library / libb562d621bdf8e20e
Running Lean (Lean Series)
In a sentence
A systematic, experiment-driven process for iterating from your initial startup vision (Plan A) to a business model that actually works before you run out of resources.
Running Lean is a practical, step-by-step handbook that turns the abstract principles of Lean Startup, Customer Development, and bootstrapping into a concrete, repeatable workflow for vetting product ideas. Ash Maurya shows how to document your business model on a one-page Lean Canvas, identify and prioritize the riskiest assumptions, and then systematically test them through customer interviews, demos, and metrics—first qualitatively, then quantitatively—until you achieve product/market fit. Drawing on firsthand experience building multiple products and conducting hundreds of workshops with entrepreneurs across industries, the book gives founders a battle-tested roadmap that maximizes learning per unit of time and dramatically raises the odds of building something people actually want.
The four lenses
- Science
- Statistics
- Systems
- Strategy
Tags
The model
A causal/process model in which design levers (Lean Canvas documentation, risk prioritization, customer experiments, MVP scope) drive psychological and behavioral states (validated learning, customer commitment) that produce outcome metrics (activation, retention, product/market fit, sustainable growth).
Lean Canvas Documentationdesign lever
The practice of capturing the startup's business model hypotheses (problem, customer segments, UVP, solution, channels, revenue, cost, key metrics, unfair advantage) on a single portable one-page canvas to make assumptions explicit and shareable.
Risk Prioritizationdesign lever
The activity of identifying which business model assumptions are riskiest (product, customer, market risk) and ranking business models so that the highest-loss, highest-uncertainty parts are tested first rather than making marginal progress and getting stuck later.
Customer Experimentationdesign lever
The disciplined practice of running staged experiments—problem interviews, solution interviews, MVP interviews, and metric tests—through the Build-Measure-Learn loop to test falsifiable hypotheses with real customers, first qualitatively then quantitatively.
MVP Scope Reductiondesign lever
The practice of paring the minimum viable product down to its essence—the smallest feature set that delivers on the unique value proposition—to shorten cycle time from requirements to release and accelerate learning while reducing waste.
Validated Learningpsychological state
The knowledge state in which a specific business model hypothesis has been confirmed or refuted by measuring real customer behavior, generating actionable insight that drives the next set of actions and reduces uncertainty about customers.
Customer Commitmentbehavioral pattern
The behavioral state of customers signaling strong willingness to adopt and pay—through verbal commitments, prepayments, or signups—that provides a high-quality signal of demand and improves the reliability of learning relative to low-friction tire-kickers.
Activationoutcome metric
The outcome metric capturing whether an interested customer has their first gratifying user experience, connecting the promise made on the landing page (the UVP) with the actual product during the activation flow.
Retentionoutcome metric
The outcome metric measuring repeated use and ongoing engagement with the product over time, serving as the key indicator of whether the startup has built something people want and is the ultimate form of validation.
Product/Market Fitoutcome metric
The first significant startup milestone of being in a good market with a product that satisfies that market, evidenced by strong activation and retention (40% threshold) and passing the Sean Ellis test, after which some success is almost guaranteed.
Sustainable Growthoutcome metric
The outcome of scaling the business model after product/market fit by tuning a key engine of growth—sticky (high retention), viral (high referral), or paid (high margins)—to achieve repeatable and compounding customer growth.
How they connect
- lean canvas documentation → predicts risk prioritization
- risk prioritization → predicts customer experimentation
- customer experimentation → predicts validated learning
- customer experimentation → influences customer commitment
- validated learning → mediates product market fit
- customer commitment → influences activation
- mvp scope reduction → influences activation
- activation → predicts retention
- retention → predicts product market fit
- product market fit → predicts sustainable growth
The process
This book provides a systematic playbook for entrepreneurs to de-risk their startups by applying Lean Startup principles. The core methodology revolves around documenting initial assumptions as a 'Plan A' using a Lean Canvas, and then rigorously testing the riskiest parts of that plan through a continuous cycle of experimentation. The playbook emphasizes a customer-centric approach, starting with understanding customer problems through structured interviews before ever building a solution. The process guides the practitioner from initial brainstorming of customer segments and value propositions to conducting problem and solution interviews to validate hypotheses. Based on validated learning, a Minimum Viable Product (MVP) is defined and built, focusing only on essential features. This MVP is then tested with early adopters to gather qualitative and quantitative feedback, which is tracked using actionable metrics on a conversion dashboard. The final stages involve managing the feature pipeline based on customer feedback and using specific tests to determine if product/market fit has been achieved, guiding the startup from a state of searching for a business model to executing on one.
