Podcast
SaaS Sessions
Hosted by Sunil Neurgaonkar · EN
SaaS Sessions is India's first and #1 SaaS-focused podcast with over 21000+ listeners.
The podcast was started by Sunil Neurgaonkar in 2019 and has hosted over 100+ leaders from the SaaS community.
We have hosted leaders (C-level/VPs/Directors) from SaaS companies like Clari, Retool, Github, Segment, G2, Moengage, Whatfix, and more.
10episodes
Episodes
Newest firstAll episodes
S10E2 - From Harvard Law to SaaS CEO: Decoding the "Paperless" Future ft Shashank Bijapur, Spotdraft
Feb 1700:31:00Tap to summarizeShashank Bijapur, co-founder and CEO of Spotdraft, explores the transition from the archaic, manual world of legal practice to the high-velocity domain of B2B SaaS. In this episode, we strip away the jargon surrounding "LegalTech" to reveal how Spotdraft powers the invisible infrastructure of global commerce - from airport leases to ride-sharing agreements. Shashank provides a masterclass on finding product-market fit in the mid-market, the reality of AI's role in high-stakes legal workflows, and the strategic pivot from technical perfection to market-driven iteration.Key Takeaways1. The "Aha Moment": Identifying Stagnation in Essential Industries- Digital Lag: While photography (Adobe) and accounting (Intuit) underwent digital revolutions decades ago, legal innovation peaked in 1993 with Microsoft Word's "Track Changes."- The Opportunity Gap: Identifying ubiquitous, paper-heavy processes that remain manual despite technological advancements is the strongest signal for a SaaS disruption.- Democratic Software: The goal isn't just to replace a lawyer; it's to turn complex legal processes into software that is as accessible and intuitive as a consumer app.2. GTM Strategy: The Power of Mid-Market Focus- Avoid the "Gambler's Fallacy": Shashank emphasizes the importance of trashing unusable early products rather than doubling down on a failing idea.- Homogeneity Matters: The US is the primary target for Indian SaaS due to its massive, homogeneous market, which allows for a repeatable ecosystem and faster flywheels.- The Mid-Market Sweet Spot: Avoiding the high-churn "small business" trap and the "unobtainable enterprise" early on leads to a focused GTM where legal teams (the true buyer persona) have decision-making power.3. The Founder's Dilemma: Accuracy vs. Speed- Legal Training vs. Startup Reality: Lawyers are trained for 100% accuracy; founders must embrace "fail fast." Overcoming the urge to pursue a "perfect product" is essential to gathering user feedback.- Technical Maturity: In 2017, the promise of AI exceeded the technology's capability. Spotdraft pivoted to building robust workflows first, capturing the data needed to make today's LLM integrations effective.- The Talent Moat: When a founder lacks specific functional knowledge (like GTM or engineering), the solution is "talent density"—hiring highly motivated experts who believe in the mission.4. The Future of AI in High-Stakes Legal- The End of "Form Filling": UI is shifting from manual data entry to conversational interfaces where users describe an outcome, and the AI configures the workflow.- Context is King: General LLMs lack company-specific context. AI's value in SaaS comes from mapping global laws against a company's specific historical data and standards.- Humans in the Loop: AI will handle "grunt work" and pattern recognition, but $1M+ deals will still require a human handshake and strategic negotiation for at least the next decade.About Spotdraft:Spotdraft is an AI-driven, end-to-end contract automation platform designed to clear the "madness from quote to cash." It helps businesses of all sizes—from startups to giants like Uber and Airbnb—create, manage, and analyze contracts seamlessly.Chapters:00:10 - Introduction00:50 - Journey from Lawyer to SaaS CEO03:34 - The "Aha Moment" for LegalTech07:09 - Spotdraft's Hidden Role in Everyday Life11:34 - GTM Strategy: Building from India for the US18:24 - Balancing Legal Risk with Founder Speed22:56 - How LLMs are Changing Legal Workflows30:22 - Lightning Round: Lessons Learned & AI ToolsVisit our website - https://saassessions.com/Connect with me on LinkedIn - https://www.linkedin.com/in/sunilneurgaonkar/
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S10E1 - Engineering the Super Bowl ft. Catherine Johnson, VP of Global Solutions Engg. at Hydrolix
