In this post, we will not dig into more advanced techniques that involve individual LTV predictions. I am thinking of writing a separate blog post about that.
Consider these as primers to customer lifetime value: these 3 parts are quite easy to digest and will give you a good intro to LTV. In Part 1 , I went through the logical piece, so if you’re interested, go check it out! In (a small) Part 2 , I showed an example of how cohort retention adds up to an average weighted lifetime of a customer. And here, in Part 3, I have added a Python blueprint code that you can use and improve upon to extrapolate your customer LTV.
In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.
Learn and Become a Master of one of the most used python tools for Data Analysis.
NumPy Cheat Sheet: Data Analysis in Python. This Python cheat sheet is a quick reference for NumPy beginners looking to get started with data analysis.
Beginner’s Guide to Data Analysis using numpy and pandas. Oftentimes, we tend to forget that the pandas library is built on top of the numpy package.
Many a time, I have seen beginners in data science skip exploratory data analysis (EDA) and jump straight into building a hypothesis function or model. In my opinion, this should not be the case.