product, the size of the serviceable addressable market (SAM), and customer sentiment about the category and product you sell. And in the current AI hype cycle, it’s worth asking a simple question: is there substance behind the story, or is it a solution looking for a problem?

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AI is changing how we execute - less so what the foundations of great RevOps look like. On a recent Domestique webinar with Alex Biale, we unpacked why the best AI-native teams treat GTM like a product: clear strategy, defined processes, the right tech, ongoing enablement, and clean data - all instrumented in real time. My core takeaways: - Data is the operating system. If inputs are messy, AI just compounds the chaos. Start with a shared data dictionary (MQL/SQL/ICP, stage criteria, ownership, etc). - Orchestration is earned. You don’t get AI co-pilots and shadow agents until the foundation is trustworthy. Focus on your data-layer first to earn your right to orchestration. - Build weekly GTM pulse checks (pipeline movement, inter-stage conversions, leading signals) so there’s still time to act - not just diagnose at the end of the quarter. - Enablement isn’t a QBR slide anymore - it’s real-time feedback from call transcripts into Slack, fueling better discovery, handoffs, forecasts, and coaching. We also touched on a couple other key points like: - The goal posts for greatness are moving and the benchmarks are going up. - Why GTM still wins on the basics done right - now executed with AI. Check out the link in the comments for the full conversation.

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Hundreds of conversations in the past 18 months. Customer Success leaders. GTM leaders. Founders. Investors. ICs. One question: “How do you actually use AI at work?” 80% gave me the same answer. And 80% were wrong about their own level. I mapped it into a framework (swipe through below). The answers fall into exactly 5 levels. Most people think they’re at Level 3. They’re not. The real gap isn’t between 1 and 2. It’s between 2 and 4. That’s where AI stops doing tasks for you and starts changing how you think about the work. Sharing this because I wish someone had shared it with me a year ago. Drop your level in the comments ↓ #AI #CustomerSuccess #Leadership

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When GTM teams aren't aligned, execution breaks down. Content gets lost, sales plays stall, and buyer experiences suffer. 🫣 True alignment isn't just about shared goals – it's about shared execution. And that's where enablement comes in. Learn how Seismic helps unify GTM efforts and drive real results, here ➡️ https://lnkd.in/gV_hEGvP ​

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Tony Fadell’s X post today on the shape of product orgs kicked up a lot of dust and probably caused both PMs and PMMs a little angst. I’ve been thinking a lot lately about what the future PMM org actually looks like. This model where one person owns requirements through messaging makes sense on the extremes: it works at very small companies where one person wears all the hats, and at very big companies where headcount is easy and roles can be narrower. But what about the big middle ground? In this new world of AI, what do these roles look like, and how does PMM start to clash with other existing roles? When I look at the spectrum of how a product goes to market, I think it distills down to two paths: 1. The Inbound Strategist The inbound PMM starts to blend with PM to create a hybrid role: customer research, market awareness, product requirements, messaging, and working w/ Eng. PMs who can storytell, or PMMs who lean technical and embrace AI, should lean this way. 2. The Outbound Orchestrator The outbound PMM starts to blend more with Content and MOps to create an outbound hybrid role. They take the core messaging and leverage AI to generate and orchestrate content across channels. They are systems thinkers and data-heavy, optimizing ads and copy variants regularly. If you’re a PMM today, you should be honest with yourself about where you lean. If you lean inbound, you should be building the PM skills that are now available to you due to AI. Learn prototyping and work in Lovable, Cursor, or v0. If you lean outbound, learn content generation through tools like Figma or Canva, and orchestration through tools like Typeface. What did I get wrong? Curious to know what you all think the PMM org of the future looks like.

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