Feb 300:45:26Tap to summarizeReal-time analytics at a petabyte scale isn't just a technical challenge; it's a business survival requirement. Catherine Johnson, VP of Global Solutions Engineering at Hydrolix, joins the show to deconstruct the "impossible" architecture required to power the 2025 Super Bowl broadcast for Fox Sports. From managing 1.4 petabytes of daily log data to the brutal reality of why traditional auto-scaling fails during mission-critical events, Catherine reveals the strategic framework behind being a "Truth Teller" in the high-stakes world of Solutions Engineering.Key Takeaways1. Data Architecture as a Competitive Moat- Normalization is Non-Negotiable: At a petabyte scale, you cannot afford "dirty" data. Success requires normalizing disparate CDN logs—matching units (ms vs. s) and handling recursive URL encoding—into a single, queryable schema.- Indexing vs. Regex: Computational intensity kills performance. Strategic indexing for exact matches must replace regular expressions for high-frequency queries to avoid massive, costly table scans.- Schema Flexibility: Implementing multiple schemas on a single table allows for both granular technical deep-dives and high-level executive overviews without duplicating storage.2. Scaling Strategies for "High-Intensity" Events- The Limits of Auto-scaling: For predictable surges like the Super Bowl, relying on auto-scaling is a risk. Pre-scaling to 3x expected peak ensures availability when AWS regional compute limits are hit.- Multi-Region Redundancy: True global scale often exceeds the capacity of a single cloud region. Architecting for multi-region deployment is a requirement, not an option, for Tier-1 broadcast events.- Segregated Query Pools: Prevent "compute competition" by isolating resources. Executive dashboards, SRE monitoring, and ad-hoc troubleshooting should never fight for the same compute cycles.3. Solutions Engineering as "Truth Telling"- The Trust-Based Framework: A Solution Engineer’s (SE) primary role isn't selling—it's building trust through accurate empathy. If the product isn't a fit, say it. Protecting your professional reputation outlasts any single sales cycle.- Root Cause Inquiry: When a customer asks for a feature or query optimization, pause. Don't answer the technical question until you've uncovered the business outcome they are trying to achieve.- Business Mapping: Every technical requirement must map directly to a business requirement. If it doesn't, it’s just unnecessary complexity.4. The "Break-Fast" Learning Philosophy- Fearless Experimentation: The learning curve is shortened by breaking things in dedicated environments. If you only follow the "happy path" of a tutorial, you haven't actually learned the system.- Bridging Data Realities: There is often a gap between how data is stored for performance and how it looks in the real world. Success in SE requires the ability to bridge these two perspectives for the customer.Chapters:00:10 - Introduction: Meet Catherine Johnson00:50 - The Origins of Hydrolix: Solving the CDN Log Crisis06:10 - Deep Dive: Behind the Scenes of the 2025 Super Bowl10:14 - When the Path Changes: Adjusting Architecture Mid-Season14:25 - Multi-Region Deployment & AWS Compute Limits16:51 - Half-Second Query Times: How to Segregate Compute25:49 - The Non-Obvious Skills of Top-Tier SEs31:32 - The "Farming" Lesson: Understanding How Businesses Make Money37:04 - Lightning RoundVisit our website - https://saassessions.com/Connect with me on LinkedIn - https://www.linkedin.com/in/sunilneurgaonkar/
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S9E8 - Unified Commerce & AI ft. Jigar Dafda, CPTO at Fynd
Dec 2200:42:24Tap to summarizeIn this episode of the SaaS Sessions podcast, Sunil Neurgaonkar sits down with Jigar Dafda, Chief Technology & Product Officer at Fynd, to unpack how AI is fundamentally reshaping e-commerce in India.From conversational commerce and hyper-personalization to autonomous back offices and AI-driven customer support, this conversation cuts through the hype to explain what’s actually changing, what’s overblown, and what founders must build for if they want to survive the next decade of commerce.Key Takeaways -1. Commerce Is Shifting From Interfaces to Conversations-Traditional storefronts and search-driven UX are being replaced by conversational buying surfaces.- SEO is giving way to GEO (Generative Engine Optimization) as ChatGPT-like interfaces become the new entry point.- Merchants will still own fulfillment and data—but discovery will increasingly happen outside their websites.2. Hyper-Personalization Is No Longer Optional—It’s Infrastructure- Customer Data Platforms (CDPs) are the backbone for AI-driven personalization across online and offline channels.- AI enables real-time personalization without armies of data scientists or analysts.