Front Lines

We spoke with Michael Bamberger, CEO of Tetra Insights about their path to becoming a leading enterprise customer research platform. Here are the key go-to-market lessons from their journey: → Challenge industry assumptions. Tetra discovered that qualitative customer insights in video form were more influential than quantitative data for driving decisions. This counterintuitive insight shaped their entire product strategy. → Spot workflow evolution early. They identified a crucial shift: enterprise customers wanted to own their research process rather than outsource it. This observation led them to build tools for internal teams instead of offering services. → Create content that solves strategic problems. Rather than following industry trends, Tetra developed webinars addressing how research teams could prove ROI during budget scrutiny. This led to six-figure deals from webinar viewers alone. → Design for enterprise embedding. By making their platform part of client onboarding for entire product teams, they achieved 3x year-over-year growth within accounts. The key was becoming essential to customer workflows. → Prioritize technical excellence from day one. Early attempts to save money with less experienced engineers proved costly. They learned that senior technical talent is crucial for building enterprise-grade platforms that can scale. → Align with executive priorities. Instead of just selling features, they positioned their platform as essential for achieving research ROI and team efficiency - tying directly to C-suite concerns about costs and impact. These insights from Tetra Insights show how deep market understanding and strategic positioning can drive enterprise adoption. Listen to the full conversation with Michael Bamberger on Category Visionaries to learn more about building enterprise SaaS platforms today: https://lnkd.in/ep9UAmDg

We spoke with René Janssen, founder of Lepaya, about revolutionizing the $400B enterprise training market. Here are the key go-to-market lessons from their journey: → Kill bad strategies fast. After just 3 months, Lepaya abandoned their marketplace model when they realized every deal required two separate sales cycles. Sometimes the "platform play" isn't the answer. → Reframe market maturity as opportunity. While competitors saw a traditional market needing minor improvements, Lepaya identified how declining productivity growth (from 6% to 1%) created urgency for transformation. → Challenge false dichotomies. Instead of choosing between fully digital or fully in-person training, Lepaya built a hybrid model combining technology's scale with human expertise where needed. → Make ROI concrete and measurable. They moved beyond "happy sheets" to track specific metrics: retention cost savings, productivity gains per employee, and behavioral changes 6 months post-training. → Map the full decision ecosystem. Rather than generic marketing, Lepaya created research-driven content addressing each stakeholder's specific needs in complex enterprise sales cycles. These insights from Lepaya show how rethinking traditional categories can unlock massive opportunities in mature markets. Listen to the full conversation with René Janssen on Category Visionaries to learn more about their approach to transforming enterprise training today: https://lnkd.in/d2yMmekW

We spoke with Mykolas Rambus, CEO of Hush, about their path to doubling revenue quarter-over-quarter in the enterprise privacy space. Here are the key go-to-market lessons from their remarkable journey: → Invert the sales conversation. Instead of pitching features, Hush leads with an "outside-in diagnostic" showing security leaders their actual vulnerabilities - including surprising leaks from sources like executive family members' social media. → Transform elite solutions into scalable products. Hush took privacy protection that previously required $100k+ retainers and three-letter agency expertise, making it accessible to every employee in an organization. → Make corporate mandates feel personal. Rather than another top-down IT initiative, Hush positions their solution around individual identity theft protection (affecting 1 in 17 Americans yearly), driving voluntary adoption. → Build for crisis activation. Recognizing that security leaders make buying decisions during incidents, Hush focused on building presence in peer networks rather than traditional marketing channels. → Remove adoption friction entirely. Instead of complex onboarding, Hush requires minimal data fragments to start showing personal vulnerability, letting employees control their own privacy protection process. → Get ahead of threat evolution. By positioning for the rise of AI-powered social engineering ($20 deepfake tools), Hush built enterprise solutions before personal privacy threats became business risks. These insights from Hush demonstrate how rethinking traditional enterprise security go-to-market can drive rapid growth. Listen to the full conversation with Mykolas Rambus on Category Visionaries to learn more about their approach to privacy innovation today: https://lnkd.in/e4dSdVrC #enterprisesecurity #privacy #startup #venturecapital #b2bsaas

