#leananalytics

I’m not going to write a full review of this book. The breadth and depth of the information contained within the relatively small number of pages of this book is quite extensive, and covering it all would make for a long and rambling post.

Lean Analytics is an extended walkthrough/tutorial/guide that breaks down and examines important metrics across 6 of different business models (eCommerce, SaaS, Moblie App, Media, User Generated Content, Marketplace) and 5 different business stages (Empathy, Stickiness, Virality, Revenue, Scale). It also contains practical advice to help businesses set goals and plan for success. In essence, it really dives into the MEASURE and LEARN components of the build>measure>learn cycle. And it does it in language that is accessible even to readers who don’t have a statistical, marketing, or technical backgrounds.

Different readers will get different things out of this book. One of the best features, in my opinion, is that after the authors explain the theoretical aspects of a concept, they feature a real-world example to highlight everything they just talked about. Then, they give a short paragraph and/or bullet point breakdown of key lessons learned so that if you didn’t find the section particularly relevant to you or your business (if, for example, it was a section about an early-stage SaaS company and you run a late-stage eCommerce company) you can skip over the tiny details and still get the big picture.

Top three things that stood out to me:

1.) Facts on Facts on Facts

There were a number of small but important facts scattered throughout the book that elicited a small “huh” from me as I read. For example, I learned the speed at which a user invites a friend to try a service is an order of magnitude more important than the number of friends he or she invites total, and without taking this speed into consideration the Viral Coefficient is relatively pointless.

2.) Baselines

Near the end of the book the authors catalogued a number of baselines for metrics broken down by business model and industry. I had been searching for many of these over the past few months, both for work and for school consulting projects, but I hadn’t had a lot of success.

The authors did a great job of listing baselines for different metrics, but also going a step further to examining what those baselines meant. The most useful for me was their evaluation of the signup rates and subsequent conversion rates for a SaaS companies who ask for credit card info upfront vs. those who don’t.

3.) The Intrapreneur Section

The Lean series has been adopted by many companies of varying sizes, but the examples used in the books, at least in my limited experience, (I’m only beginning to make my way through the series) pretty much always focus on small startups. Lean Analytics touches, if only for a chapter or two, on the bureaucracy, politics, and special challenges of being a disruptive innovator within a larger organization.

Final Thoughts