Create and Iterate the Lean Canvas
To quickly capture, document, and evolve the startup's business model hypotheses in a concise, single-page format, facilitating systematic testing and communication.
When to use: At the inception of a new business idea and continuously throughout the validation process as new insights are gained.
Step 1Brainstorm and list potential customer segments for your product, splitting broad segments into smaller, more focused ones.
Entry: An initial idea for a product or solution exists.
Exit: A list of potential, specific customer segments is created.
- Which customer segments appear most promising to explore first?
In: Initial product idea · Out: List of potential customer segments
ch03
Step 2Sketch a Lean Canvas for the top 1-3 most promising customer segments in under 15 minutes.
Entry: Promising customer segments have been identified.
Exit: One or more initial Lean Canvases are drafted.
In: Lean Canvas template, Identified customer segments · Out: Drafted Lean Canvas (Plan A)
ch01 · ch03
Step 3Share the documented Lean Canvas with advisors, mentors, or team members for initial feedback.
Entry: A draft Lean Canvas exists.
Exit: Initial feedback on the business model has been received.
In: Drafted Lean Canvas · Out: Feedback on business model hypotheses
ch01 · ch03 · ch04
Step 4Continuously revise the Lean Canvas based on insights gained from customer interviews and experiments.
Entry: New data from experiments or interviews is available.
Exit: The Lean Canvas is updated to reflect the latest validated learning.
- Does the new learning require a minor tweak or a major pivot?
In: Customer feedback, Experiment results · Out: Updated Lean Canvas
ch03
Identify and Prioritize Risks
To systematically identify, rank, and prioritize the most significant risks in the business model to ensure that validation efforts are focused where they matter most.
When to use: After creating the initial Lean Canvas and before designing experiments.
Step 1Identify the current stage of the startup (Problem/Solution Fit, Product/Market Fit, or Scale) to frame the context of risks.
Entry: An initial business model (e.g., Lean Canvas) has been documented.
Exit: The startup's current stage is defined.
In: Lean Canvas · Out: Defined startup stage
ch01
Step 2Categorize risks into three main types: product risk (getting the product right), customer risk (building a path to customers), and market risk (building a viable business).
Entry: The startup's stage is defined.
Exit: Risks from the Lean Canvas are categorized.
In: Lean Canvas · Out: Categorized list of risks
ch04
Step 3Rank the business models or customer segments based on criteria such as customer pain level, ease of reach, price/margin, market size, and technical feasibility.
Entry: Multiple potential business models or customer segments exist.
Exit: A ranked list of business models or segments.
- Which business model/segment combination represents the best starting point?
In: List of potential business models/segments · Out: Prioritized business model for testing
ch04
Step 4Conduct business model interviews with external advisors to validate the prioritized risks.
Entry: Risks have been prioritized internally.
Exit: External feedback on the highest-priority risks is gathered.
In: Lean Canvas, Prioritized risk list · Out: Validated risk assessment
ch04
Conduct Problem Interviews
To validate whether a hypothesized customer problem is real, significant, and worth solving before building a solution.
When to use: After identifying a target customer segment and their potential problems on the Lean Canvas.
Step 1Prepare an interview script focused on learning, not pitching.
Entry: A target customer segment and a set of problems to test are defined on the Lean Canvas.
Exit: A structured interview script is ready.
In: Lean Canvas hypotheses · Out: Problem interview script
ch06 · ch07
Step 2Recruit and schedule 30-60 interviews with a broad range of prospects within the target segment.
Entry: Interview script is prepared.
Exit: A schedule of interviews is in place.
In: List of potential interviewees · Out: Scheduled interviews
ch06
Step 3Conduct the interview by following the script, focusing on understanding how the customer currently solves the problem.
Entry: Interview is scheduled and participant is present.
Exit: Interview is completed.
In: Interview script · Out: Raw interview notes
ch06 · ch07
Step 4Ask the customer to rank the top problems you've identified to gauge their relative importance.
Entry: The problem context has been established in the interview.
Exit: Customer's ranking of problems is recorded.
In: List of hypothesized problems · Out: Problem ranking data
ch07
Step 5Wrap up by asking for permission to follow up and for referrals to other potential interviewees.
