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Forget Product-Market Fit – Here’s What Early-Stage Startups Should Really Chase The Startup Myth Everyone Believes If you’ve spent any time around investors, accelerators, or startup Twitter, you’ve probably heard the same advice over and over again: “You just need to find product-market fit.” It’s treated like a holy grail — that magical moment when your product perfectly aligns with what customers want, and growth takes off on its own. Founders chase it endlessly, pitch decks worship it, and entire strategies are built around it. But here’s the truth we’ve seen first-hand working with early-stage founders at Product Siddha: product-market fit isn’t real in the way people think it is. Markets evolve, customers change, and what feels like “fit” today may completely fall apart in six months. Instead of chasing an illusion, smart startups focus on something more practical and powerful – continuous validation and learning. Why Product-Market Fit Misleads Founders For early-stage startups, the concept of “fit” assumes that both your product and your market are stable enough to align perfectly. But in reality, everything is in motion. Your customers are still figuring out what they need. You’re still refining what you’re building. And competitors are constantly shifting the landscape. When founders chase a static idea of “fit,” they often fall into these traps: Waiting too long for “perfect validation” before launching. Overbuilding features that customers never asked for. Mistaking early enthusiasm for sustainable traction. Treating feedback as a finish line instead of a compass. We’ve seen early teams spend months (sometimes years) perfecting an MVP they never actually test with real users – because they’re waiting to “find fit.” What they should be doing is testing faster, learning faster, and adapting faster. What Actually Drives Startup Success The startups that grow successfully aren’t the ones that “found” fit – they’re the ones that learn faster than everyone else. They don’t treat product-market fit as a milestone. They treat it as a moving target and build systems to adjust continuously. At Product Siddha, we help founders build MVPs that are designed for validation velocity, not just launch speed. That means: Getting early users involved before the full product exists. Measuring real behavior, not just survey opinions. Iterating weekly based on what data and conversations reveal. If you can shorten your learning loop, you can outpace competitors who are still waiting for validation. The Continuous Validation Framework Instead of chasing product-market fit, we help startups build around three principles that create ongoing alignment with customers and markets: Customer Intimacy — deeply understanding your users’ behavior and context. Rapid Experimentation — testing small ideas fast to learn what works. Honest Measurement — tracking metrics that actually matter, not vanity ones. Let’s unpack each one. 1. Customer Intimacy: Stop Guessing, Start Observing Most early-stage teams think they understand their users because they ran a few interviews. But interviews only show what customers say they do, not what they actually do. Customer intimacy means spending real time watching how users interact with your MVP, even if it’s just a prototype, a Figma mockup, or a landing page test. At Product Siddha, we encourage founders to spend at least 30% of their time each week in direct contact with users. Example weekly breakdown: Activity Time (hrs/week) Purpose Observe users in real workflows 4 Identify friction and unmet needs Review product usage data 3 Spot hidden behavior trends Conduct customer calls 3 Hear the language of their pain points Reflect & plan experiments 2 Turn observations into testable ideas Success indicators: Product decisions reference specific customer stories. You can clearly describe your users’ day-to-day behavior. You adjust features based on what people actually do, not what they say. 2. Rapid Experimentation: Learn Fast, Fail Small Startups often think validation requires big product launches. In reality, it’s about running small, controlled experiments that give you real insights without wasting resources. Here’s a simple cycle we use with founders: Week Step What You Do 1 Form Hypothesis “If we add X feature, engagement will increase.” 1 Design Mini-Test Create a quick MVP, landing page, or clickable demo. 2 Launch to Small Group Get 10–20 real users to interact. 2 Measure & Analyze Collect both qualitative and quantitative feedback. 2 Decide & Iterate Keep, pivot, or discard based on data. Target: Run 8–12 micro-experiments per month. Goal: Validate or kill 3–4 key assumptions before scaling. The faster you run this loop, the faster your product evolves toward real traction. 3. Honest Measurement: The Metrics That Actually Matter Many founders love dashboards full of signups and traffic charts, but those don’t tell you whether your product truly delivers value. Real validation comes from retention and engagement, not acquisition. Here’s how we advise startups to measure progress: Metric Why It Matters What to Track Retention Are users coming back? 7-day, 30-day, 90-day active usage Activation Are users reaching their “aha” moment? % of users completing core action Expansion Are customers deepening engagement? Frequency of use, upsells, referrals Feedback Loops Are you learning from users? # of actionable insights per week It’s not about “how many” people signed up – it’s about how many stuck around because they found real value. Why This Shift Matters for Early-Stage Startups The old “product-market fit” mindset made sense when markets moved slowly. Today, user expectations change weekly. Competitors launch in months. New AI tools appear overnight. Waiting to “find fit” is like waiting for still water in a storm. Founders who focus on continuous learning instead of perfect fit: Ship faster. Adapt faster. Build products people genuinely want, because they keep listening. At Product Siddha, we’ve seen startups that work this way: Pivot earlier before burning through their runway. Discover surprising use cases through real observation. Raise funding faster because their insights are grounded in data, not theory. Mindset Comparison: Old vs. New Category Product-Market Fit Mindset Continuous Validation Mindset Goal Find the “perfect” fit Keep improving alignment Launch Philosophy Wait until ready Ship small, learn fast Customer Interaction Occasional interviews Weekly observation

