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Growth Data Analytics Playbook: The Modern Guide to Finding, Measuring, and Scaling Product-Market Fit
A go-to guide for product and business growth.
While growth is key for survival in the tech world, training is minimal—sometimes even nonexistent—for leveraging data analytics. This book changes that.
In the Growth Data Analytics Playbook, Mengying Li, Joe Kumar, and Yuzheng Sun outline a structured approach for utilizing data insights to drive product and business growth. You’ll learn actionable strategies for identifying and understanding key opportunities, enabling accurate performance measurement and informed decision-making. Mengying, Joe, and Yuzheng explore product-market fit, retention metrics, and revenue generation, along with strategies for enhancing user adoption and optimizing conversion rates. A bridge between theory and application, the Growth Data Analytics Playbook is a compelling and comprehensive guide that paves the way for sustainable growth.
While growth is key for survival in the tech world, training is minimal—sometimes even nonexistent—for leveraging data analytics. This book changes that.
In the Growth Data Analytics Playbook, Mengying Li, Joe Kumar, and Yuzheng Sun outline a structured approach for utilizing data insights to drive product and business growth. You’ll learn actionable strategies for identifying and understanding key opportunities, enabling accurate performance measurement and informed decision-making. Mengying, Joe, and Yuzheng explore product-market fit, retention metrics, and revenue generation, along with strategies for enhancing user adoption and optimizing conversion rates. A bridge between theory and application, the Growth Data Analytics Playbook is a compelling and comprehensive guide that paves the way for sustainable growth.
- GenresBusiness
250 pages, Kindle Edition
Published November 18, 2025
25 people are currently reading
410 people want to read
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January 19, 2026In "Growth Data Analytics Playbook: How to Turn Gut Instinct into Data-Driven Product Growth" by Joe Kumar, Mengying Li, and Yuzheng Sun, the authors explore the moment every successful product team eventually faces: the point where instinct and personal closeness to users are no longer enough. In the earliest stage of a startup, founders often know their customers individually, understand their motivations, and can rely on intuition to guide decisions. But as the product scales, that intimacy disappears. Signals become noisy, assumptions replace direct feedback, and growth begins to feel like guesswork. The book argues that to grow sustainably, teams must translate human insight into measurable systems, replacing vague feelings with structured analysis that reveals why users stay, why they leave, and how real value is created over time.
A central idea is that not all metrics are created equal. Many teams focus on surface-level numbers such as downloads, signups, or page views, mistaking activity for value. The authors emphasize the importance of defining a single guiding metric that reflects genuine user benefit rather than empty volume. This 'North Star' is meant to capture the moment when a user truly experiences what the product promises. For a communication tool, this might be repeated collaboration; for a content platform, sustained consumption or creation. By aligning the entire organization around this measure, teams gain a shared understanding of what success actually means and avoid being distracted by statistics that look impressive but reveal little about long-term health.
Closely tied to this is the concept of product–market fit, which the book treats not as a vague feeling but as something that can be observed through behavior, especially retention. If users continue to return, it suggests the product has become part of their routine or solved a meaningful problem. When retention over time stabilizes instead of steadily declining, it signals that a core group finds lasting value. However, because retention reveals problems only after they have already taken hold, the authors stress the need for leading indicators: early actions that predict whether a new user will become a loyal one. By identifying these moments - such as completing a key task or forming an initial connection - teams can guide more people toward the experiences that anchor long-term engagement.
To move beyond intuition, the book introduces the idea of growth accounting, a disciplined way to track how a user base truly changes. Instead of celebrating raw increases in total users, it encourages breaking growth into components: new arrivals, returning users, those who have left, and those who come back after a period of absence. This approach exposes whether progress comes from genuine retention or simply from constantly replacing lost users with new ones. It also highlights the danger of relying solely on aggressive acquisition, which can mask underlying problems if churn remains high. By treating users like entries in a financial ledger, teams can see where value is being created and where it is quietly leaking away.
Engagement depth is another crucial theme. A large audience means little if most people interact only briefly. The authors propose looking at how frequently individuals return and how embedded the product becomes in their routines. Simple ratios that compare daily and monthly activity can reveal whether a product is a habit or just an occasional stop. More refined measures track how many days within a period a person is active, allowing teams to distinguish casual users from those who rely on the product almost every day. These highly engaged individuals often account for a disproportionate share of usage and influence, shaping community norms, generating content, and spreading the product through word of mouth.