Entry: The main part of the interview is complete.
Exit: Follow-up permission and potential referrals are secured.
Out: Referrals
ch07
Step 6Document the results immediately after each interview using a structured template.
Entry: An interview has just concluded.
Exit: A structured summary of the interview is completed.
In: Raw interview notes · Out: Documented interview results
ch06 · ch07
Conduct Solution Interviews
To validate that a proposed solution (demo) resonates with customers and to test their willingness to pay before building the product.
When to use: After Problem Interviews have validated a high-value customer problem.
Step 1Create an effective demo of the proposed solution.
Entry: A high-value customer problem has been validated.
Exit: A demo is ready for presentation to customers.
- What is the minimum fidelity needed for the demo to be effective?
In: Validated customer problem, Solution idea · Out: Solution demo
ch08
Step 2Prepare a solution interview script that sets the stage, re-confirms the problem, and walks the customer through the demo.
Entry: A demo has been created.
Exit: A solution interview script is ready.
In: Solution demo · Out: Solution interview script
ch08
Step 3Conduct the interview by first re-validating the problem context, then presenting the demo.
Entry: Interview scheduled with a customer from the problem interview pool.
Exit: Customer has seen the demo and provided initial reactions.
- Does the customer still acknowledge the problem as significant?
In: Solution interview script, Solution demo · Out: Qualitative feedback on the solution
ch08
Step 4Test the pricing model by presenting the price and gauging the customer's reaction.
Entry: The customer has understood the solution via the demo.
Exit: Customer's willingness to pay has been tested.
- If the customer balks at the price, should the price be adjusted or the value proposition be clarified?
In: Pricing hypothesis · Out: Pricing feedback
ch08
Step 5Wrap up by asking for a commitment, such as signing up for a beta or pre-ordering, and document results immediately.
Entry: Pricing has been discussed.
Exit: Interview results, including any commitment, are documented.
Out: Documented interview results, List of early adopters/beta users
ch08
Define and Build the Minimum Viable Product (MVP)
To define and build the smallest possible version of the product that delivers the core value proposition to early adopters, enabling the fastest loop of validated learning.
When to use: After solution interviews have validated a core problem, solution, and customer willingness to pay.
Step 1Use the Unique Value Proposition (UVP) to identify the single most important problem the MVP must solve.
Entry: Sufficient solution interviews have been conducted to validate the core value proposition.
Exit: The number-one problem for the MVP is clearly defined.
In: Validated UVP, Solution interview feedback · Out: Defined core problem for MVP
ch09
Step 2Classify all potential features from solution interviews as 'must-have', 'nice-to-have', or 'don't need'.
Entry: A list of potential features exists from customer feedback.
Exit: All features are classified.
- Which features are absolutely essential to delivering the core UVP?
In: Feature requests from interviews · Out: Prioritized feature list
ch09
Step 3Define the MVP scope by including only the 'must-have' features.
Entry: Features have been classified.
Exit: A final, minimal feature set for the MVP is defined.
In: Prioritized feature list · Out: MVP feature specification
ch09
Step 4Build the MVP, focusing on learning and speed over optimization and scalability.
Entry: MVP scope is defined.
Exit: A functional MVP is built and ready for early adopters.
In: MVP feature specification · Out: Built MVP
ch02 · ch09
Step 5Implement a payment strategy from day one, even if it's just collecting payment details for a future charge.
Entry: The MVP is being built.
Exit: The MVP includes a mechanism to test payment.
ch09
Design the Initial Customer Experience
To create a marketing website and user activation flow that effectively communicates the product's value and guides new users to their first successful experience.
When to use: In parallel with MVP development.
Step 1Develop a compelling landing page focused on clearly communicating the Unique Value Proposition (UVP).
Entry: The UVP has been crafted and validated.
Exit: A landing page is designed and built.
In: UVP · Out: Marketing landing page
ch09
Step 2Build out essential supporting pages for the marketing website.
Entry: Landing page is complete.
Exit: A basic marketing website is live.
Out: Marketing website
ch09
Step 3Design the user activation flow, which is the path from signup to the user's first 'aha' moment.
Entry: The MVP's core functionality is defined.
Exit: The activation flow is designed and mocked up.
- How many steps should be in the flow?
- What user information is critical to collect upfront?
In: UVP, MVP feature set · Out: Activation flow design
ch09
Step 4Implement the activation flow within the MVP and prepare for user issues.
