Lillian Pierson, P.E.

The fastest-growing SaaS companies don’t start with messaging. They start with reality. Not personas. (Seems like a joke but no shortage of personas out there like "Digital-First Dave" and "Cost-Conscious Carla") The best companies go straight to the source: their target market. What’s actually happening in their target customers’ world? I’ve seen it play out across 200+ buyer research projects at Wynter. The companies that nail positioning and marketing? They ask sharper questions: → What slows you down in your workflow? → What’s the trigger that gets you searching for a solution? → What would actually make your job easier? They don’t assume. They investigate. The quality of your decisions comes from the quality of your information. And the results show up fast because now you’re speaking to real problems, in real language, with real stakes. It’s not just tighter messaging. It's marketing that finally lands. Stop guessing what matters to your buyers, ask them. It's the only way to know, really. Use tools like Wynter to get insights straight from the source. Run a target customer survey with Wynter to learn what your ICPs want https://wynter.com

108

48 ความคิดเห็น

Your POC process is probably why you're not closing enterprise deals.   After analyzing POC outcomes across our portfolio, the data is clear: Companies with structured and priced POCs close 3x more deals than those running free pilots.   Why charge? Price signals seriousness. Even nominal fees filter serious buyers from tire-kickers. Frame your pilots as fixed-fee engagements: Say "we structure this as a 4-week, fixed-fee engagement to quantify value and build your business case."   Be sure to clarify pricing expectations in the process: If your pilot costs $5K but commercial deals are $100K-$300K based on the value unlocked, state this explicitly to avoid anchoring.   Here are 5 best POC best practices we see:   1. Define success criteria, not scope Align on specific KPIs, business outcomes, and who signs off before writing a line of code.   2. Time-box ruthlessly with weekly checkpoints POCs should run 30-90 days max. Set weekly or bi-weekly checkpoints to maintain urgency.   3. Pre-commit the path to commercial discussions Before starting any pilot, confirm that hitting the success metrics will trigger stakeholder presentations and commercial negotiations.   4. Demand access to the full buying center Technical users alone can't close deals. Ensure you meet decision-makers and budget holders during the POC, not after.   5. Document like a contract Formalize scope, terms, and deliverables in the agreement. Include specific responsibilities for both sides, data access requirements, success metrics, timelines, and post-POC commitments.   --   POCs are where your enterprise motion gets built. Treat them that way.   I wrote a guide to AI pricing with Madhavan Ramanujam and Joshua Bloom that discusses these ideas in more detail. If you're curious to dive deeper, I'll leave that link below. Also, Madhavan just released a new book called Scaling Innovation that also explores these topics. Highly recommend!