Understanding these power users is essential because their behavior offers a blueprint for sustainable growth. By studying what they did early on - what features they used, which actions they took, how quickly they connected with others - teams can redesign onboarding and early experiences to steer newcomers toward similar patterns. Rather than hoping that value will be discovered by chance, the product can be structured to lead users step by step toward the behaviors that correlate with long-term commitment.
The book also examines the problem of churn and argues that departures rarely happen without warning. Before users leave entirely, their activity often declines or becomes irregular. By monitoring such signals, teams can identify people who are at risk and intervene with timely support, improvements, or relevant communication. This shifts retention from a reactive process to a proactive one. The authors also caution against overwhelming disengaged users with generic reminders, noting that attention is scarce and easily lost. Thoughtful, targeted re-engagement, delivered when it is genuinely relevant, is far more effective than constant noise.
Financial sustainability is woven into this analytical view of growth. Retaining customers and expanding their usage or spending is often more powerful than acquiring new ones. Metrics that separate revenue kept from existing users from revenue gained through upgrades reveal whether a business is merely stable or truly compounding in value. When existing customers contribute more over time, growth becomes less dependent on continuous marketing spend and more resilient to market shifts.
Speed and experimentation form the final layer of the framework. Performance, such as how quickly an application loads or responds, directly affects whether users remain engaged. Even small delays can push people away before they experience any benefit. Beyond technical speed, organizational speed matters as well: the ability to test ideas rapidly, learn from real behavior, and adjust without lengthy debates. Controlled experiments allow teams to evaluate features on small segments, observe real outcomes, and scale only what works. This culture of continuous testing replaces opinion-driven decisions with evidence-based progress.
All these elements come together in the idea of growth as a self-reinforcing system rather than a one-way funnel. Instead of endlessly pouring resources into acquisition, the goal is to design loops in which existing users attract new ones, engagement generates more content or connections, and value feeds back into further growth. By identifying friction points and strengthening the links between actions and rewards, a product can build momentum that sustains itself over time.
In conclusion, "Growth Data Analytics Playbook: How to Turn Gut Instinct into Data-Driven Product Growth" by Joe Kumar, Mengying Li, and Yuzheng Sun shows that lasting success is not built on clever tricks or short-term spikes but on a clear understanding of user behavior, measured and interpreted with rigor. The book demonstrates how intuition can be transformed into structured insight through the use of meaningful metrics, disciplined growth accounting, deep engagement analysis, proactive retention strategies, and rapid experimentation. By shifting from guesswork to evidence, teams can uncover what truly drives loyalty, design experiences that replicate the habits of their most committed users, and build growth systems that compound rather than collapse. Ultimately, it argues that when data is used not as a scoreboard but as a guide to human behavior, it becomes the bridge between early vision and scalable, enduring impact.
A central idea is that not all metrics are created equal. Many teams focus on surface-level numbers such as downloads, signups, or page views, mistaking activity for value. The authors emphasize the importance of defining a single guiding metric that reflects genuine user benefit rather than empty volume. This 'North Star' is meant to capture the moment when a user truly experiences what the product promises. For a communication tool, this might be repeated collaboration; for a content platform, sustained consumption or creation. By aligning the entire organization around this measure, teams gain a shared understanding of what success actually means and avoid being distracted by statistics that look impressive but reveal little about long-term health.
Closely tied to this is the concept of product–market fit, which the book treats not as a vague feeling but as something that can be observed through behavior, especially retention. If users continue to return, it suggests the product has become part of their routine or solved a meaningful problem. When retention over time stabilizes instead of steadily declining, it signals that a core group finds lasting value. However, because retention reveals problems only after they have already taken hold, the authors stress the need for leading indicators: early actions that predict whether a new user will become a loyal one. By identifying these moments - such as completing a key task or forming an initial connection - teams can guide more people toward the experiences that anchor long-term engagement.
To move beyond intuition, the book introduces the idea of growth accounting, a disciplined way to track how a user base truly changes. Instead of celebrating raw increases in total users, it encourages breaking growth into components: new arrivals, returning users, those who have left, and those who come back after a period of absence. This approach exposes whether progress comes from genuine retention or simply from constantly replacing lost users with new ones. It also highlights the danger of relying solely on aggressive acquisition, which can mask underlying problems if churn remains high. By treating users like entries in a financial ledger, teams can see where value is being created and where it is quietly leaking away.
