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)
Part 1: Data Analytics and Forecasting with Python
Part 2: Market and Customer Insights
Part 3: Operation and Pricing Optimization

Designing a conjoint experiment

A product or service area is described as a set of attributes. For example, a laptop may have characteristics such as screen size, screen size, brand, and price. Therefore, each attribute can be divided into several levels—for example, the screen size can be 13, 14, or 15 inches. Respondents are presented with a set of products, prototypes, mockups, or images created from a combination of all or some layers of configuration attributes to select, rank, or display products for evaluation. You will be asked to rank. Each example is similar enough for consumers to consider it a good alternative but different enough for respondents to clearly identify their preferences. Each example consists of a unique combination of product features. The data can consist of individual ratings, rankings, or a selection from alternative combinations.

Conjoint design involves four different steps:

  1. Identifying the sort of research.
  2. Determining the pertinent...