Pylon's pricing model has changed 10 times. Here's how.

LEADING CUSTOMER SUCCESS FROM THE AI TRENCHES Every company says they’re “doing AI.” But leading Customer Success for a SaaS platform that 𝘶𝘴𝘦𝘴 AI isn’t the same as leading it for a company that 𝘪𝘴 AI. Most CS leaders are preparing for one challenge. They’ll face two. SAAS + AI = BUSINESS MODEL TRANSFORMATION Adding AI isn’t a feature release, it’s a business model rewrite. Publicly available data says: – Seat-based pricing dropped from 21 to 15 percent of firms last year, while two-thirds of IT leaders saw surprise AI-related costs. – For every $1 spent on AI development, companies spend $3 on change management. CS now manages financial literacy and transformation risk: – Predicting consumption volatility – Proving ROI (AI “magic” doesn’t renew contracts) – Redesigning workflows and incentives The best AI-augmented CS teams act as change-management experts first, CSMs second. AI-NATIVE = RELIABILITY & GOVERNANCE When AI 𝘪𝘴 the product, success means dependable intelligence. CS becomes Reliability Ops, owning model drift, fallback frequency, and bias risk. Your team must: – Translate performance metrics into business risk language – Run real-time feedback loops to ModelOps and Product – Support outcome-based renewals tied to reliability – Manage trust during model updates—opt-outs, rollbacks, transparency THE HYBRID REALITY Most firms live between these worlds, expanding AI faster than their CS teams evolve. Suddenly, customers ask about accuracy rates, not adoption curves. Your relationship managers now field questions about model confidence intervals. CAPABILITIES THAT MATTER PHASE 1 – AI-Enhanced SaaS: build ROI frameworks, teach consumption economics, lead change programs. PHASE 2 – AI-Native Readiness: add model-ops fluency, reliability dashboards, risk frameworks. PHASE 3 – Bridge Role: translate drift into business impact, own outcome metrics, orchestrate updates with trust. THE HARD QUESTIONS – Can your team explain AI’s ROI in dollars? – Do you know what happens when the AI is wrong? – Are you measuring reliability or just renewals? – Have you budgeted for the 3:1 change-management reality? THE BOTTOM LINE In this new landscape, Customer Success has evolved from a function to the control tower of trust. You're not selling software or intelligence anymore. You’re selling transformation and dependable autonomy. Customer Success now means managing trust, reliability, and economics together. The companies getting it right report 2-3× traction and renewal lift. The rest? Their customers quietly disengage.

OpenAI is no longer just an AI builder or provider, it’s becoming (or perhaps already is🤔) a powerful competitor to many SaaS companies. These blogs tell how OpenAI leverages its own technology to support internal teams, from customer support and inbound sales to reviewing thousands of contracts. It’s fascinating to see how deeply we can integrate AI into every part of business. https://lnkd.in/gXa8R-3F https://lnkd.in/gT8PJTTB https://lnkd.in/gXhS_HtC

Sometimes i need to share things that suck... companies come to us at Paid when their AI agent pricing is broken. A few months ago a founder told me: "we're closing our first enterprise deal but we just made a ballpark estimate on price", and in a recent call he told me he dropped it by 50% and then 60%, and now the margins are gone. I'd like to say this is the exception but it may be more common than we think. Lots of people are building things without knowing how they'll monetize them (and we were kind of like that at first too) I built a framework (called DRIVE) based on what actually worked across 250+ companies. The tl;dr is kind of like: Month 1: prove value. Month 2: track everything. Month 6+: charge for outcomes not actions. Full breakdown here: https://lnkd.in/dbcBQUDb

🎧 What happens when you listen to thousands of Gong and Chorus calls? You get a masterclass in what separates reactive customer success from proactive, trusted partnership. This dives into the patterns AI uncovered across 10,000+ CSM conversations. The learnings are gold for SaaS leaders and CS pros alike. Key takeaways: 💡CSMs who ask strategic, open-ended questions build deeper trust. 💡The best calls focus less on product features, more on customer outcomes. 💡AI can surface coaching moments that transform onboarding and renewal conversations. This isn’t just about automation; it’s about amplifying human connection at scale. If you're leading a CS team, imagine what your call data could teach you. If you're a CSM, imagine what you could learn from your own patterns. The future of CS isn’t just data-driven... it’s insight-driven. https://lnkd.in/gBbWyyfb #customersuccess #automation #AI #artificialintelligence #insight #data #digitalcustomersuccess