Engagement depth is another crucial theme. A large audience means little if most people interact only briefly. The authors propose looking at how frequently individuals return and how embedded the product becomes in their routines. Simple ratios that compare daily and monthly activity can reveal whether a product is a habit or just an occasional stop. More refined measures track how many days within a period a person is active, allowing teams to distinguish casual users from those who rely on the product almost every day. These highly engaged individuals often account for a disproportionate share of usage and influence, shaping community norms, generating content, and spreading the product through word of mouth.
Understanding these power users is essential because their behavior offers a blueprint for sustainable growth. By studying what they did early on - what features they used, which actions they took, how quickly they connected with others - teams can redesign onboarding and early experiences to steer newcomers toward similar patterns. Rather than hoping that value will be discovered by chance, the product can be structured to lead users step by step toward the behaviors that correlate with long-term commitment.
The book also examines the problem of churn and argues that departures rarely happen without warning. Before users leave entirely, their activity often declines or becomes irregular. By monitoring such signals, teams can identify people who are at risk and intervene with timely support, improvements, or relevant communication. This shifts retention from a reactive process to a proactive one. The authors also caution against overwhelming disengaged users with generic reminders, noting that attention is scarce and easily lost. Thoughtful, targeted re-engagement, delivered when it is genuinely relevant, is far more effective than constant noise.
Financial sustainability is woven into this analytical view of growth. Retaining customers and expanding their usage or spending is often more powerful than acquiring new ones. Metrics that separate revenue kept from existing users from revenue gained through upgrades reveal whether a business is merely stable or truly compounding in value. When existing customers contribute more over time, growth becomes less dependent on continuous marketing spend and more resilient to market shifts.
Speed and experimentation form the final layer of the framework. Performance, such as how quickly an application loads or responds, directly affects whether users remain engaged. Even small delays can push people away before they experience any benefit. Beyond technical speed, organizational speed matters as well: the ability to test ideas rapidly, learn from real behavior, and adjust without lengthy debates. Controlled experiments allow teams to evaluate features on small segments, observe real outcomes, and scale only what works. This culture of continuous testing replaces opinion-driven decisions with evidence-based progress.
All these elements come together in the idea of growth as a self-reinforcing system rather than a one-way funnel. Instead of endlessly pouring resources into acquisition, the goal is to design loops in which existing users attract new ones, engagement generates more content or connections, and value feeds back into further growth. By identifying friction points and strengthening the links between actions and rewards, a product can build momentum that sustains itself over time.
In conclusion, "Growth Data Analytics Playbook: How to Turn Gut Instinct into Data-Driven Product Growth" by Joe Kumar, Mengying Li, and Yuzheng Sun shows that lasting success is not built on clever tricks or short-term spikes but on a clear understanding of user behavior, measured and interpreted with rigor. The book demonstrates how intuition can be transformed into structured insight through the use of meaningful metrics, disciplined growth accounting, deep engagement analysis, proactive retention strategies, and rapid experimentation. By shifting from guesswork to evidence, teams can uncover what truly drives loyalty, design experiences that replicate the habits of their most committed users, and build growth systems that compound rather than collapse. Ultimately, it argues that when data is used not as a scoreboard but as a guide to human behavior, it becomes the bridge between early vision and scalable, enduring impact.
January 19, 2026
metaphors do not fit, not so practical
summary
Practical guide to using data analytics for product and business growth, especially in tech and product-led companies.
Focuses on a structured approach to identify growth opportunities and make data-driven decisions rather than relying on intuition.
Teaches how to find, measure, and scale product-market fit, a key milestone before accelerating growth (product-market fit = matching a product to strong demand).
Covers core growth metrics including retention, user adoption, conversion rates, and revenue indicators.
Provides strategies to interpret metrics, set up performance measurement, and take action based on analytics.
Aims to bridge theory and practical application with real examples and frameworks to help teams drive sustainable growth.
Useful for data scientists, product managers, founders, and growth teams who want a repeatable approach to leveraging analytics for product success.
summary
Practical guide to using data analytics for product and business growth, especially in tech and product-led companies.
Focuses on a structured approach to identify growth opportunities and make data-driven decisions rather than relying on intuition.
Teaches how to find, measure, and scale product-market fit, a key milestone before accelerating growth (product-market fit = matching a product to strong demand).
Covers core growth metrics including retention, user adoption, conversion rates, and revenue indicators.
Provides strategies to interpret metrics, set up performance measurement, and take action based on analytics.
Aims to bridge theory and practical application with real examples and frameworks to help teams drive sustainable growth.
Useful for data scientists, product managers, founders, and growth teams who want a repeatable approach to leveraging analytics for product success.
December 18, 2025
💯💯💯💯💯
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