Lean Analytics book intro and applical highlights 1

As Kenzai moves more into product market fit stages, we as the development team have decided to move our daily ready to the book Lean Analytics by Alistair Croll

I started this book a while back when I first finished another great book, Running Lean

I am going to be highlighting for myself and for easy reference to my team here on my blog.

Highlights:

Cohorts Analysis

Defined: A group of people banded together or treated as a group.

Basically, looking at your data in groups of users segments.

Example would be, the first users on our Life program which started around May 2014, its a very basic program right now that covers what we feel users will need to meet their needs after the Body program to handle life, these users will respond to our changes differently then any of the users who enter the program right now, and with each change that we make, the churn rate of users who enter into our Life program could go up or down just based on this history of how we have interacted with them over the history of our product. We could do something worse, but our older users will be more forgiving to us, or we could do something better but our older users are less effected just becuase they are less excited by anything we do. We hope that our oldest users our our happiest users, and to do this, we must track them different than our newest users.

The book uses an example of a product that is purchased month to month, the users that enter into the product, have a level of purchases that starts higher and gets lower each month. They break down the users by entry date and track the users spending rates from month to month, and show that the overall data grouping the users together, does not do much to show anything. But if they break down the users into cohorts by month of entry, they can actually show that the product is increasing sales because the monthly spending of the new users is increasing. The same could be said for our users, the better we make our Body program, program to program, and the better we make our life features, then we can track each user set of Body group that comes into our Life product and how many decide to pay for the Life program. We can also track each of these groups throughout our Life program and see who drops out, or joins back in over the history of our product.

We would take each of these cohorts of users and tie them into our pirate metrics that are applicable

  • Activation
  • Retention
  • Referral
  • Revenue

Leaving out acquisition of course. Tracking each of these cohorts in reference to the 4 pirate metrics above would represent that the product is being a positive and effective product to our users. By the very nature of our product, activation, retention, referral and our revenue would translate into us changing users lives for the better and providing a better and better service to our users.

Circle of life for analytical startups

I am going to steal an image from a really good blog post, so not really stealing it right as long as I reference his work, where he references the Lean Analytics book.
(http://www.kaushik.net/avinash/lean-analytics-cycle-metrics-hypothesis-experiment-act/)

Circle of life for analytical startups

This is pretty simple to flow through once you read this flow chart and also if you read the post by Kaushik. So I don't feel much need in breaking this down, as he did an amazing job.

I will give you this one definition KPI to help you read thorugh this:

Defined: KPI

A performance indicator or key performance indicator (KPI) is a type of performance measurement. An organization may use KPIs to evaluate its success, or to evaluate the success of a particular activity in which it is engaged.