Framer vs Webflow: Best No-Code CMS for Interactive Design and Animations The No-Code Design Platform Landscape Designers and product teams increasingly seek tools that allow them to create sophisticated websites without extensive coding knowledge. The rise of no-code platforms has democratized web design, enabling people with visual design skills to build functional, interactive sites that previously required developer involvement. Among these platforms, Framer and Webflow have emerged as leading choices for teams prioritizing interactive design and sophisticated animations. Both tools offer powerful capabilities, yet they approach web design from different philosophical starting points and serve somewhat different use cases. Understanding these distinctions helps teams select the platform that aligns with their specific needs and working styles. Framer’s Design-First Philosophy Framer originated as a prototyping tool before evolving into a full website builder. This heritage shows in its interface and workflow, which feel familiar to designers accustomed to tools like Figma or Sketch. The platform emphasizes visual design and animation as primary concerns, with technical implementation details handled largely behind the scenes. The Framer interface uses a layer-based approach where designers stack and arrange elements visually. Creating animations happens through an intuitive timeline interface that lets designers define motion without writing code. This approach makes Framer accessible to people with strong visual design skills but limited technical backgrounds. Framer excels at micro-interactions and smooth transitions. Designers can create hover effects, scroll-triggered animations, and component state changes with relative ease. The platform generates performant code automatically, handling optimization and browser compatibility without requiring designer intervention. Content management in Framer has improved significantly in recent iterations. The platform now includes CMS functionality that allows content editors to update text, images, and other elements without accessing the design interface. This separation of design and content makes Framer viable for sites that require regular updates. Webflow’s Structure and Control Webflow takes a different approach, giving designers more direct control over the underlying web structure. The platform exposes concepts like flexbox, grid layouts, and CSS properties through a visual interface. This design philosophy assumes users have some understanding of how websites work at a technical level, even if they cannot write code fluently. The Webflow designer operates more like a visual CSS editor than a pure design tool. Users define styles, create reusable classes, and manage responsive behavior across different screen sizes with granular control. This approach produces cleaner code and greater flexibility for complex layouts, but it also requires a steeper learning curve. Animation capabilities in Webflow center around its interactions panel, which allows designers to trigger animations based on page load, scroll position, hover states, and clicks. The system uses a trigger-and-action model where designers define what event should initiate which animation. Complex animation sequences can be built by chaining multiple actions together. Webflow’s CMS represents one of its strongest features. The platform provides a robust content management system with custom collection types, dynamic filtering, and powerful template capabilities. Content-heavy sites like blogs, portfolios, and directories work particularly well in Webflow because of this CMS flexibility. Framer vs Webflow Feature Comparison Feature Framer Webflow Learning Curve Gentler for pure designers Steeper, requires web concepts Animation Interface Timeline-based, intuitive Trigger-action model Layout Control Visual layer stacking CSS-based with flexbox/grid CMS Capabilities Basic to intermediate Advanced and flexible Component System React-based components Symbol and class system Code Export Limited Full code export available Collaboration Real-time design collaboration Designer and editor roles Pricing Model Per site Per project and hosting Interactive Design Capabilities Both Framer and Webflow support sophisticated interactive design, but they achieve it through different mechanisms. Framer’s component-based architecture allows designers to create reusable elements with built-in interactivity. These components can have multiple states, respond to user input, and include animations that trigger based on those states. Webflow’s interaction system provides fine-grained control over animation timing, easing curves, and chained effects. Designers can create complex scroll-based animations where different elements move at different rates, creating parallax effects or revealing content progressively as users navigate down the page. For teams at Product Siddha building interactive product showcases or marketing sites, both platforms offer adequate tools. The choice often comes down to whether the team prefers Framer’s component-based approach or Webflow’s trigger-action model for defining interactions. Animation Performance and Quality Animation performance matters significantly for user experience. Poorly optimized animations create janky, unprofessional experiences that frustrate users and harm conversion