134

14 ความคิดเห็น

Pavilion shared wrong stats to 90,000+ subscribers about RevOps. Why do you do this? A guest author wrote a newsletter saying basically that RevOps is not good anymore and long live GTM Engineering. He based his numbers mainly on job board data. He stats there are 822 GTM‑Engineer openings in the US, but it is actually 12 times less. At the same time he says RevOps is in decline, but it is actually on the rise. The issue is he made a mistake in his methodology. When searching for jobs on indeed or LinkedIn it is important to put the full job title in between “” else linked widens the search scope to include unintended jobs. Hence, when searching with “”, we see: GTM Engineer job openings in the US: - 66 (linkedIn) - 25+ (indeed) RevOps job openings in the US: - 549 (linkedin) - 1,000+ (indeed) Now, lets look at the total professionals for each role using LinkedIn Sales navigator (globally) People working in RevOps Key terms: “Revenue Operations” + “RevOps” 2023: 17k+ 2024: 16.5k+ 2025: 20k+ People working in GTM Engineering Key terms: “GTM Engineer”  2024: 870 2025: 650 (82 work at Clay) - YES, it is going down! Rebuking quotes: "Over the last twelve months, major tech companies have either downsized or eliminated their RevOps functions." - Citing companies like Dell and Microsoft. - Those companies laid off 10k+ people. - RevOps is just collateral damage and marginal in this. “About 1,400 LinkedIn job ads for “GTM Engineer” - Does not add up as we have seen above “If both Fortune-500 vendors and venture-backed startups are trimming RevOps, the contraction isn’t an enterprise quirk: it’s industry-wide.” - The previous hiring trends confirm that this is factually wrong. The opposite is true. - There are only 95 GTM engineers in companies with 1,000+ employees. I have seen larger RevOps departments than that. “Hiring dollars that used to go to RevOps are now being re-routed to Go-to-Market Engineers. Essentially the same mandate, just packaged with deeper coding skills.” - First, a lot of speculation and data says otherwise. - Second, this is not the same mandate. GTM Engineering is part of RevOps - Third, as RevOps/SalesOps/MarketingOps was not coding since decades. Using no-code is actually easier then what we did before. “The trust deficit, the hiring pull‑back, the layoffs, and the flight of budget toward code‑first GTM engineers paint a single picture: RevOps is at risk” - Conclusion based on wrong facts. I bet this will reach the eyes of the Pavilion crew, guys please just fact check before making such bolt claims. My view on the topic: - RevOps is in demand - Many companies are understanding it better - PE/VCs are behind - RevOps is driving AI in companies - There are no quick hacks. RevOps community, please share, to avoid spreading fake stats... P.S. I reached out to the author and gave a heads-up that I will publish this post. We had a short exchange and I informed him that this post goes out today.

257

98 ความคิดเห็น

GTM Engineer might be the hottest title in tech right now, but the work has always been there. Some wear the title. Others just do the work, connecting systems, stitching insights, enabling teams, and pushing go-to-market efforts forward without the fanfare. Whether your org calls them GTM Engineers, Revenue Ops, or just “the person who makes everything work,” they’re often the difference between activity and real impact. If that’s you, this asset will help. It’s a clear, no-fluff breakdown of what great GTM execution looks like and how to improve it. Built to support the people behind the motion. Enter Peel Playbook - GTM Engineer Edition (of course as a Talkable) Talk to it - steal the great ideas - link in comments

49

3 ความคิดเห็น

Yesterday, I hosted a panel at HubSpot INBOUND on what the future of GTM AI tech stack will look like. I saved one of my favorite questions for the end: “What is one AI use case that you think is going to blow everything open?” Here’s what came back: (1) AI-Driven Enablement (from Stevie Case, CRO at Vanta) Reps get real-time coaching—live scoring, in-call feedback, and instant optimization. No manager required. Every call becomes a training moment. Every rep gets better, faster. (2) AI Agents that Build Software Speed up Customer Response (from Siqi Chen, CEO & CFO at Runway) This one’s wild: reps initiating and shipping software within minutes of getting customer feedback. Yes, engineers are involved but this puts a whole new meaning to putting your customers first. (3) Voice AI that Adapts to Humans (from Mati Staniszewski, Co-Founder at ElevenLabs) Imagine a voice agent that flexes its tone and pacing based on who’s on the other end. Slower, calmer for older callers. Snappier, faster for younger ones. Hyper-personalized customer experience delivered entirely through AI voice. Three different answers. But one common theme? AI isn’t just automating and making things more efficient; it’s redefining GTM execution, experience, and experimentation. Thanks to panelists Stevie Case, Siqi Chen, Mati Staniszewski, CEO & Co-founder at ElevenLabs for the great discussion. Stage 2 Capital HubSpot #inbound #GTMAI