Cassandra Gholston founded PartnerTap, a partner orchestration platform that's raised $9 million to solve a critical enterprise sales challenge. As a software sales leader, she noticed something: the most successful reps weren't cold calling—they were working with partners. But there was a problem: partner data was locked away in CRM systems, making collaboration nearly impossible. "To try to figure out who are all the Cassandras in my territory at different partner companies was so hard," she recalls. The stakes were high. In today's enterprise deals: → 13 people make consensus buying decisions → Each is influenced by 7 different partners → That's 91 people potentially affecting a single sale Cassandra recognized this was unsustainable without data sharing. She methodically prepared for entrepreneurship: → Banked commission checks for over a year → Built wireframes nights and weekends → Tested concepts with future users PartnerTap launched with a hypothesis: connect sellers directly with partner data. It quickly failed. "We thought we're just going to connect sellers with partner data without the partner team," she explains. "We realized pretty soon that we had to build a whole other module and pivot." This meant shifting from a bottoms-up to a top-down approach, starting with partner teams, not sellers. Another unconventional decision: targeting the largest enterprises immediately. "When you decide you're going to sell into the largest organizations in the world as a startup, that's a hard road. Most startups are going to go after smaller companies first." Their first customer? ADP—one of the world's largest payroll providers. The champion who backed them declared, "I would bet my job on this." This strategic choice created a network effect: → ADP became a customer → ADP's partners became customers → Those partners' partners became customers Today, PartnerTap serves giants like Salesforce and SAP, helping them securely share CRM data to identify mutual opportunities. Their core value—"customer love"—isn't just a slogan. Their proof? Zero enterprise customer churn since founding, even through COVID-19. Cassandra's unconventional journey offers a powerful lesson for founders: sometimes the hardest path—challenging industry data-sharing norms and targeting enterprise from day one—creates the most defensible business. Listen to the full conversation with Cassandra Gholston on Category Visionaries today:?https://lnkd.in/ex77czUj

James O'Brien ?? co-founded Ducky, an internal data search for LLMs that's raised $2.7 million in funding. Three months ago, their product was a customer support solution that was performing "fine" but not venture-scale. The turning point came when they noticed developers repeatedly asking for access to their underlying knowledge retrieval infrastructure. James and his co-founder Hong faced a critical decision: → Continue pushing a product in a marketing-heavy category they weren't skilled at → Or pivot to a developer tool that matched their technical strengths They chose to validate the pivot methodically: → Time-boxed exploration to three weeks → Built multiple prototypes → Showed them to potential customers The results were clear – their ML infrastructure was the more promising opportunity. Their pivot from customer support to devtools was completed in under three months, and the market response has exceeded expectations. What makes their approach unique is how they're cutting through the AI hype: → They focus on business value, not AI capabilities → They discovered many companies are tasked to "do something with AI" without clear objectives → They help developers optimize LLM usage without requiring AI expertise Their usage-based pricing creates natural alignment: "If you use it and it works, you will use it more. And that means that we're doing our job." Ducky operates as a pre-LLM compute layer that finds and transforms internal business data for optimal LLM consumption. While based in Nashville rather than Silicon Valley, this has become an advantage. James builds relationships through Nashville's tight-knit startup community while targeting developers who need their specialized infrastructure. The most important lesson? "If you never know I exist, but your tool works way better than anybody else's, that is us doing our job super well." Check out our latest Category Visionaries episode with James O'Brien to learn how Ducky found product-market fit by becoming the infrastructure their customers actually needed here:?https://lnkd.in/eRErTCAU

Redefining Supplemental Health Insurance: GTM Lessons from Ansel Health We recently sat down with Veer Gidwaney, CEO of Ansel Health, to discuss how they're transforming supplemental insurance through automation and strategic partnerships. Here are the key go-to-market insights from their journey to securing Fortune 500 clients: → With 100M Americans facing medical debt, Ansel identified that traditional supplemental insurance products had lost product-market fit → Instead of competing directly, they built a platform powering other insurance companies - creating a coalition-based distribution strategy → By owning their core technology stack, they automated 75% of claims processing - achieving industry-leading NPS scores in the 80s → Their platform approach helped secure their first Fortune 500 clients by leveraging established brands and distribution channels → Through product innovation, they're working to expand the supplemental insurance market to 4-5x its current size These insights from Ansel Health demonstrate how rethinking traditional insurance models can drive rapid B2B growth. Listen to the full conversation with Veer Gidwaney on Category Visionaries to learn more about their approach to insurance innovation today: https://lnkd.in/exP-XYXJ #B2B #InsurTech #ProductStrategy #GTM #Startups

We spoke with Meryem Arik, founder of TitanML, about navigating the pre and post-ChatGPT landscape in AI infrastructure. Here are the key go-to-market lessons from their journey: → Invert the technical founder's playbook. Titan ML discovered that "building is easy and finding things people want to buy is hard." They now validate through sales before building features. → Walk away from custom traps. When a major financial institution offered a lucrative contract for custom features, they declined. This counter-intuitive decision protected their vision of building scalable infrastructure. → Make transparency your sales strategy. Rather than traditional sales tactics, they openly discuss open source alternatives and DIY approaches with developers. This educational approach built deeper trust with technical buyers. → Create your category proactively. Instead of fitting into existing boxes like "deployment" or "inference," they're actively defining a new infrastructure category that spans both. → Navigate market timing shifts. Pre-ChatGPT, they faced skepticism about market size. Post-ChatGPT, they had to help confused buyers develop AI adoption frameworks. Different markets require different approaches. These insights from Titan ML show how technical founders can build trust and scale in emerging markets. Listen to the full conversation with Meryem Arik on Category Visionaries to learn more about bringing AI infrastructure to market here: https://lnkd.in/dcgNNfn8 #AIInfrastructure #StartupLessons #ProductStrategy #GTM #B2B