rates. Both Framer and Webflow generate performant animations, but they handle this differently. Framer uses React and Framer Motion under the hood, producing JavaScript-based animations that integrate tightly with component behavior. The platform automatically optimizes animations for performance, using GPU acceleration and efficient rendering techniques. Designers rarely need to think about performance optimization explicitly. Webflow generates CSS animations and transitions whenever possible, falling back to JavaScript only when necessary. CSS animations generally perform better than JavaScript alternatives, particularly on mobile devices. Webflow also provides tools for previewing animations at different frame rates, helping designers identify performance issues before publishing. Responsive Design Workflows Modern websites must work across devices ranging from phones to large desktop displays. Both platforms provide tools for creating responsive designs, though their approaches differ. Framer handles responsiveness primarily through breakpoints where designers define how layouts adapt at different screen widths. The platform includes a mobile-first preview and allows designers to override specific properties at each breakpoint. Auto-layout features help components resize intelligently as screen dimensions change. Webflow gives designers more granular control over responsive behavior. Every property can be adjusted independently at each breakpoint. This flexibility allows for precise control but requires more manual work to ensure designs adapt appropriately across all screen sizes. For complex responsive layouts with significant layout changes across breakpoints, Webflow’s detailed control proves valuable. For simpler sites where content primarily reflows, Framer’s streamlined approach may suffice. Content Management Considerations Sites requiring frequent content updates need capable content management systems. Webflow’s CMS has matured into a powerful tool suitable for content-heavy sites. Content editors can manage blog posts, case studies, team profiles, and other dynamic content through an intuitive

Unlocking Innovation: Product Siddha’s Approach to the New Product Development Process The Challenge of Systematic Innovation Every organization wants to create products that resonate with customers and generate sustainable revenue. Yet most product initiatives fail to meet expectations. Some never reach the market. Others launch but fail to gain traction. Many succeed initially but cannot maintain momentum as market conditions shift. These failures rarely result from lack of effort or talent. More often, they stem from inadequate processes for moving from initial concept through development and into market success. Organizations need structured approaches that guide decision making while remaining flexible enough to adapt as learning occurs. Product Siddha has developed a new product development process that addresses these challenges. This approach combines proven frameworks with practical adaptations based on real-world experience across multiple industries and product types. Discovery: Understanding Problems Worth Solving The new product development process begins with thorough discovery work. This phase focuses on understanding customer needs, market dynamics, and competitive positioning before committing resources to building anything. Many organizations rush through discovery, eager to start development. This impatience costs them later when products miss the mark. Discovery involves multiple research methods working in concert. Customer interviews reveal pain points and desired outcomes. Market analysis identifies opportunities and constraints. Competitive assessment shows what alternatives exist and where gaps remain. Technical exploration determines what solutions are feasible given current capabilities and reasonable investments. Product Siddha structures discovery around specific questions that need answers. What problems do target customers face? How do they currently address these problems? What would make a solution compelling enough to change behavior? What are customers willing to pay? Which customer segments offer the best opportunities? The discovery phase produces clear documentation of findings, including customer profiles, problem statements, and opportunity assessments. This foundation guides all subsequent work and provides a reference point when difficult trade-offs arise during development. Concept Development and Validation Once discovery establishes a solid understanding of the opportunity, the new product development process moves into concept development. This phase translates insights into concrete product concepts that can be evaluated and refined. Concept development generates multiple possible solutions rather than converging immediately on a single approach. This divergent thinking often reveals options that would not emerge if teams jumped directly to implementation. Different concepts might serve different customer segments, use different business models, or take varying technical approaches to solving the same core problem. Each concept gets developed enough to enable meaningful evaluation. This typically includes value propositions, high-level feature descriptions, rough business models, and technical feasibility assessments. The goal involves creating sufficient clarity to make informed choices about which concepts warrant further investment. Validation testing provides reality checks on concepts before heavy development begins. Product Siddha uses various validation techniques depending on the product type and market context. These might include customer surveys, landing page tests, prototype demonstrations, or small-scale pilots with friendly customers. Product Siddha’s Development Process Phases Phase Key Activities Primary Outputs Success Criteria Discovery Customer research, market analysis Problem definition, opportunity