- The real win isn’t better targeting—it’s higher conversion with less customer effort.3. Dynamic Pricing and Forecasting Are Moving Into the Back Office- Pricing, inventory planning, and demand forecasting are becoming autonomous systems.- Decisions that once took days (via SQL and dashboards) now happen in real time.- AI shifts teams from “executors” to “validators” of system-generated decisions.4. Customer Support Is the Lowest-Hanging AI Opportunity- 60–80% of customer queries are repetitive and easily automated.- AI agents now deliver 24/7, multilingual, context-aware support at scale.- The real challenge is no longer conversation—it’s clean integration across OMS, WMS, and logistics systems.Lightning Round Insights:- Fastest way to learn today: Use ChatGPT as a personalized tutor—summarize, question, and iterate.- Hardest leadership lesson: Systems are easy. People are not.- Founder advice: Build for where the market is going, not where it is today—today’s solution will expire faster than you expect.About Fynd:Fynd is one of India’s leading unified commerce platforms, powering brands across online, offline, marketplaces, and quick commerce. From storefronts and PIM to OMS, WMS, and omnichannel integrations, Fynd enables end-to-end retail operations on a single stack.Chapters:00:10 – Introduction00:50 – Jigar’s decade-long journey at Fynd05:20 – AI before vs after ChatGPT08:10 – Conversational commerce & GEO13:40 – Hyper-personalization and CDPs19:40 – Dynamic pricing and demand forecasting30:30 – AI in customer support37:20 – Predictions for the future of e-commerce39:40 – Lightning roundVisit our website - https://saassessions.com/Connect with me on LinkedIn - https://www.linkedin.com/in/sunilneurgaonkar/
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S9E7 - From Clicks to Conversations ft. Tom Drummond, Founder & Managing Director at Heavybit Industries
Oct 600:43:37Tap to summarizeTom Drummond, founder and managing director at Heavybit Industries, dissects the seismic shift from graphical interfaces to conversational AI—and why most SaaS companies are thinking about it wrong. This isn't about adding chatbots to legacy products. It's about fundamentally rethinking what software means when voice becomes the primary interaction mode and agents become your customers. Drummond reveals why rapid execution trumps defensibility, how API-first companies will dominate the agent economy, and why trust—not technology—remains the ultimate bottleneck.Key Takeaways:1. Large Language Models Are Creating the Biggest Interface Shift Since the GUIThe fundamental breakthrough isn't AI intelligence—it's natural language interpretation that frees computing from screensThis democratizes access beyond anything the mobile revolution achieved, making software ubiquitous without requiring visual interfacesThe transition will be generational: today's builders remain skeptical while the next generation will trust AI as naturally as we trust Wikipedia2. Visual Interfaces Won't Disappear—They'll Become Trust MechanismsGUIs will shift from primary interaction mode to verification and confidence layer for voice-driven commandsHumans need visual confirmation not because they're old-fashioned, but because they require ownership and accountabilityThe winning pattern: conversational interfaces for input, visual interfaces for trust and evidence3. Software Must Do More When Friction DisappearsIf you previously delivered value by creating forms to fill out, you've been selling toil—not solutionsWhen a 22-second phone call replaces a 10-minute form, your platform value collapses unless you deliver actual outcomesThe new bar: integrate across systems, automate end-to-end workflows, and eliminate entire categories of work4. Momentum Is the Only Moat That Matters at Early StageDefensibility discussions are premature when the entire market is being redefined and expectations resetInvestors have shifted to momentum-based evaluation even at seed stage—growth velocity trumps articulated competitive advantagesExecute aggressively with AI internally before worrying about competitive positioning: ship faster, operate leaner, reimagine everythingLightning Round Insights:Learning accelerator: Experiential over theoretical—don't read about programming, program; don't study sales, sellCareer wisdom: Agency and aggressive opportunity capture matter more than perfect strategy in high-change environmentsDaily AI tool: Continue (Heavybit portfolio company)—enables rapid internal tool development with model-agnostic approach and custom data sourcesChapters:00:00 - Introduction and Heavybit's Investment Thesis04:33 - The Language Model Revolution: From Screens to Voice12:13 - Rethinking Product Design: Phone Numbers Over Websites21:36 - Key Challenges: Trust, Pricing, and Agent Distribution30:04 - Differentiation Strategy: Momentum Over Moats36:56 - Why Switching Costs Still Matter for Sustainable Growth40:04 - Lightning Round and Closing ThoughtsVisit our website - https://saassessions.com/Connect with me on LinkedIn - https://www.linkedin.com/in/sunilneurgaonkar/