Welcome Grant Deken, Head of Product for Klaviyo Service on this episode of 🔥The Lantern 🔥 Klaviyo has been a data-first company since the beginning, bringing all of your customer data into one place to get the right message to the right customer at the right time. 🔍 What’s going on inside Klaviyo in 2025? 🔎 In 2025 they’ve expanded that vision substantially with their B2C CRM, which includes customer service, to capture more of the end to end customer relationship - recently announced at K:BOS! They’re launching two new customer agents with Klaviyo AI or KAI, accelerating the work teams can do to get in front of customers, build better experiences, and deepen relationships. 🔍What else is Grant working on that he would share with the Boston startup community? 🔎 Grant owns new products at Klaviyo where they’ve rolled out reviews and now Klaviyo Service. Klaviyo Service has been built from the ground up with three products: 1.) Customer Agent - instant “on” intelligence on top of the Klaviyo data platform driving revenue and impact for brands 2.) Customer Hub - bringing merchandising, personalization, and service together on the website storefront 3.) Help Desk - bringing a fresh perspective with service agents, giving them all the analytics and marketing data, to have a true and complete customer picture Klaviyo Service delivers not just better service but helps rethink service as more of a revenue driver and growth engine for brands. When Grant came to Klaviyo, he talked to co-founders Andrew Bialecki and Ed Hallen about creating a startup environment with this hyperscale company to have as much impact as possible. Credit to Ed & Andrew for helping clear the path to help the team experiment and build new things. It’s a year of acceleration and they’re trying to emulate these wins across the whole org! 🤔 What has Grant learned from his startup career and building at Klaviyo? 🤔 Leaning in and saying yes more. Take more risks, especially early in your career! The more you do, the more you learn. The failures are really where the learnings are, you can’t get those unless you take chances! When he worked for Bryan House at Elastic Path, Grant ran Growth and worked on integrations, learning the value of bridge building across an organization. Thinking across the business and then building those bridges with your counterparts, you can move much faster. The Lantern is brought to you by MGMT Boston, Rho, & Invest Northern Ireland – Americas this month

🤖 Can 200 million businesses finally afford enterprise-grade customer service? Follow Me: https://lnkd.in/g7tAAYHG Meta just announced Business AI, a customer service agent that could democratize what Fortune 500 companies have had for years. This changes the game for SMBs globally. Here's why this matters 💡 The challenge: 600 million daily conversations happen between businesses and customers on Meta's platforms. Most small businesses can't afford dedicated 24/7 support teams. Customer expectations keep rising, but resources remain tight. The breakthrough: Business AI learns from your existing content—social posts, ads, website copy—to provide personalized responses across Facebook, Instagram, WhatsApp, and your own website. No massive setup required. Real impact on operations: • SMBs using AI for customer service report 95% improved response quality • Resolution times drop significantly, with 72% seeing faster turnarounds • Studies show businesses using AI see revenue increases, with 91% reporting positive impact • Available free within Meta ads; paid option for websites at competitive pricing What makes this different ⚡ Unlike complex enterprise solutions, Business AI integrates where customers already are. Clara Shih, Meta's head of business AI (previously at Salesforce), emphasizes this is about "delivering that 24-seven personalized service that every consumer wants." The broader picture: By 2025, 95% of customer interactions are expected to be AI-powered. Companies are seeing average returns of $3.50 for every $1 invested in AI customer service. Action steps for business leaders: ✓ Start small: Test AI for common queries first ✓ Maintain human oversight for complex issues ✓ Use this tech gap moment before competitors scale ✓ Consider that 78% of organizations already use AI—waiting means falling behind The playing field is leveling. Small businesses in Manila, Mumbai, or Manchester can now offer service experiences that rival global enterprises. But here's the catch: While 64% of consumers surveyed said they'd rather companies didn't use AI for service, this same research shows customers value fast, accurate support above all. The key is transparent, thoughtful implementation that enhances rather than replaces human connection. Learn more about Meta's announcement: CNBC's coverage of Business AI launch - https://lnkd.in/eZqhZpKC Industry analysis on AI's impact on SMBs: Salesforce research on SMB AI trends - https://lnkd.in/eTgy6aKH What's your take? Are you experimenting with AI for customer service, or still evaluating? Share your experience below. #BusinessAI #CustomerService #SmallBusiness #AIforBusiness #DigitalTransformation