assessment Clear understanding of customer needs Concept Development Ideation, evaluation, validation Product concepts, validation results Validated concept with market evidence Planning Roadmap creation, resource allocation Development plan, success metrics Aligned team with clear direction Build & Test Iterative development, user testing Working product increments Functional product meeting requirements Launch Preparation Go-to-market planning, training Launch materials, trained teams Ready for market introduction Market Introduction Phased rollout, feedback collection Live product, user data Active users demonstrating value Strategic Planning for Execution After validation confirms a concept worth pursuing, careful planning sets the stage for efficient execution. The planning phase of the new product development process defines what will be built, in what sequence, and with what resources. Product roadmapping translates the validated concept into a sequence of deliverable increments. Rather than planning the entire product in detail upfront, Product Siddha emphasizes planning the first increment thoroughly while maintaining flexibility for later phases. This approach accommodates learning that occurs during development without requiring complete replanning when assumptions prove incorrect. Resource planning ensures teams have the necessary skills, tools, and time to execute effectively. This includes identifying any capability gaps that need addressing through hiring, training, or partnerships. Clear resource plans prevent common problems like assigning work to teams that lack required expertise or scheduling work without accounting for other commitments. Success metrics get defined during planning so everyone understands how the product’s performance will be evaluated. These metrics connect to business objectives and customer outcomes rather than focusing solely on completion of features. Well-defined metrics guide prioritization decisions throughout development. Iterative Build and Testing Cycles The construction phase uses iterative cycles that build working increments, test them with users, and incorporate feedback before proceeding. This approach surfaces problems early when they remain relatively easy and inexpensive to address. Each iteration produces something testable. Early iterations might focus on core functionality that delivers the primary value proposition. Later iterations add supporting features, refinements, and optimizations. The sequence gets determined by what provides the most learning about the product’s viability and value. User testing occurs throughout development rather than only after completion. Product Siddha involves representative users in evaluating each increment to ensure the product remains aligned with actual needs. This continuous validation prevents the common scenario where teams build something impressive from a technical perspective that fails to resonate with its intended audience. Technical quality receives appropriate attention throughout the new product development process. While early increments may take shortcuts to enable rapid learning, fundamental architectural decisions get made thoughtfully. Code reviews, testing practices, and documentation standards help maintain product quality as development progresses. Preparing for Market Introduction As development nears completion, focus shifts to preparing for successful market introduction. This involves more than just finishing the product. It requires coordinating multiple functions to ensure smooth launch and adoption. Go-to-market planning defines how the product will reach customers. This includes positioning and messaging, pricing strategy, distribution channels, and promotional activities. Product Siddha works with clients to ensure go-to-market plans align with

MVP vs Prototype: What Founders Need to Know Before Investing The Confusion That Costs Founders Money Many founders waste significant time and capital because they misunderstand what they should build first. The terms “prototype” and “minimum viable product” get used interchangeably in casual conversation, leading entrepreneurs to invest in the wrong thing at the wrong time. This confusion creates real consequences: delayed market entry, depleted resources, and missed opportunities to learn from actual users. Understanding the distinction between these two approaches helps founders make better decisions about where to invest their limited resources. Each serves a different purpose in the product development process, and choosing the right one depends on what questions you need answered at your current stage. What a Prototype Actually Is A prototype exists to demonstrate an idea and test assumptions about user interaction and feasibility. It can range from paper sketches to interactive digital mockups to functional demonstrations built with no-code tools. The defining characteristic of a prototype is that it does not need to work as a real product. It only needs to appear functional enough to gather meaningful feedback. Prototypes help answer questions like: Do users understand the concept? Can they navigate the interface? Does the proposed solution address their actual problems? Will the technical approach work at all? These questions can often be answered without writing production-quality code or building scalable infrastructure. The investment required for prototyping typically measures in days or weeks rather than months. Founders can test multiple variations quickly and inexpensively. A designer can create interactive prototypes using tools like Figma that feel real to users during testing sessions but contain no actual functionality behind the interface. Understanding MVP Development A minimum viable product represents something fundamentally different. An MVP must actually work for real users in real situations. It delivers genuine value, even if that value is limited compared to the full product vision. Users