Sheila Head

Moving from a single product to a platform is one of the toughest shifts a GTM team can make. Next week, I'll be speaking at the Product Marketing Summit - Seattle, hosted by the Product Marketing Alliance, on navigating that shift. We'll explore how pricing and packaging decisions reshape the entire GTM strategy, and how to drive scalable growth without disrupting existing pipeline. Looking forward to some great conversations! 🏙️

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Want to see what Kernel’s CRM and account data actually look like? In last week’s session with Ramy A. from Pigment and Matthew Volm from RevOps Co-op, we walked through how enterprise RevOps teams are rethinking planning and account data management in the age of AI. The clip below shows how we use Kernel to map complex corporate hierarchies inside our own CRM and build the account data foundation that makes it possible. A big theme from the discussion was the shift from static to dynamic account data. Most teams still rely on rigid, once-a-year segmentation and firmographics that go stale quickly. The market changes continuously, and your planning needs account data that keeps pace. AI can help with this, but only if it starts with accurate entities, identities and buying centers rather than generic data from traditional providers. We also spent time on the power of custom hierarchies and real buying centers. Legal entities rarely match how a business actually decides or buys. Using AI to model the true structure of an organization gives RevOps a far more accurate base for planning, territory design and forecasting. This shift is already happening inside the enterprise RevOps teams we work with at Gong, Navan, Zip and Remote. It was especially valuable to hear how Ramy and the Pigment team use Kernel to build the account data foundation they need for accurate planning. If you missed the full conversation, the link is in the comments. Don't miss our next event with Jordan Crawford next Tuesday 📅

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One of my most useful AI scheduled tasks starts with a simple signal: Jensen is speaking. I have a handful of scheduled tasks, but when I recently shared this one with a peer group, it got a few “oohs” and “ahhs.” People immediately began thinking about how they could adapt it to their own use cases. That made me realize it was an idea worth sharing. Jensen is the ultimate visionary. With every keynote and speaking session, he’s writing the NVIDIA story in real time—clarifying what matters now and where the industry is going next. At a company moving this quickly, that narrative is more than inspiration. It’s strategic input. My AI scans for new Jensen talks, then goes beyond summarization. It identifies key themes and takeaways and considers them through a marketing lens: What could these signals mean for my role and my team in digital marketing growth? What should we explore, prioritize or act on? It doesn’t replace my judgment. It gives me a consistent way to listen, connect the dots and turn an important signal into action. What are some of your favorite—or unexpectedly helpful—agent scheduled tasks?

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CMOs/VP PMMs - If you’re planning your 2026 org, don’t start with the org chart. As teams plan for next year, they shuffle boxes, add a few heads, and redraw a few reporting lines to manage complexity. That’s fine if it’s business as usual. But if you’re scaling – or getting ready to – this won’t cut it. Assuming you’ve got your 2026 goals in place by now (you do right? 😉), start by thinking about the work before the workers: Step 1: List the Jobs to Be Done Map the actual work that needs doing, no job titles: - Develop sales battlecards - Run win/loss interviews - Build release messaging - Maintain competitive intelligence - Produce thought leadership - Run customer advisory boards - Analyse pipeline contribution Step 2: Cluster into Work Streams You’ll end up with 20+ jobs. Group them into 4–6 streams: - Customer Intelligence (research, win/loss, personas) - Enablement Content (battlecards, decks, messaging) - Market Analysis (competitive intel, analyst relations) - GTM Orchestration (launches, enablement, alignment) Step 3: Map the Cadence When and how often does each stream need attention? - Annual (positioning refresh) - Quarterly (campaigns) - Weekly (competitive intel) - Daily (sales enablement) - In bursts (major launches) Step 4: Match Resources to Need Now ask: who or what should deliver? - Full-time employees (core needs) - Fractional experts (specialist knowledge) - Agencies (surge capacity) - AI tools (scalable workflows) - Hybrid mixes This way, your 2026 plan isn’t about headcount. It’s about building a resource system that flexes with growth. Adapted from the EOS Traction model, this turns planning from a budget battle into capability design. You’ll know how your budget maps to impact – and how the right work gets done by the right resource of the right kind. Workshop this out next week, and the rest of your annual planning conversations will look very different.

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Competitive intelligence is moving from quarterly research to always-on GTM infrastructure. Not because teams need more dashboards. Because pricing pages change faster, docs reveal product direction earlier, review sites surface objections publicly, and sales teams need current talk tracks. The winners will not be the teams watching the most competitors. They will be the teams that turn the right public signals into decisions quickly. That is the lane we are building toward with Clura. #CompetitiveIntelligence #GTM #ProductMarketing

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