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Review Time - Lean Analytics: Use Data to Build a Better Startup Faster

Hi Everyone, I have been MIA for a few weeks however in the meantime, I managed to complete this amazing data book.

Lean Analytics: Use Data to Build a Better Startup Faster by Alistair Croll and Benjamin Yoskovitz




Introduction


The book consists of several chapters that start from finding the right metric to several stage-driven techniques that are right for your business.

The book claims that "Lean Startup helps you structure your progress and identify the riskiest parts of your business, then learn about them quickly so you can adapt. Lean Analytics is used to measure that progress, helping you to ask the most important questions and get clear answers quickly."


In this book, the authors educate us on how to figure out your business model and your stage of growth.


Below are the topics covered:

  • How to find the "One Metric That Matters" to you right now.

  • Analysis of qualitative and quantitative data, vanity metrics, correlation, cohorts, segmentation, and leading indicators.

  • What makes a good metric, 5 things to keep in mind for the right metric. Along with several other comparisons of metrics.

  • How to Think Like a Data Scientist

  • Finding the right metric

  • Analytics framework: AARRR (Acquisition, Adoption, Retention, Revenue, Referral)

  • Importance of Northstar metrics

    • In the world of analytics and data, this means picking a single metric that’s incredibly important for the step you’re currently working through in your startup. We call this the One Metric That Matters (OMTM).

Below is the most exciting part of the book:


The 6 business models are explained in detail with frequent and significant KPIs along with an example case study.


6 Business Models:

E-Commerce Company (a visitor buys something from a web-based retailer)


Key Takeaways:

  • It’s important to know if you’re focused on loyalty or acquisition. This drives your whole marketing strategy and many of the features you build.

  • Searches, both off- and on-site, are an increasingly common way of finding something for purchase.

  • While conversion rates, repeat purchases, and transaction sizes are important, the ultimate metric is the product of the three of them: revenue per customer.

  • Don’t overlook real-world considerations like shipping, warehouse logistics, and inventory.

A SaaS Company (A company that offers the software on an on-demand basis, usually delivered through a website it operates.)

For example, Salesforce, Gmail, Basecamp, and Asana are all popular SaaS products.


Key takeaways:

  • While freemium gets a lot of visibility, it’s actually a sales tactic, and one you need to use carefully. In SaaS, churn is everything.

  • If you can build a group of loyal users faster than they erode, you’ll thrive.

  • You need to measure user engagement long before the users become customers, and measure customer activity long before they vanish, to stay ahead of the game.

  • Many people equate SaaS models with subscriptions, but you can monetize on-demand software in many other ways, sometimes to great effect.

Free Mobile App (A third business model that’s increasingly common is the mobile app.)


Key Takeaways:

  • Mobile apps make money in a variety of ways.

  • Most of the money comes from a small number of users; these should be segmented and analyzed as a distinct group.

  • The key metric is average revenue per user, but you may also track the average revenue per paying user, since these “whales” are so distinct.

Media Site Advertising pays for the Internet.

Key Takeaways

  • For media sites, ad revenue is everything — but the advertising may include displays, pay-per-view, pay-per-click, and affiliate models, so tracking revenues is complex.

  • Media sites need inventory (in the form of visitor eyeballs) and desirability, which comes from content that attracts the demographic advertisers want.

  • It’s hard to strike a balance between having good content and enough ads to pay the bills.

User-Generated Content


There is this important differences put out that clarify why community based sites are UGC sites as well.

You might think that Facebook, reddit, and Twitter are media sites, and you’d be right: they make their money from advertising. But their primary goal is rallying an engaged community that creates content. Similarly focused sites like Wikipedia make their money from other sources, such as donations. We call these businesses user-generated content (UGC) sites.

Key Takeaways:

  • Visitor engagement is everything in UGC.

  • You track visitors’ involvement in an “engagement funnel.”

  • Many users will lurk, some will contribute lightly, and others will become dedicated content creators. This 80/20 split exists throughout the activities you want your users to accomplish.

  • To keep users coming back and engaged, you’ll need to notify them of activity through email and other forms of “interruption.”

  • Fraud prevention is a significant amount of work for a UGC site.

Two-Sided Marketplaces (Two-sided marketplaces are a variation on e-commerce site.)

Key Takeaways:

  • Two-sided markets come in all shapes and sizes.

  • Early on, the big challenge is solving the “chicken and egg” problem of finding enough buyers and sellers. It’s usually good to focus on the people who have money to spend first.

  • Since sellers are inventory, you need to track the growth of that inventory and how well it fits what buyers are looking for.

  • While many marketplaces take a percentage of transactions, you may be able to make money in other ways, by helping sellers promote their products or charging a listing fee.

And finally the book lists out that every startup goes through stages starting with problem discovery, then building something, then finding out if what was built is good enough, then spreading the word and collecting money. To clearly understand, Lean Startup advises these stages — Empathy, Stickiness, Virality, Revenue, and Scale.

All of these chapters are backed by analytics lessons learning, KPIs, example case study. I strongly recommend this book to those who particularly wants to learn and expand their business and also to web analysts and data scientists, because it shows how to move beyond traditional “funnel visualizations” and connect their work to more meaningful business discussions.


Disclaimer: All the key takeaways are taken from the book.

I strongly rate this book 4.5 stars and the 0.5 of this book is that the book is too long and technical for a common man to follow. However, the readers can skip certain chapters and only read those that benefit their business model.


Hope you enjoy this post. Feel free to like, share, and subscribe! Until next month, Happy Reading.

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