can accomplish meaningful tasks, and the product can begin generating the data and feedback necessary for informed decisions about future development. MVP development requires real engineering work. The product needs functional backend systems, reliable data storage, and code that can handle actual usage. While an MVP deliberately omits many planned features, what it does include must work properly. Users will not tolerate a product that constantly breaks or loses their data, regardless of how early-stage it claims to be. The investment in MVP development typically ranges from several weeks to a few months, depending on complexity. The costs are substantially higher than prototyping because you are building something that must function in production environments with real users. Product Siddha guides founders through MVP development by helping them identify the absolute minimum feature set that can deliver real value. This process prevents the common mistake of building an MVP that includes too much, which wastes resources and delays learning. Key Differences Between Prototypes and MVPs Characteristic Prototype MVP Purpose Test concepts and assumptions Validate market demand Functionality Can be simulated or fake Must work reliably Users Internal team and test participants Real customers in real situations Timeline Days to weeks Weeks to months Investment Low (hundreds to low thousands) Moderate to high (thousands to tens of thousands) Technical Debt Not a concern Must be managed carefully Revenue Never generates revenue Can begin monetization When to Build a Prototype First Prototyping makes sense when you have fundamental uncertainties about your product concept. If you are unsure whether users will understand your solution, whether the interface makes sense, or whether the technical approach is even feasible, a prototype provides answers at minimal cost. Founders working in unfamiliar problem spaces benefit especially from prototyping. If you are creating a product for an industry you do not know well, a prototype lets you test your understanding before committing significant resources. You can show it to potential users, watch how they interact with it, and identify misunderstandings early. Hardware products almost always require prototyping before MVP development. The costs of physical production make it prohibitive to iterate through multiple full builds. Prototypes let hardware founders test form factors, materials, and functionality before investing in manufacturing. When to Move Directly to MVP Development Some situations warrant skipping prototyping and moving directly to MVP development. If you have deep domain expertise and high confidence in your solution approach, extensive prototyping may provide limited additional value. The faster path to market learning comes from building something real that users can actually adopt. Products in well-understood categories with clear user expectations often benefit from this approach. If you are building a familiar type of product with a specific innovation or improvement, you probably understand enough about user needs and behavior to design an effective MVP without extensive prototyping. Competitive pressure can also influence this decision. In fast-moving markets where first-mover advantage matters, the time spent on prototyping might allow competitors to establish positions that become difficult to challenge. However, founders should be cautious about skipping validation steps due to competitive anxiety alone. The Sequential Approach Most founders benefit from using prototypes and MVPs sequentially rather than choosing one or the other. Start with quick prototypes to test fundamental assumptions and refine your understanding. Once you have reasonable confidence in the basic approach, move to MVP development to validate actual market demand and gather real usage data. This sequential approach provides several advantages. It surfaces major problems while they remain cheap to fix. It builds confidence among team members and investors that the product addresses real needs. It creates opportunities to refine positioning and messaging before investing in production-quality development. Product Siddha often works with founders who attempted to skip prototyping and built MVPs that missed the mark. Helping these companies course-correct costs more than proper validation would have initially. The pressure to salvage sunk costs can lead to throwing good money after bad rather than acknowledging mistakes and adjusting direction. Common Mistakes in Both Approaches Founders frequently build prototypes that are too elaborate. They invest in polish and details that do not help

Why Modern Product Managers Need to Think Like Growth Hackers The Convergence of Two Disciplines Product managers traditionally focused on building features, managing roadmaps, and coordinating development teams. Their success was measured primarily by shipping products on time and meeting technical specifications. This approach worked well when markets moved slowly and competition remained predictable. The current business environment demands a different approach. Markets shift rapidly, customer acquisition costs continue rising, and users have countless alternatives available at their fingertips. Product managers who think only about building products without considering how those products attract, engage, and retain users find themselves creating solutions that nobody adopts. Growth-oriented thinking has become necessary for product managers who want their work to translate into actual business results. This does not mean abandoning core product management principles. Rather, it involves expanding the lens through which product decisions get made. Understanding the Growth Mindset Growth hackers approach problems with a particular set of assumptions and methods. They prioritize rapid experimentation over lengthy planning cycles. They look for leverage points where