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S9E6 - The Future of Intelligent Agents in SaaS ft. Bhaskar Roy, Chief of AI Products and Solutions at Workato
Sep 2900:39:41Tap to summarizeBhaskar Roy, Chief of AI Products and Solutions at Workato, breaks down the fundamental shift from app-centric thinking to agent-first architecture. This conversation cuts through the AI hype to reveal how enterprises are moving beyond simple content generation to deploy agents at the core of business processes—from quote-to-cash workflows to IT helpdesk operations. Roy reveals the critical gap between low-agency experimentation and high-value automation, outlines the governance frameworks required for autonomous agents, and explains why getting hands-on is the only way to separate signal from noise in the agentic era.Key Takeaways1. The Agency Gap: Most Companies Are Stuck in Low-Value TerritoryGartner research shows most companies remain in low-agency activities like content creation and email writing, while maximum ROI comes from agents executing core processes like order-to-cash and supply chain managementSaaS is deterministic and requires months for customization, while agents adapt and execute in real-timeThe transformation eliminates bottlenecks where process experts depend on developers for integrations2. Purpose-Specific Agents with Enterprise Skills Beat General-Purpose ApproachesAgents must be narrowly focused with defined skills—finance agents restricted to finance users, each agent limited to relevant capabilities onlyGovernance controls agent-to-agent collaboration, with supervisor agents coordinating and ensuring complianceAgent authentication ensures agents respect user permissions—only updating data the individual user can access3. App Events and Enterprise Acumen Enable Proactive IntelligenceAgents listen to events across systems—new hires, leads, tickets—then reason, contextualize, and take autonomous actionEnterprise acumen monitors KPIs continuously and proactively recommends actions as metrics fluctuateThe shift from reactive to proactive requires human-in-the-loop now, but full autonomy approaches rapidly4. The Mindset Shift: From App-Centric to Agent-First ThinkingStop thinking about which app to use—start asking which agent can handle core business processes betterWhen agents become core to business, reliability matters—platforms must provide innovation with enterprise-grade trustReading about AI isn't learning—build agents, test them, discover what's real versus hypeChapters:00:00 - Introduction00:46 - Journey at Workato: From Integration to Intelligent Agents03:40 - The Evolution from SaaS to Agentic Workflows07:51 - Best-of-Breed Apps Creating Data Silos and Integration Challenges10:54 - Employee Productivity Gains Through Unified Agent Interfaces13:20 - The Agency Gap: Low-Value vs. Core Business Process Automation17:32 - Real-World Agent Deployments: Quote-to-Cash and IT Helpdesk20:12 - Proactive vs. Reactive Agents: Where Does Automation Stop?24:42 - Trust, Governance, and Control in Autonomous Agent Systems28:42 - Preparing for the Apps-to-Agents Transition33:04 - Lightning Round: Getting Hands-On to Shorten Learning CurvesVisit our website - https://saassessions.com/Connect with me on LinkedIn - https://www.linkedin.com/in/sunilneurgaonkar/
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S9E5 - Building AI Into SaaS the Right Way: Lessons from Megh Gautam, Former CPO at Crunchbase
Sep 1200:36:35Tap to summarizeEvery SaaS company is racing to “add AI,” but most are doing it wrong. In this episode, Megh Gautam, Former Chief Product Officer at Crunchbase, reveals the hard truths behind building AI into established SaaS products. From avoiding hype-driven features to building trust through data quality and transparency, Megh shares how Crunchbase rolled out AI-powered capabilities without breaking user trust. He also breaks down the internal alignment, cross-functional execution, and relentless feedback loops required to ship AI features that actually matter.Key Takeaways -Start with Real User ProblemsAI should not be an “add-on story” — it must solve a core customer pain.Crunchbase began with AI in search, a high-usage, high-friction feature.Prioritize critical workflows over “nice-to-have” gimmicks.Data Quality