Building E-commerce Infrastructure: Lessons from Max Retail's Journey We spoke with Melodie van der Baan, CEO of Max Retail, about transforming from a manual inventory matching service to a $10M e-commerce infrastructure platform. Here are the key go-to-market lessons from their journey: → Let behavior guide product evolution. Instead of building a marketplace first, Max Retail started by manually matching excess inventory between retailers. This revealed critical patterns in customer behavior and unit economics before writing a single line of code. → Recognize when customers reject your model. When retailers said "We don't want to buy. We got bills. We just want to sell," Max Retail completely pivoted their approach from facilitating exchanges to enabling new sales channels. → Use market accidents as intelligence. An accidental email blast to both retailers and brands revealed massive untapped demand from brand manufacturers. This "mistake" led to discovering their most profitable customer segment. → Build infrastructure for trapped inventory. Max Retail realized independent retailers couldn't access marketplaces because "their data is too dirty, their inventory is too fragmented." By solving these underlying barriers, they unlocked a 2-million retailer market. → Focus on customer revenue first. By structuring their model where "we win when they win," Max Retail grew average monthly retailer payouts from $151 to $1,200. This alignment drove 55% monthly active usage without traditional marketplace incentives. These insights from Max Retail show how letting real market behavior guide your evolution can unlock massive opportunities. Listen to the full conversation with Melodie van der Baan on Category Visionaries to learn more about building infrastructure for independent retail here: https://lnkd.in/er9Sw_Jx #B2B #Startup #RetailTech #MarketplaceTech #GoToMarket

We spoke with Matthew Stoudt, Founder of AppliedVR, about their path to becoming the first FDA-approved VR therapy for chronic pain. Here are the key go-to-market lessons from their journey: → Build evidence before scale. AppliedVR made building clinical validation their early mantra, creating an "unparalleled body of evidence" that enabled FDA approval and insurance coverage. → Design for real use, not ideal scenarios. They scrapped technically impressive features like biometric monitoring when home testing revealed they created adoption friction. As Matthew notes, "If it's complicated, if it's hard to use... it's going to sit in a corner and gather dust." → Choose strategic beachheads wisely. Instead of targeting the broad consumer market, they focused on the VA where 2,170 facilities were already using VR and 1.5M veterans needed chronic pain treatment. → Master the regulatory pathway. They became the first FDA-approved VR treatment by methodically building evidence and institutional relationships, creating a moat against competitors. → Think distribution-first. While others focused on technology, AppliedVR built the prescription and insurance infrastructure needed for sustainable scaling. → Solve the whole problem. They recognized chronic pain required more than just symptom management, developing an 8-week program that taught lasting pain management skills. These insights from AppliedVR show how methodical market development can enable breakthrough innovation in regulated markets. Listen to the full conversation with Matthew Stoudt on Category Visionaries to learn more about their approach to creating a new category of medicine here: https://lnkd.in/eScMHX5d #HealthTech #Innovation #StartupLessons #DigitalHealth #VirtualReality

Canay Deniz founded Ren Systems to solve a problem he initially didn't believe existed. When high-profile dealmakers (including a former SEAL Team 2 commander and Fortune 200 CEOs) complained about missing important relationship signals, Canay's first thought was: "These guys just don't know how to use LinkedIn." But after interviewing hundreds of professionals, he discovered a universal truth: the level of noise is overwhelming for people whose success depends on relationships. Ren Systems launched on March 1, 2020 – the day before the world shut down. While most startups rush to market, Canay spent two full years refining the product before actively selling: "We knew we needed to take a different approach. We knew we needed to get the end user experience right." This patience paid off. Their early users were an "insane" group of beta testers – high-profile executives who typically won't try new software. The experience taught them something critical: their users (senior dealmakers) had zero patience for learning curves. "If it doesn't work within 5 seconds, I already lost interest." They built a product that filtered millions of data points to answer one simple question: not WHO to contact or HOW, but WHEN and WHY you should reach out. This differentiation helped them raise $8.8M (including strategic investment from ZoomInfo) and build a pipeline so strong that their 12-person team is "struggling to process the deals already there." Perhaps most interesting is their contrarian bet: In a world where AI is supposed to automate everything, Ren strengthens the one thing AI can't replace – human relationships. Listen to our conversation with Canay to learn how Ren Systems is systematizing serendipity for dealmakers in commercial real estate, management consulting, and investment banking here: https://lnkd.in/ehHr8tcD