small changes produce disproportionate results. They measure everything and let data guide their decisions rather than relying on intuition alone. Product managers who adopt this mindset begin asking different questions during product development. Instead of simply asking whether a feature works technically, they wonder how it might attract new users or increase engagement among existing ones. They consider the viral coefficient of features they build and think about network effects from the earliest design stages. This shift in thinking affects the entire product development process. Features get evaluated not just on user value but on their contribution to acquisition, activation, retention, revenue, and referral. Product managers start seeing their work as part of a complete system for sustainable growth rather than a series of isolated feature releases. Building Measurement Into Product Design Growth hackers live by their metrics. They instrument everything, run constant experiments, and base decisions on observed results rather than assumptions. Product managers who think like growth hackers bring this discipline into their work from the beginning of any project. When designing a new feature, growth-oriented product managers define success metrics before writing any code. They determine how they will measure whether the feature achieves its intended goals. They build tracking and analytics directly into the product architecture rather than treating measurement as an afterthought. This approach requires product managers to become comfortable with data analysis and statistical thinking. They need to understand concepts like statistical significance, cohort analysis, and attribution modeling. These skills allow them to design meaningful experiments and interpret results correctly. Product Siddha works with product teams to establish measurement frameworks that connect product features directly to business outcomes. This foundation enables teams to make evidence-based decisions about what to build next and how to prioritize competing demands on development resources. Traditional vs Growth-Oriented Product Development Aspect Traditional Approach Growth-Oriented Approach Success Metric Feature completion User adoption and engagement Decision Making Stakeholder requests Data-driven experimentation Development Cycle Quarterly releases Continuous iteration Priority Focus Feature breadth Growth impact User Feedback Post-launch surveys Real-time behavioral data Embedding Viral Mechanics Products that grow organically through user referrals cost far less to scale than those requiring constant paid acquisition. Product managers with growth mindsets design viral mechanics into their products rather than treating virality as something that happens accidentally. This involves understanding why people share products with others and making that sharing behavior easy and rewarding. Viral mechanics work best when they feel natural rather than forced. The product itself should create situations where users want to invite others because doing so makes the product more valuable for everyone involved. Collaboration tools provide clear examples of inherent viral mechanics. When someone creates a document or project and needs input from colleagues, inviting others serves both the product’s growth and the user’s immediate needs. Product managers should look for similar natural sharing moments within their own products. Optimizing for Activation and Retention Acquiring users means nothing if those users never experience value from the product or abandon it after initial use. Product managers thinking like growth hackers obsess over activation rates and retention curves as much as acquisition numbers. Activation optimization focuses on getting new users to their first moment of genuine value as quickly as possible. This requires understanding what that moment looks like for different user segments and removing any barriers that prevent people from reaching it. Product managers must ruthlessly eliminate friction from early user experiences while ensuring people understand why the product matters to them. Retention depends on building habits and continuously demonstrating value. Product managers need to understand behavioral psychology and habit formation. They design features that give users reasons to return regularly and create experiences that become more valuable over time rather than less. Experimentation as Core Practice Growth hackers run dozens or hundreds of experiments to find tactics that work. They accept that most experiments will fail but recognize that a few successful ones can dramatically impact growth trajectories. Product managers adopting this approach need to create organizational capacity for rapid experimentation. This means building products with experimentation infrastructure from the start. Feature flags, A/B testing frameworks, and analytics pipelines become as important as core functionality. Product managers need to educate stakeholders about the value of experimentation and manage expectations around the failure rate of individual tests. The experimentation mindset also affects how product managers allocate development resources. Rather than committing large blocks of time to uncertain initiatives, they structure work to allow for quick tests that validate or invalidate assumptions before heavy investment occurs. Cross-Functional Collaboration Growth rarely happens within functional silos. It requires coordination between product development, marketing, sales, customer success, and data teams. Product managers who think like growth hackers become skilled at working across these boundaries and aligning different functions around shared growth objectives. This collaborative approach means product managers spend more time with marketing teams understanding acquisition channels and conversion funnels. They work with customer success to understand why users churn and what drives