Book Image

The Art of Data-Driven Business

By : Alan Bernardo Palacio
Book Image

The Art of Data-Driven Business

By: Alan Bernardo Palacio

Overview of this book

One of the most valuable contributions of data science is toward helping businesses make the right decisions. Understanding this complicated confluence of two disparate worlds, as well as a fiercely competitive market, calls for all the guidance you can get. The Art of Data-Driven Business is your invaluable guide to gaining a business-driven perspective, as well as leveraging the power of machine learning (ML) to guide decision-making in your business. This book provides a common ground of discussion for several profiles within a company. You’ll begin by looking at how to use Python and its many libraries for machine learning. Experienced data scientists may want to skip this short introduction, but you’ll soon get to the meat of the book and explore the many and varied ways ML with Python can be applied to the domain of business decisions through real-world business problems that you can tackle by yourself. As you advance, you’ll gain practical insights into the value that ML can provide to your business, as well as the technical ability to apply a wide variety of tried-and-tested ML methods. By the end of this Python book, you’ll have learned the value of basing your business decisions on data-driven methodologies and have developed the Python skills needed to apply what you’ve learned in the real world.
Table of Contents (17 chapters)
1
Part 1: Data Analytics and Forecasting with Python
4
Part 2: Market and Customer Insights
9
Part 3: Operation and Pricing Optimization

Summary

Web analytics allows us to optimize the performance of the products and services sold online. The information obtained enables us to improve the way in which we communicate with clients, thanks to a deeper understanding of our customers and their consumption patterns. In this chapter, we have dived into a basic understanding of this data and how it can be used to determine the CLV of our customers, understand their characteristics, and identify key metrics to establish a successful digital marketing plan.

The next chapter will look into the considerations made by several industry experts on how data, machine learning, and BI can be used in real-life business contexts to improve operations.