Determines TrustBad data in = garbage out, especially with AI models.Crunchbase spent a decade building clean, reliable data pipelines before layering AI.Trustworthy results require grounding AI outputs in verified “truth sets.”User Trust Demands TransparencyCustomers don’t just want answers — they want to know how those answers were derived.Explainability and confidence thresholds are essential for adoption.If unsure, don’t hallucinate — caveat results and suggest alternatives.AI is a Company-Wide Effort, Not Just a Product LaunchDesigners, engineers, PMs, marketing, and GTM must move in lockstep.Pricing, packaging, and positioning are as critical as the technical build.Internal discomfort is normal — priorities will shift faster than in traditional SaaS launches.Continuous Feedback Loops Drive IterationEarly adopter programs and dense customer feedback cycles are critical.Patterns of confusion often surface only after repeated customer interactions.AI workflows blur traditional SaaS team boundaries — ownership must evolve.Chapters: 00:10 - Introduction 00:50 - Megh’s SaaS journey (Twilio, Dropbox, Crunchbase) 02:45 - AI hype vs. solving real user problems 06:05 - Why Crunchbase started with AI in search 10:17 - Data quality as the foundation for trustworthy AI 15:07 - Overcoming AI skepticism with transparency 20:01 - Aligning product, engineering, marketing, and GTM on AI launches 25:46 - Feedback loops and customer education 30:32 - Lightning Round: Megh’s favorite AI tools 36:27 - Closing thoughts and key remindersVisit our website - https://saassessions.com/Connect with me on LinkedIn - https://www.linkedin.com/in/sunilneurgaonkar/
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S9E4 - From Community to Capital ft. Max Altschuler, General Partner at GTMfund
May 21, 202500:40:22Tap to summarizeIn this powerhouse episode, Max Altschuler - founder of Sales Hacker, former VP of Marketing at Outreach, and now General Partner at GTMfund - breaks down what it takes to build and scale B2B SaaS companies with speed and substance. Max shares his journey from being an early-stage operator to becoming a SaaS investor, unpacking the real mechanics behind GTM strategy, community-driven growth, category creation, and what founders often get wrong. This is a masterclass in strategic execution and long-game thinking for SaaS leaders.Key Takeaways –1. Betting on Founders: What Drives Early-Stage InvestingFounder-market fit trumps product perfection - invest in people who are machines.Space matters: Great founders + a growing wave = potential breakout.Outreach wasn’t a spreadsheet decision - it was a conviction bet on Manny Medina's obsession and clarity.2. Strategic Distribution Is the New ProductDistribution is where the new edge is; AI levels the playing field for building.GTM is the real differentiator - your ability to generate demand at scale will define outcomes.Sales Hacker’s distribution muscle supercharged Outreach’s category dominance.3. Acquisitions Are Not Just About Revenue, They’re About VelocitySales Hacker wasn’t bought for its revenue but to compound Outreach’s strategic value.Community-led growth isn't a tactic; it’s an ecosystem asset.Integration didn’t mean conversion - it meant amplification without breaking trust.4. Lessons in SaaS Scale and GTM ExecutionDon’t underinvest in product expansion; build or buy fast when signals are clear.Self-serve isn’t optional anymore; it’s mandatory for market-wide coverage.Be obsessed, but don’t burn out your team; clarity in communication scales leadership.About the GTMfund: GTMfund is an early-stage venture fund backed by 300+ of the most respected go-to-market leaders from companies like Salesforce, Zoom, and Snowflake. It focuses exclusively on backing SaaS startups with strong GTM execution and strategic potential.Connect with Max Altschuler | Check out GTMfundVisit our website - https://saassessions.com/Connect with me on LinkedIn - https://www.linkedin.com/in/sunilneurgaonkar/
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S9E3 - Cracking Early-Stage SaaS Growth ft. Jacob Bank, CEO of Relay.app