Entry: Activation flow is designed.
Exit: The activation flow is implemented in the MVP.
In: Activation flow design · Out: Implemented activation flow
ch09
Conduct MVP Interviews
To gather qualitative feedback on the live MVP from early adopters, focusing on usability, messaging, pricing, and the activation flow.
When to use: Immediately after the MVP is built and ready for its first users.
Step 1Prepare for the interview by setting up the MVP, marketing site, and conversion metrics.
Entry: The MVP is live and accessible.
Exit: All materials for the interview are prepared.
In: Live MVP, Marketing website · Out: Interview script and setup
ch11
Step 2Conduct a five-second test of the landing page to assess the clarity of the UVP.
Entry: Interview has started.
Exit: Initial feedback on messaging clarity is gathered.
In: Marketing landing page · Out: UVP clarity feedback
ch11
Step 3Observe the user as they navigate to the pricing page and go through the signup and activation flow.
Entry: The user is ready to explore the site.
Exit: Usability issues in the activation funnel are identified.
In: Live MVP and website · Out: List of usability issues
ch11
Step 4Solicit feedback on the pricing model after they have seen it.
Entry: User has viewed the pricing page.
Exit: Feedback on pricing is collected.
In: Pricing page · Out: Pricing model feedback
ch11
Step 5Document results and usability issues immediately after the interview.
Entry: The interview has concluded.
Exit: A prioritized list of issues to fix is created.
In: Interview notes · Out: Documented feedback and prioritized issue list
ch11 · ch12
Implement and Monitor Actionable Metrics
To move beyond vanity metrics and establish a system for tracking actionable metrics that provide true insight into customer behavior and inform product decisions.
When to use: As soon as the MVP is live and generating user data.
Step 1Identify actionable metrics that tie specific, repeatable user actions to observable results.
Entry: The product is generating user data.
Exit: A set of key actionable metrics is defined.
- Which metrics best represent the customer lifecycle (Acquisition, Activation, Retention, Revenue, Referral)?
In: Business goals · Out: Defined actionable metrics
ch10
Step 2Build a conversion dashboard to visualize these key metrics.
Entry: Actionable metrics have been defined.
Exit: A functional conversion dashboard is in place.
- Which analytics tool best fits the startup's needs and budget?
In: Defined actionable metrics, User data stream · Out: Conversion dashboard
ch10
Step 3Perform cohort analysis to understand user behavior over time.
Entry: The dashboard is collecting time-series data.
Exit: Cohort reports are generated and analyzed.
In: User data · Out: Cohort analysis insights
ch10
Step 4Conduct regular (e.g., weekly) conversion dashboard review meetings.
Entry: The dashboard has been running long enough to show trends.
Exit: A prioritized action plan based on metric analysis is created.
- What is the biggest drop-off point in the funnel that needs to be fixed first?
In: Conversion dashboard · Out: Prioritized action plan
ch14
Manage the Feature Pipeline
To systematically manage and prioritize feature development after the initial MVP launch, ensuring that the product evolves based on validated learning and avoids feature creep.
When to use: Once the MVP is live and feature requests start coming from customers and internal stakeholders.
Step 1Collect all feature requests into a single backlog.
Entry: A feature request is received.
Exit: The request is added to the backlog.
In: Feature requests · Out: Feature backlog
ch13
Step 2Classify requests as small bug fixes or larger minimal marketable features (MMFs).
Entry: A new request is in the backlog.
Exit: The request is classified.
- Is this a small fix or a larger feature?
In: Feature request · Out: Classified feature request
ch13
Step 3For MMFs, conduct customer interviews to validate the problem and assess its value.
Entry: A request is classified as an MMF.
Exit: The problem behind the feature request is validated or invalidated.
- Is this feature worth pursuing?
In: MMF request · Out: Validated problem
ch13
Step 4Create and validate mock-ups of the proposed feature with customers before writing code.
Entry: The problem for the MMF is validated.
Exit: The proposed solution is validated via mock-ups.
In: Validated problem · Out: Validated feature mock-up
ch13
Step 5Build the feature and perform a partial rollout to a small segment of customers for qualitative validation.
Entry: The feature mock-up is validated.
Exit: The feature is validated with a small user group.
In: Validated feature mock-up · Out: Built feature
ch13
Step 6Perform a full rollout and verify the feature's impact quantitatively using cohort analysis or split-tests.
Entry: The feature has passed qualitative validation.
