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The Organic Growth Playbook: Activate High-Yield Behaviors To Achieve Extraordinary Results-Every Time
Conventional marketing strategies that focus on product differentiation and positioning often fail to deliver faster growth.Jaworski and Lurie offer a novel approach to the problem of growth based on two simple but profound insights.First, they demonstrate that in every purchase process there are a few high-yield customer behaviors that matter most in determining whether and what customers buy.Second, they show howchangingthose high-yield customer behaviors can consistently drive faster revenue growth. Drawing on decades of client work, the authors provide a detailed, engaging account of a proven system for accelerating or even doubling growth. As evidence of its value, the system has been adopted by a host of Fortune 500 firms as their marketing and growth planning process.
292 pages, Hardcover
Published October 1, 2018
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Displaying 1 of 1 review
July 26, 2026
The five-principle framework is about mapping the buying process, segmenting by propensity to buy, identifying drivers and barriers, building a behavior-change value proposition, and concentrating investment disproportionately on the segments most likely to move.
This book is not about organic search or content marketing, but it gave me some good ideas to apply in that field anyway - a content pipeline should prioritize addressing what stops people from doing something, before addressing why you should do it.
The driver/barrier framework is the best thing in the book. Most growth teams spend all their energy on drivers: reasons to buy, features, benefits, proof points, case studies. Very few build content or collateral around barriers: the specific reasons qualified buyers don't start. Career risk ("what if I champion this and the test shows our biggest channel doesn't work?"). Switching cost ("we just signed a two-year contract with our current vendor"). Decision paralysis ("we know our measurement is broken but we don't know how broken"). Political complexity ("my CFO won't approve a vendor the CMO picked without seeing the numbers herself").
The buying process waterfall (consider, evaluate, buy, experience, advocate) is standard and well-explained. Where it gets useful is the propensity overlay: not all prospects at the "evaluate" stage are equally likely to move. Some are stuck, some are ready. The book argues you should invest disproportionately in the ones closest to moving, which sounds obvious until you check how your own budget is actually allocated.
Where it falls apart: the propensity segmentation methodology requires data most companies don't have. The book assumes you can score prospects by purchase probability using historical conversion data, behavioral signals, and firmographic attributes. If you're running 200+ deals per quarter through a mature CRM with years of closed-lost analysis, this works. If you're a 15-person company closing 3-5 deals a month, you don't have the statistical base to segment anything. The framework is correct. The prerequisite data doesn't exist at the scale where most startups operate.
The examples skew consumer and large enterprise. The Jockey underwear case study is detailed and well-constructed. The pharmaceutical and financial services examples are thorough. B2B SaaS with long sales cycles gets mentioned but never worked through end to end.
The academic register will lose some readers. Jaworski is at Georgetown, Lurie is a practitioner, and the book reads like the meeting point between the two: rigorous enough for a classroom, specific enough for an operator, but heavier on frameworks-within-frameworks than it needs to be. The propensity scoring chapter could have been cut by 40% without losing anything.
One thing the book gets right that almost nobody in the growth/marketing space talks about: your buyer language changes by funnel stage. How a prospect describes their problem before they've talked to anyone is different from how a customer describes it after they've been using the product for six months. If your content is built on post-purchase customer interviews (which is where most VoC programs source their data), you're writing in a vocabulary your pre-purchase prospects don't use yet. The book doesn't frame it in those terms, but the driver/barrier methodology forces you to notice the gap.
Published in 2020, pre-AI, but it doesn't matter. The barrier framework isn't a technology-dependent insight. LLMs don't change the fact that qualified buyers get stuck for reasons that have nothing to do with your product's features.
This book is not about organic search or content marketing, but it gave me some good ideas to apply in that field anyway - a content pipeline should prioritize addressing what stops people from doing something, before addressing why you should do it.
The driver/barrier framework is the best thing in the book. Most growth teams spend all their energy on drivers: reasons to buy, features, benefits, proof points, case studies. Very few build content or collateral around barriers: the specific reasons qualified buyers don't start. Career risk ("what if I champion this and the test shows our biggest channel doesn't work?"). Switching cost ("we just signed a two-year contract with our current vendor"). Decision paralysis ("we know our measurement is broken but we don't know how broken"). Political complexity ("my CFO won't approve a vendor the CMO picked without seeing the numbers herself").
The buying process waterfall (consider, evaluate, buy, experience, advocate) is standard and well-explained. Where it gets useful is the propensity overlay: not all prospects at the "evaluate" stage are equally likely to move. Some are stuck, some are ready. The book argues you should invest disproportionately in the ones closest to moving, which sounds obvious until you check how your own budget is actually allocated.
Where it falls apart: the propensity segmentation methodology requires data most companies don't have. The book assumes you can score prospects by purchase probability using historical conversion data, behavioral signals, and firmographic attributes. If you're running 200+ deals per quarter through a mature CRM with years of closed-lost analysis, this works. If you're a 15-person company closing 3-5 deals a month, you don't have the statistical base to segment anything. The framework is correct. The prerequisite data doesn't exist at the scale where most startups operate.
The examples skew consumer and large enterprise. The Jockey underwear case study is detailed and well-constructed. The pharmaceutical and financial services examples are thorough. B2B SaaS with long sales cycles gets mentioned but never worked through end to end.
The academic register will lose some readers. Jaworski is at Georgetown, Lurie is a practitioner, and the book reads like the meeting point between the two: rigorous enough for a classroom, specific enough for an operator, but heavier on frameworks-within-frameworks than it needs to be. The propensity scoring chapter could have been cut by 40% without losing anything.
One thing the book gets right that almost nobody in the growth/marketing space talks about: your buyer language changes by funnel stage. How a prospect describes their problem before they've talked to anyone is different from how a customer describes it after they've been using the product for six months. If your content is built on post-purchase customer interviews (which is where most VoC programs source their data), you're writing in a vocabulary your pre-purchase prospects don't use yet. The book doesn't frame it in those terms, but the driver/barrier methodology forces you to notice the gap.
Published in 2020, pre-AI, but it doesn't matter. The barrier framework isn't a technology-dependent insight. LLMs don't change the fact that qualified buyers get stuck for reasons that have nothing to do with your product's features.
Displaying 1 of 1 review