360

28 ความคิดเห็น

Yesterday Clay called “real-time territories” one of 5 unsolved GTM problems. Static territories are a problem. Unsolved? Not so fast. Gradient Works is solving the static territory problem for thousands of reps today with dynamic books. It’s what we do. Regardless, I’m glad to see a GTM leader like Clay call attention to the problem of legacy territories. It’s a huge issue. 76% of sales teams use geographic territories and 64% aren’t happy with the results. This kind of legacy territory design costs teams 10% of potential revenue[1] and it’s a big contributor to today’s terrible attainment[2]. People just don’t know of an alternative (as Clay’s post[3] makes clear) so they keep doing it the way they have for 100 years (literally; I have receipts). For the past 3 years we’ve been championing dynamic books. It’s an operating model first, tooling second. We’ve built Gradient Works to make the model easy to deploy and execute. Here’s how it works: Instead of carving fixed patches, teams that use dynamic books do the following: 1. Ruthlessly define ICP and tier accounts. 2. Keep segmentation (SMB, MM, Ent) but drop geography. 3. Do a bottoms-up analysis to calculate how many accounts reps can actually work at once. 4. Assign the best accounts (using scoring, firmographics and signals) to max out rep capacity, so they have a focused, highly prioritized book. Leave the rest in a ready pool for marketing nurture. 5. Let the reps cook. They’ll either turn accounts into customers or find out a reason they can’t make progress. 6. If a rep can’t make progress, let them return the account to the pool with clear guardrails. 7. Top off the reps’ books with the next best set of accounts available from the ready pool. 8. Hold reps accountable for covering their books. If they don’t, retrieve and redistribute the accounts they’re not working. 9. Repeat If you want to read more about the Dynamic Books model we’ve got a ton of resources: Dynamic Books Hub: https://lnkd.in/gcrXWtdj Vs. Traditional Territories: https://lnkd.in/gwQsGb3J Capacity Calculations: https://lnkd.in/gAkVE4eA If Clay’s post (or this one) has you intrigued, message me. Happy to share what we’ve learned. Also happy to I’ll connect you with some Gradient Works customers who can share their experience. — [1] Stats from HBR and the Sales Management Association [2] Anywhere from 32% of reps making quota to 51% depending on the source [3] https://lnkd.in/gf8Js3-h.

51

17 ความคิดเห็น

🚀 HubSpot is now the first CRM to launch a connector for Claude HubSpot's new Claude connector does something powerful: it grounds Claude's responses in real context from your CRM. No more generic responses. No more starting from scratch. Your marketing team can instantly ask: "Show me contacts who engaged with our last campaign but didn't convert" and get a visual breakdown ready for action. Your sales team can pull deal summaries by stage and priority—contextualized to your actual pipeline. But here's what makes this different: the insights don't live in isolation. You take them right back into HubSpot where the work happens. We built this connector because context is everything. When Claude can access your business context in real-time—your contacts, your deals, your actual pipeline—it becomes exponentially more useful. This is just the beginning. AI that knows your business —no matter how big or small—isn't just better AI, it's AI that actually moves the needle. If you want smarter answers from Claude, start with HubSpot. 🧡

2,042

131 ความคิดเห็น

Most CRO programs are backwards. Here's what I learned after tracking $50M+ in revenue optimization… Everyone's obsessing over A/B vs. Multivariate testing. But they're asking the WRONG question. It's not "Which test should I run?" It's "Do I have the foundation to test at all?" After auditing 200+ optimization programs, here's the uncomfortable truth: 90% of companies fail CRO before they even start testing. They skip the fundamentals and jump straight to tactics. Here's the systematic approach that actually works: 🟡 The CRO Foundation Framework Layer 1: Traffic Qualification → Under 10K daily visitors? A/B only → 100K+ daily? MVT becomes viable → Between? Sequential A/B wins every time Layer 2: Resource Reality Check → Team expertise assessment → Statistical significance planning → Timeline vs. impact prioritization 🟡 The Scale Decision Matrix Most agencies get this backwards: Low Traffic + Complex MVT = Wasted months Here's what elite teams actually do... Enterprise Scale (1M+ monthly): ↳ MVT for incremental gains (2-5% lifts) ↳ Test element interactions Growth Stage (100K-1M monthly): ↳ Hybrid: A/B validation → MVT refinement ↳ Sequential testing protocols Early Stage (<100K monthly): ↳ Pure A/B for radical changes ↳ Speed over sophistication 🟡 The $5M Mistake Pattern Running MVT without sufficient traffic. Result? → Inconclusive data for months → False confidence in losing variants → Massive opportunity cost The fix: MVT needs 16x more traffic than A/B. 🟡 What The Best Teams Actually Do They don't choose A/B vs. MVT. They architect testing systems: Phase 1: A/B for foundational wins Phase 2: MVT for interaction discovery Phase 3: AI-powered personalization This compound approach generated 32% conversion lifts in our portfolio companies. Because here's what most miss: CRO isn't about testing. It's about building systematic optimization engines. The companies crushing it in 2025 treat testing like investment portfolios: → High-probability A/B bets → High-upside MVT experiments → Diversified across user segments With iOS tracking changes, testing becomes MORE critical. But only if you solve attribution first. Your conversion rate is just a reflection of how well you understand your customers. And testing is how you systematically improve that understanding. === 👉 What's your biggest CRO challenge - insufficient traffic for meaningful tests, or too many variables to test systematically? ♻️ Kindly repost to share with your network 💌 Join our our newsletter for premium VIP insights. Link in the comments.