Exit: The feature is fully released and its impact is measured.
In: Built feature · Out: Released feature, Quantitative impact data
ch13
Assess Product/Market Fit
To determine if the startup has achieved product/market fit, which signals a transition from searching for a business model to scaling it.
When to use: When qualitative feedback and quantitative metrics suggest the product is resonating with a core group of customers.
Step 1Conduct the Sean Ellis Test by surveying users with the question: 'How would you feel if you could no longer use this product?'
Entry: A stable base of active users exists.
Exit: Survey responses are collected.
In: List of active users · Out: Survey data
ch14
Step 2Analyze the survey results to determine the percentage of users who would be 'Very disappointed'.
Entry: Survey data has been collected.
Exit: The percentage of 'Very disappointed' users is calculated.
- Is the percentage above or below the 40% threshold?
In: Survey data · Out: Product/market fit score
ch14
Step 3Review retention metrics to ensure a significant portion of activated users are retained over time.
Entry: Sufficient historical user data exists.
Exit: Retention cohorts are analyzed against the benchmark.
- Does the retention curve flatten out, and at what level?
In: Cohort analysis data · Out: Assessment of user retention
ch14
Step 4Synthesize the qualitative and quantitative data to make a judgment call on product/market fit.
Entry: Data from the Sean Ellis test and retention analysis is available.
Exit: A decision is made on whether to focus on growth or continue iterating.
- Have we achieved product/market fit?
In: Product/market fit score, Retention analysis · Out: Strategic decision to scale or iterate
ch12 · ch14
A candidate measure
Running Lean (Lean Series) — derived measurement candidates
Lean Canvas Documentation
Completeness percentage; Number of shares; Update frequency
self-report suitability: medium
Risk Prioritization
Number of models ranked; Alignment of experiments to top risks
self-report suitability: medium
Customer Experimentation
Number of interviews per week; Hypotheses tested per iteration; Signal strength per experiment
self-report suitability: medium
MVP Scope Reduction
Feature count in release; Cycle time from requirements to release
self-report suitability: low
Validated Learning
Lessons-learned entries; Canvas changes per cycle; Pivot/persevere decisions
self-report suitability: low
Customer Commitment
Prepayment rate; Signup conversion; Verbal commitment rate
self-report suitability: medium
Activation
Activation conversion rate; Funnel drop-off points
self-report suitability: low
Retention
Cohort retention rate; Customer Happiness Index
self-report suitability: low
Product/Market Fit
40% retention threshold; % very disappointed (Sean Ellis test)
self-report suitability: medium
Sustainable Growth
Churn rate; Viral coefficient; LTV/COCA ratio
self-report suitability: low
The story
The reader An entrepreneur or founder who wants to build a successful new product without wasting time, money, and effort.
External problem
Most startups fail because they build the wrong product before running out of resources.
Internal problem
Founders feel uncertain, fearful of wasting years of their life, and unsure how to know if their idea will work.
Philosophical problem
It's just plain wrong to bet years of effort on untested assumptions and faith when a disciplined, learnable process exists.
The plan
- Document your Plan A on a one-page Lean Canvas.
- Identify and prioritize the riskiest parts of your plan.
- Run problem interviews to find a problem worth solving.
- Run solution interviews to test the solution and pricing.
- Build and validate an MVP, then measure activation and retention.
- Iterate toward product/market fit, then scale with the right engine of growth.
Success
- You find a plan that works before running out of resources.
- You build something people actually want and will pay for.
- You achieve product/market fit and can confidently shift focus to scaling.
- You raise funding at the ideal time with real traction as leverage.
At stake
- You waste months or years building a product nobody wants.
- You run out of resources before finding a working business model.
- Your startup fails like most startups do.
- You raise funding prematurely with no validation and unfavorable terms.
Chapter by chapter
ch01Meta-Principles
This chapter delineates the foundational meta-principles behind the Lean Startup methodology, emphasizing the necessity of careful planning, risk assessment, and systematic testing to align a startup's vision with market needs.
ch02Running Lean Illustrated
This chapter illustrates how the author applied the principles of the Running Lean methodology while writing his book, showcasing the iterative process of product development.
ch03Create Your Lean Canvas
This chapter illustrates the Lean Canvas methodology as a powerful tool for entrepreneurs to succinctly capture and develop their business model through iterative brainstorming and testing.
ch04Prioritize Where to Start
This chapter emphasizes the critical need for effective risk prioritization in startups, distinguishing between uncertainty and risk to focus on the riskiest components of a business model.
ch05Get Ready to Experiment
This chapter emphasizes the importance of assembling the right teams and efficiently running experiments to validate product hypotheses, while balancing speed, learning, and focus.
ch06Get Ready to Interview Customers
The foundational step in customer development is conducting meaningful interviews that yield insights and inform product development, yet many founders initially default to ineffective methods like surveys and focus groups.
ch07The Problem Interview
To develop a solution effectively, entrepreneurs must first conduct thorough problem interviews to understand their customers' specific pain points, validating product, market, and customer risks.