Apr 2, 202500:43:22Tap to summarizeIn this episode of the SaaS Sessions podcast, Jacob Bank, founder of Relay.app, shares his journey from academia to startup founder, discussing the challenges of building a product in the AI space. He emphasizes the importance of validating ideas, finding early customers, and experimenting with various marketing channels. Jacob also highlights the significance of cohort retention as a measure of product-market fit and the need to balance innovation with competition in a rapidly evolving market.Key Takeaways –1. You’re not failing - your distribution isBuilding is easy; getting customers is the battlefield.Early channels (Reddit, network, cold email) only take you so far.Most startup advice is outdated or irrelevant to your context - test everything yourself.2. Validate with precision, not egoThe Mom Test changed how Jacob gathered honest feedback.10 well-run interviews can kill or greenlight an idea.Getting “likes” is not validation - retention and willingness to pay are.3. Every growth stage needs a new motion0 → 10: Scrappy hustle (Reddit, LinkedIn DMs, direct outreach).10 → 100: Partner marketing, SEO, and high-intent blog content.100 → 1000: Viral LinkedIn content + YouTube for education + community-led growth.4. PMF isn’t hype - it’s cohort retentionRetention is the only true sign of product-market fit.Competitive pressure is a forcing function to build better products.Don’t be afraid to pick a fight in a crowded space - just know your edge.Connect with Jacob Bank:🔗 Jacob Bank - https://www.linkedin.com/in/jacobbank/📅 Join his Build an AI Agent with Me sessions - https://events.relay.app🌐 Try Relay.app for free: https://relay.appRelay.app is an AI agent builder that connects your tools into smart workflows. Designed to bring humans into the loop where automation fails, Relay combines intuitive UX with AI-native capabilities, enabling teams to move faster without drowning in manual ops.Chapters:00:10 – Introduction00:50 – Jacob’s journey from academia to Google to Relay02:14 – The pain of early go-to-market and what didn’t work06:09 – Using The Mom Test to validate early MVPs07:59 – Breaking through with traction experiments10:52 – Reddit, Product Hunt, and the weak links in early GTM13:49 – From 10 to 100: What channels actually scaled15:18 – Facing the 100 → 1000 wall16:37 – Cracking virality with LinkedIn21:29 – Mid-funnel levers: YouTube and email27:13 – Competing in a mature category and why it’s a good thing33:15 – Defining and validating PMF the hard way38:27 – Retention is king—no tricks, just product40:28 – Lightning round42:41 – Final thoughts + how to join Jacob’s live AI agent sessionsVisit our website - https://saassessions.com/Connect with me on LinkedIn - https://www.linkedin.com/in/sunilneurgaonkar/
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S9E2 - How AI is Revolutionizing Attribution for Modern GTM Teams ft. Deepinder Dhingra, RevSure
Jan 17, 202500:37:21Tap to summarizeIn this episode, we dive into the evolving landscape of B2B SaaS attribution with Deepinder Dhingra, Founder and CEO of RevSure.ai. DD shares insights from his 20+ years in enterprise software, analytics, and AI, unpacking how SaaS companies can harness AI-driven attribution to improve GTM strategies. He explores the challenges of attribution complexity, the role of AI in unifying data, and actionable frameworks for building an effective attribution model. DD also shares his thoughts on the future of AI in SaaS and key misconceptions about being a founder in this space.Key Takeaways:1. The Evolution of Attribution in SaaS- Past GTM motions: Outbound, focused on sales-driven efforts.- Present complexity: Consumerization of GTM with multiple teams (marketing, SDR, BDR, sales).- Challenge: Fragmented data across tools requires a robust attribution strategy.2. AI’s Role in Attribution- Data Harmonization: AI connects data from CRMs, marketing automation, ABM tools, and offline channels.- Revenue Graphs: Building linkages across touchpoints like leads, campaigns, and opportunities.- Predictive Insights: Real-time data analysis to optimize spend and strategy.3. Common GTM Team Pitfalls- Misaligned Goals: Teams focus on “who gets the credit” rather than actionable insights.- Lack of Full-Funnel Thinking: Insights should span marketing, SDR, and sales efforts.- Overreliance on Rules-Based Models: Shift to data-driven, machine learning approaches like marketing mix models and incrementality testing.4. Building an AI-Powered Attribution Framework- Collaborative Effort: Align marketing, sales, and ops under a shared vision.- Tech Stack Audit: Ensure compatibility with your GTM motion.