Various - When Companies Spy on You: Corporate Data Mining and Big Business

Published in 2018 by Cavendish Square Publishing, LLC
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Copyright 2018 by Cavendish Square Publishing, LLC

First Edition

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Library of Congress Cataloging-in-Publication Data

Names: Freedman, Jeri.

Title: When companies spy on you: corporate data mining and big business / Jeri Freedman.

Description: New York : Cavendish Square, 2018. | Series: Spying, surveillance, and privacy in the 21st-century | Includes index.

Identifiers: ISBN 9781502626752 (library bound) | ISBN 9781502626707 (ebook)

Subjects: LCSH: Data mining. | Business--Data processing.

Classification: LCC HF5415.125 F74 2018 | DDC 658.802--dc23

Editorial Director: David McNamara

Editor: Fletcher Doyle

Copy Editor: Nathan Heidelberger

Associate Art Director: Amy Greenan

Designer: Stephanie Flecha

Production Coordinator: Karol Szymczuk

Photo Research: J8 Media

The photographs in this book are used by permission and through the courtesy of:

Cover Mark Horn/Stone/Getty Images; p. George Steinmetz/Corbis/Getty Images.

Printed in the United States of America

Contents

Data Mining and Big Business

The Usefulness of Data Mining

The Disadvantages of Data Mining

What the Future Holds

Data Mining Timeline

Glossary

Further Information

Bibliography

Index

About the Author

Huge banks of computers capture and analyze data about peoples lives, activities, and purchases.

CHAPTER 1

Data Mining and Big Business

I n 1949, George Orwell wrote the book Nineteen Eighty-Four. One of the key elements of the book was the governments constant surveillance of peoples activities. Today, our daily activities are under constant surveillance, but not by the government. Rather, corporations are monitoring our purchases, entertainment choices, travel plans, eating preferences, and almost every other element of our lives. Every time we make an online purchase, or even view an item online, that data is recorded. Corporations know our personal details and preferences. They use that information for a variety of purposes, some of them useful, some annoying. The vast collection and sharing of personal data has made it extremely difficult to keep any part of our lives and habits private.

At the heart of this situation is data mining. Data mining is the collection and analysis of large amounts of data in order to reveal correlations (relationships). An example of such a correlation is people who buy canned chicken noodle soup also often purchase childrens clothing. As can be seen from this example, one major purpose of data mining is to find ways to target people with appropriate marketing information to get them to buy things. In recent years, the process of data mining for commercial purposes has been refined to determine the items and services a specific person is likely to purchase. The desire of companies to profile their customers this way has fueled the efforts of companies to acquire as much information as possible about individuals, which can then be used for marketing purposes.

How Data Mining Works

Data consists of pieces of information that can be identified by, recorded on, and processed by a computer. Data includes facts (such as the items a person has purchased) and numbers (such as the cost of those items, or the buyers age). Today, companies can acquire massive quantities of data because so many activities are carried out via computer, from point-of-sale systems in stores and restaurants, to online purchases, to forms that are either filled out online or completed manually and later entered into computer systems for storage. Other data comes from companies internal systems, including their sales, inventory, payroll, and accounting systems.

This data can be used to provide information that will help companies enhance their profitability. However, in order to obtain useful information from this huge pool of data, it is necessary to identify patterns or relationships among the data. Information might include the products that sell to a certain age group, or the time of year when they sell, for example. Information, in turn, can generate knowledge. Knowledge includes elements such as past trends and predictions of likely future trends. For example, analysis of the customers response to past promotions can shed light on consumers buying habits. They may be more likely to respond to promotions for some types of items than for others.

As the reach and power of computer systems have grown, there have been great advances in companies ability to capture, transmit, and process data. Large increases in computer storage capacity have allowed companies to integrate the databases from various departments to look for relationships in the data that is stored on different systems, such as sales, inventory, and accounting. The result has been the creation of data warehouses , consolidated systems that store huge amounts of data from various systems. Data warehousing provides a means for companies to centrally access and manage their data. Advances in data analysis software have increased companies ability to manage and analyze this data to identify relationships and trends. The value of this data is not lost on the corporations that collect it. Many companies have started selling data about their customers to other companies in related businesses or industries that can use it to identify and market to potential customers.

Among the most significant users of data mining are retail, financial, and communications companiesall types of companies focused on selling products to consumers, both individually and as groups. On an individual level, a company can analyze a customers buying history and send the customer promotions, such as free shipping or coupons with discounts, for the specific types of items he or she buys. This process is called targeted promotion. When the company sends a customer advertisements for the specific types of items he or she buys, this is called targeted advertising. This is what happens when a retailer sends recommendations to specific customers based on their past purchases or items they have viewed.

Companies can also use data mining to analyze demographic data to target promotions to particular segments of consumers. Demographics are personal characteristics such as the age and gender of purchasers, or the geographic area in which they live.

Data Mining Is Everywhere

Data-mining applications are available for all sizes of businesses. Data-mining applications exist for giant integrated computer systems of large corporations and the