68

37 ความคิดเห็น

Positioning mistakes cost more than product mistakes. Here’s what I'm seeing over and over again in SaaS: 1. 50-75% of your leads aren’t ICP? That’s not a lead quality issue — it’s a positioning quality issue. Bad inputs = bad funnel. 2. Killer UX doesn’t matter if buyers don’t get your category. Education comes before differentiation. Always. 3. Value-based pricing? Smart in theory. But if customers start gaming the metric, your incentives are broken. Behavior follows pricing — not the other way around. 4. More features ≠ more value. Without clear context, capabilities become clutter. Use frameworks like the Value Matrix to separate the noise from what actually drives willingness to pay. 5. Four tiers is often one too many. Three gives you a “Goldilocks” middle. Two forces trade-offs. (Okta recently simplified their tiers — and conversions improved.) 6. Don’t call it ‘Enterprise’ unless it acts like one. Slapping a label on your highest plan isn’t strategy — it’s theater. You need true enterprise readiness (support, SLAs, integrations, etc.). 7. Stuck between SMB and Enterprise? That’s a roadmap problem, not a sales one. If leadership pushes upmarket without resources to match, you’ll alienate both sides. Pick a lane. Commit. 8. Trying to be everything to everyone? You’ll end up irrelevant to most. Positioning isn’t about being better — it’s about being different enough that comparisons break down. Your product can be perfect. But if your positioning is off, it’s like shouting into a void. Get it right, or nothing else matters.

44

13 ความคิดเห็น

We've scaled from $2M to $8M ARR in six months. Here's our exact tech stack that made it possible: We avoided operational chaos as we scaled by being ruthless about our tooling selection. Every tool you invest in early on either has to accelerate revenue or eliminate friction and waste. Here are the top 11 tools we use: → Clay — GTM orchestration engine for mapping target accounts, enriching with external data, and triggering outbound workflows. → Smartlead — Scales bulk email outreach while managing deliverability at high volumes. → Juicebox — AI recruiting agent platform for leadership-led sourcing and candidate engagement. → Common Room — Aggregates buying signals across channels, scores contacts/accounts, add drives intent-based activation → HockeyStack — Provides full-funnel attribution, linking performance channels and content to revenue. → Amplitude — Deep product analytics tool, used for onboarding journey tracking and product insights. → Hex — AI-enabled analytics workspace for exploring product data, dashboards, and launches. → Circle — Community and cohort management platform used to manage our content engineer group. → Webflow — CMS and site builder that integrates seamlessly with AirOps and the broader content stack. → Descript — Transcript-based audio/video editing tool powering our webinar and content workflows. → Attention — Records calls, extracts insights, and powers our workflow to collect the greatest insights from customers. Half of these integrate directly. The other half we've connected through Zapier or custom APIs. What tools are we missing that you couldn't live without?

230

36 ความคิดเห็น