- Real-Time Monitoring: Use leading and predictive indicators to measure success.Lightning Round Insights:1. Fun Fact About DD: He’s a skilled pickleball player!2. Challenge to Solve in Indian SaaS: Optimizing cross-border GTM motions.3. Misconception About Founders: It’s not all fun; founders take the brunt of market brutality and drive teams for competitive speed.About RevSure.ai:RevSure.ai is revolutionizing attribution for B2B SaaS companies by leveraging AI to unify data, provide actionable insights, and optimize GTM strategies. Their AI-powered attribution models address the complexities of modern SaaS motions and enable teams to act with precision.Connect with DD:LinkedIn - https://www.linkedin.com/in/deepinder-singh-dhingra-66bb54/RevSure - https://www.revsure.ai/Chapters:01:05 - Intro & DD’s Journey in SaaS02:05 - Evolution of Attribution in SaaS07:27 - Complexity in GTM Motions and Data Fragmentation12:10 - AI’s Role in Attribution15:10 - Common GTM Team Pitfalls19:02 - Building an AI-Powered Attribution Framework23:26 - KPIs for Attribution Success27:42 - Future of AI in Attribution30:17 - Balancing AI with Human Oversight32:22 - Lightning Round36:42 - Closing Thoughts#b2bsaas #b2b #attribution #marketing #saasVisit our website - https://saassessions.com/Connect with me on LinkedIn - https://www.linkedin.com/in/sunilneurgaonkar/
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S9E1 - Elevating Customer Onboarding for Revenue Growth ft. Sri Ganesan, CEO of Rocketlane
Jan 3, 202500:41:16Tap to summarizeEpisode Summary:Srikrishnan Ganesan, Founder, and CEO of Rocketlane, joins the SaaS Sessions Podcast to share actionable insights on customer onboarding—a crucial yet often overlooked driver of SaaS success. Sri dives deep into why onboarding sets the foundation for long-term customer satisfaction, retention, and expansion, and offers strategies to optimize this critical phase. This conversation is packed with transformative ideas for SaaS founders and operators, from avoiding common onboarding pitfalls to leveraging AI and standardized processes.Key Takeaways:1. Onboarding as a Strategic Driver- The first 30-90 days are make-or-break: onboarding directly influences churn and Net Revenue Retention (NRR).- Poor onboarding can result in 25-30% of customers failing to go live, jeopardizing renewals and expansions.- Early-stage SaaS companies often lack the rigor to drive implementation success, resulting in disengaged customers.2. Common Onboarding Pitfalls and How to Address Them- Lack of Rigor: Companies often go at the customer’s pace instead of setting clear timelines.- Order-Taking Approach: Teams fail to be prescriptive, waiting for customer direction instead of sharing best practices.- Disorganized Operations: Reliance on spreadsheets and hero-driven processes undermines scalability and consistency.- Solution: Implement standardized processes, use governance frameworks, and prioritize system-driven operations.3. The Role of Leadership and Process Design- Founders often stretch post-sales teams, delaying investments in specialized onboarding leadership.- Invest in systems that track effort, milestones, and outcomes to scale onboarding.- Standardize touchpoints like kickoff decks, project plans, and escalation paths to drive a consistent and professional experience.4. Leveraging Technology and AI for Better Onboarding- Tools like Rocketlane provide visibility and streamline processes for both customers and internal teams.- Use AI to automate repetitive tasks, identify early warnings, and enhance follow-up communications.- Fast and efficient onboarding drives 2x faster expansions and greater advocacy from happy customers.Lightning Round Insights:What Sri Wishes He’d Known Starting: How transformative AI would become and its potential to fundamentally reshape product development.Favorite AI Tools:- Avoma for sales insights.- Rocketlane’s own AI-driven features to improve onboarding experiences.Book Recommendations:- Made to Stick by Chip and Dan Heath – Learn to package ideas that resonate and stick with your audience.- Competing Against Luck by Clayton M. Christensen – Understand the "Jobs to Be Done" framework for product development.About Rocketlane:Rocketlane is a leading customer onboarding and professional services automation platform, empowering SaaS companies to deliver seamless and efficient onboarding experiences. By streamlining collaboration, improving accountability, and accelerating time-to-value, Rocketlane helps businesses improve retention and expand revenue opportunities.Chapters:00:50 - Sri’s Journey: From Freshworks to Rocketlane01:47 - The Current State of SaaS Onboarding04:15 - Key Challenges in SaaS Onboarding07:39 - Building Rigor and Governance in Onboarding15:23 - Celebrating Go-Lives and Building Advocacy19:15 - The Impact of Faster Onboarding on Retention and Expansion27:27 - Ripple Effects of Poor Onboarding34:04 - Leadership’s Role in Driving Onboarding Excellence37:04 - Lightning RoundVisit our website - https://saassessions.com/Connect with me on LinkedIn - https://www.linkedin.com/in/sunilneurgaonkar/
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