Per‑seat pricing broke their AI‑era SaaS. Expansion slowed, champions hesitated, and finance kept asking: “Why pay for users who never log in?” A client came to our company from Kyiv with exactly this problem. Here’s what we discovered: automation moved value from human seats to outcomes—documents processed, reconciliations completed, tickets resolved. Based on our experience and OpenView’s data, usage elements are now mainstream (61%), and peers with usage see ~120% median NDR vs ~109% without. McKinsey’s math is sobering: 1% price improvement can lift operating profit by 8–12%. Let me tell you with an example: in one deployment, an agent resolved 8,000 of 16,000 tickets in week one (~5× human throughput) while NPS rose ~4%. To be honest, charging per seat undersold value for large accounts and over‑charged small teams leveraging automation. Specifically, this means shift pricing to outcome proxies your buyers already track: - Workload automated (%), cycle‑time reduction, outcome quality (NPS delta, error rates) - Value units like reconciliations, documents processed, API calls, tickets resolved - Hybrid plan: platform fee + included units + capped overage with 70/90/100% alerts and pre‑bill estimates Our Shadow‑Then‑Shift method (4–6 weeks): - Parallel plans: keep legacy per‑seat; offer usage/hybrid to new cohorts - Invoice shadowing: show $0 usage lines for 1–2 cycles to teach the metric - Opt‑in upgrades + cohort gating to avoid churn - Guardrails: caps, rollover credits, and predictable invoices Results we keep seeing: cleaner trial‑to‑paid readouts, calmer finance teams, and expansion that tracks real outcomes. The result exceeded expectations when teams labeled the metric in customer language (“tickets resolved” beats “AI actions”) and instrumented trustworthy metering. How are you defining your value unit today—and what cap/rollover policy would make finance comfortable in month one? Suggested visual: a sample invoice with platform fee + included units + overage caps, plus a mini chart of automated workload % over time. #SaaSPricing #UsageBasedPricing #AgenticAI

📣 The rules of #CustomerService are being rewritten—are you ready to lead? Customer expectations are evolving fast—and top customer service companies aren’t just keeping pace; they’re setting the standard. In our latest CX Blog, we break down how elite organizations are: ➡ Turning support into strategy ➡ Preparing for agentic AI and bot fatigue ➡ Scaling smart with end-to-end outsourcing Now’s the time to think like it’s already 2026. 🔗 Read the strategy playbook: https://lnkd.in/dtD573zU #CustomerExperience #CXStrategy #ContactCenterLeadership #FutureOfCX #CustomerSupportLeaders

We thought a major account was at risk. Usage was down. Renewals delayed. But CSAT? Still high. AI flagged the root cause: the champion had left. No complaints, just silence. We re-engaged early, built a new relationship, and kept the account. AI didn’t just predict churn. It gave context, and a chance to act before it was too late. + Great read on this shift: The Proactive Edge: Leveraging AI for Customer Retention Success (Forbes) #AI #CustomerRetention #EnterpriseIT #CustomerSuccess

“AI is a powerful tool to personalize outreach, surface product-qualified accounts, and guide teams toward higher-value conversations, but it must be applied with authenticity and accuracy.” Our new Chief Customer Officer, Stephanie Berner, chatted with SalesTech Star about the practices she puts into place to help drive customer success, and how AI fits into their journey: https://lnkd.in/gum2udEB