Joanne Rodrigues-Craig - Product Analytics: Applied Data Science Techniques for Actionable Consumer Insights

A point of view can be a dangerous luxury when substituted for insight and understanding.

Marshall McLuhan

This book is a practitioners guide to generating actionable insights from consumer data. Actionable in this context refers to extracted insights used to drive change in a web or mobile product or within a broader organization. Many organizations have terabytes of user-generated data from their web products or internal organizations. However, much of the data goes unused. How should they use this data to make changes that will foster user growth, increase revenue, improve engagement, and engender efficiency in an organization?

Product Analytics will take you step-by-step on the journey to extract insight from user data. The reader will traverse the peaks and valleys of theory building, navigate the waters of designing experiments, drive the meandering roads of developing models, and finally embark on translating these results into actionable insights. This book is a primer on the product data science toolkit. Data science is a multidisciplinary field whose goal is to extract insights from data. Product data science is focused on harnessing user data to drive product and organizational changes to meet core business goals. It emphasizes the use of advanced analytics to understand and change user behavior to help start-ups and large companies alike to build engaging products and exceed revenue targets. As a side note, this book does not address other data science workflows, such as building scalable recommendation systems, computer vision, and image recognition, or other types of applications.

The analyzed data can come from a variety of sources. While its often user data from web products, it could also be data from emails or mailing campaigns, survey data, internal company data, or integrated data from marketing channels, demographic, or census data, and a variety of other types of data.

The core audience for this book consists of entrepreneurs, data scientists, analysts, or any other practitioners who are using user data to drive growth, revenue, efficiency, or engagement in their web or mobile products. This book is useful if you are or want to become a product data scientist, an analyst, or an entrepreneur building a website or web product, or if you just have an interest in working with the terabytes of behavioral data available on the web.

The book is not written for an academic audience, but rather with the practitioner in mind. If youre looking to understand real-world product data, look no further than this book.

Product data science relies on multiple disciplines to extract insight from human behavior. While the analytical toolkit is somewhat more modern, it relies on computing and statistical methods, based on xviiisome of the latest machine learning and causal inference techniques. Social scientists have been studying human behavior for the last 400 years. Social science methods and analytical tools need to be adequately integrated to drive actionable insights.