- Problem interviews are essential for validating the problem-customer segment relationship, enabling entrepreneurs to develop solutions grounded in real customer needs.
- Engaging customers through structured interviews can reveal hidden pain points that might otherwise go unaddressed.
- Formulating falsifiable hypotheses is critical for making customer feedback actionable and guiding product development effectively.
- Techniques from customer observation to structured interviews can provide a comprehensive understanding of user challenges and behaviors.
ch08The Solution Interview
This chapter argues that to effectively test a product solution, one must engage customers through structured Solution interviews that prioritize learning over pitching, while also validating the product’s viability in terms of necessity and pricing.
ch09Get to Release 1.0
The chapter emphasizes the necessity of reducing product scope and shortening the development cycle to accelerate user feedback and learning about customer needs.
ch10Get Ready to Measure
The chapter emphasizes the critical need for businesses to distinguish between actionable and vanity metrics as they refine their understanding of the customer lifecycle in pursuit of product/market fit.
ch11The MVP Interview
The MVP interview is a critical step in refining a minimum viable product (MVP) by face-to-face testing with early adopters, providing essential insights into product viability, customer engagement, and pricing strategies before wider launch.
- Conducting MVP interviews allows for crucial learning moments that enhance product success before launch.
- Converting warm leads is a critical litmus test for your product’s attractiveness and usability.
- Using structured usability testing formats can lead to critical insights about customer needs and product viability.
- Documenting insights immediately post-interview ensures that valuable feedback is not lost over time.
ch12Validate Customer Lifecycle
To optimize customer experience and conversion, founders must actively engage with early adopters, leveraging direct feedback and structured trials while carefully analyzing each stage of the customer lifecycle.
ch13Don’t Be a Feature Pusher
This chapter argues against the common urge to continuously add features in software development, advocating instead for a focused approach that prioritizes existing features and ensures validated learning before pursuing new ones.
ch14Measure Product/Market Fit
The journey towards establishing product/market fit begins with defining metrics to assess early traction, allowing startups to iteratively refine their offerings until they resonate with the market.
ch15Conclusion
The conclusion of "Running Lean" emphasizes the critical transition from attaining product/market fit to scaling a startup, while also highlighting the importance of maintaining a continuous learning culture as growth introduces new challenges.
- Achieving product/market fit is just the beginning; scaling effectively is the next major challenge.
- A company’s success is intrinsically tied to how well it cultivates a culture of continuous learning and experimentation.
- Metrics that truly reflect customer satisfaction and success must be regularly revisited and adapted throughout the growth process.
- The entrepreneurial journey should not end with one successful product; it is an evolving landscape that requires adaptive strategies and ongoing engagement.
Questions this book answers
- How do I find a problem worth solving before building a solution?
- How do I document and stress-test my business model quickly?
- Which risks should I tackle first and how do I prioritize them?
- How do I run effective customer interviews and experiments?
- How do I measure and iterate toward product/market fit?
Glossary
- Lean Canvas Documentation
- The degree to which a startup has explicitly captured and shared its business model hypotheses on a one-page Lean Canvas.
- Risk Prioritization
- The extent to which a startup identifies and ranks its riskiest assumptions to determine what to test first.
- Customer Experimentation
- The disciplined running of structured experiments and interviews to test falsifiable hypotheses with real customers.
- MVP Scope Reduction
- The degree to which the minimum viable product is pared down to the essential features delivering the UVP.
- Validated Learning
- Knowledge confirmed or refuted by measuring real customer behavior that reduces uncertainty about customers.
- Customer Commitment
- The strength of customer willingness to adopt and pay as signaled by costly actions.
- Activation
- Whether an interested customer has a first gratifying experience connecting the UVP promise to the product.
- Retention
- Repeated representative use and engagement with the product over a defined period.
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