How to Grow Your Startup with Data (Lean Analytics Book Review)

In the book Lean Startup, Eric Ries advocates entrepreneurs to build products that people love. However, entrepreneurs often find it difficult to know what people want. Most people do not know what they want, and entrepreneurs waste a lot of resources building something that no one buys. Fortunately, Lean Analytics illuminates ways to solve these problems.

In , Lean Analytics, the author attempts to guide readers to instil analytics mindset in their business, from validating products to preparing for acquisition. The book is massive, consisting of 30 chapters and over 400 pages. These pages originate from interviews involving over a hundred founders, investors and entrepreneurs.

The book is divided into four parts. Part 1 covers the fundamental analytics in business while Part 2 shows the applications of analytics. Part 3 discusses the baseline for business analytics. Finally, part 4 guides the readers to apply Lean Analytics to their organisations. This article reviews the book and provides a key summary of each chapter. The article also applies the insights to this blog’s growth. Finally, I will discuss the problems with the book.

Summary

Chapter 1 introduces readers to the Lean Analytics mindset. The core idea of Lean Analytics is knowing the kind of business you are, and the stage you’re at, you can track and optimize the One Metrics That Matters to your startup right now. 

A business is like a scientific experiment, where entrepreneurs have to test their hypothesis.The business survives if its hypothesis is correct, or it fails otherwise. And to test a hypothesis, the business will have to collect data. This continuous process of asking hypotheses and collecting data transform how entrepreneurs run their businesses. Lean Analytics help entrepreneurs to conduct these two processes effectively.

Chapter 2 discusses the aspects of a good metric such as being comparative and understandable. A good metric also needs to change the way you behave. Sometimes, businesses track their metrics not to test a hypothesis, but to make them feel good. If the businesses measure a metric that does not relate to their goals or affect their behaviour, they are only lying to themselves and wasting their time.

The authors also warn against tracking vanity metrics. A vanity metric is a piece of data that does not inform, guide or improve your business model. An example of a vanity metric is the number of signups, which tells nothing about the users and what they do. Alternatively, the authors advocate business to track actionable metrics.

Applying this insight to the blog, I can choose to track the number of visitors per day. However, this metric does not tell anything about what the visitors do or the types of posts that visitors read. As an alternative, I can track the number of visitors for each article and what types of posts do visitors like, comment and share. These metrics are more insightful because it guides me in my next decision.

As of now, the most popular most in the blog is “How to Write Well: 4 Steps to Improve Your Writing”. It received 7100 visitors on the day it was published. The post also has the most comments, likes and shares. My hypothesis is that visitors like an engaging, well-researched and well-written how-to guide. Hence, I could use this information to decide the posts that I will write in the future. If my hypothesis is correct, this blog will have a significant growth.

Next, chapter 3 discusses the questions that founders need to ask before starting a company. The authors recommend using the Lean Canvas framework to answer these questions. Chapter 4 brings the readers back to the importance of combining analytics with human introspection.

Chapter 5 reviews several analytics frameworks such as the Pirate Metrics, Engines of Growth, Lean Canvas and Startup Growth Pyramid. The authors propose a new model called Lean Analytics Stages, which combines the best of these frameworks.

Chapter 6 presents us with the concept, One Metrics That Matters (OMTM). OMTM is the metric that a startup needs to focus on above everything else at a particular stage. Although tracking metrics is good, startups can lose focus and track excessive metrics. Unfocused startups are less likely to succeed because they will waste resources while wandering aimlessly.

Next, chapter 7 discusses business models and how to come up with one, depending on your startups. The next chapters (8-13) examine six types of startups and their business models. These are e-commerce, Software as A Service (SaaS), mobile app, media site, user-generated content and two-sided marketplaces. Each chapter examines the important metrics, problems and challenges for the respective startups. After that, chapter 14 to 20 discusses each stage of the Lean Analytics Stages framework. These stages are empathy, stickiness, virality, revenue and scale.

Chapter 21 establishes the baseline for the metrics that startups track. For example, a 5% growth rate is a good baseline for a startup. The time period for this growth depends on which stage your startup is at. The chapter also outlines other key baselines for metrics such as pricing metrics, cost of customer acquisition, site engagement and web performance.

Similar to chapters 8 to 13, chapter 22 to 27 examine the metrics for the six types of startups. Part 3 ends with a review of these concepts and strategies when startups do not have a clear baseline. Chapter 29 outlines the advantages of having enterprise customers and important metrics. The final chapter recommends readers ways they can apply Lean Analytics concept in their organisation.

Although this book covers a lot of topics, it fails to dive deeper into the specifics. In fact, some chapters contain information that tends to be shallow and generic. For example, in chapter 11, the authors discuss the business model of a media site. I expected the chapter to include evidence of how media businesses achieve growth with certain strategies. Similarly, the book covers the key metrics for media site in chapter 25. These metrics are click-through rates, sessions-to-click ratio, referrers, engaged time and sharing. The chapter only briefly reviews each metric. A more detailed guide on how startups can adapt using these metrics would have been useful. These issues notwithstanding, this book is a comprehensive guide for anyone who wants to incorporate analytics mindset in his life.

Conclusion

Overall, the authors deliver the main objective of the book, which is to guide readers to instil analytics in their business, from validating products to preparing for acquisition. Additionally, the authors have provided readers with a specific framework to track these metrics, depending on which stages of business they are at. To conclude, I recommend this book to anyone who wants to use analytics to grow their business effectively. The book is massive and if your business is already growing fast, you will not have the time to read this cover-to-cover. Nonetheless, it is worth reading if you want to apply analytics in a systematic way.

Click here to get the book on Amazon.

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