Digital Privacy in the Marketplace

George Milne

• Publisher: Business Expert Press
• Year: 2015
• ISBN:
  9781606498491
• Topic: Business
• Subtopic: Pubblicità
• Index: Business

Digital Privacy in the Marketplace focuses on the data ex-changes between marketers and consumers, with special ttention to the privacy challenges that are brought about by new information technologies. The purpose of this book is to provide a background source to help the reader think more deeply about the impact of privacy issues on both consumers and marketers. It covers topics such as: why privacy is needed, the technological, historical and academic theories of privacy, how market exchange af-fects privacy, what are the privacy harms and protections available, and what is the likely future of privacy.

CHAPTER 1

The Information Environment and the Privacy Problem

Chapter Overview

In this first chapter, you will learn about the data-driven marketing information environment, the personal data ecosystem, how technology is facilitating the collection and dissemination of information, and how the different privacy expectations for technological use are creating a privacy problem between marketers and consumers.

The Information Environment

We live in an information economy that is based on accessing and utilizing information from market exchanges. The acquired information is used by both consumers and businesses to make better decisions in the marketplace. In many respects information exchange, in our digital world, is the currency of the modern market economy. Every moment as consumers, we have access to a constant flow of digital information on our phones and computers that we use to make daily decisions including purchases. Although we are aware of exchanging money for goods and services during the time of purchase, there is a less recognized second exchange at this time, where information about consumers is provided to marketers and information about marketers and their goods and services is provided to consumers (Culnan and Milberg 1998). Moreover, there are many other information exchanges that occur that are not directly tied to purchasing; they are simply a function of having an online presence. While the flow of data from consumers to marketers is sometimes intentional, other times it is not, with consumers unaware of the data collection.

Indeed, the information exchange process benefits both consumers’ and marketers’ market transactions. Consumers, for example, gather and review information about marketers and the product and services they are considering purchasing either online or in stores. Using Internet technologies, consumers can easily compare competing products features, obtain reviews, and ask questions of other customers prior to buying. They also have the ability to get answers to post purchase consumer service questions from both marketers and other consumers. Marketers, on the other hand, use the Internet to access information about consumers and their preferences so they can better gauge demand. Information is used to tailor offers that best appeal to market segments, which in many cases are the size of one. Undoubtedly, having access to data helps marketers be customer oriented, which is the basic foundation of the marketing discipline.

Data-Driven Market Economy

Privacy issues aside for the moment, the information rich environment is seen by many marketers and policy makers as a good thing. It has been acknowledged that data driven marketing is a major source of growth for the U.S. economy. A 2013 study (Deighton and Johnson 2013, p. 1) finds that the data-driven marketing economy is adding $156 billion in revenue to the U.S. economy and contributed to 675,000 jobs in 2012. The data-driven economy is comprised of middlemen that gather and manipulate individual level data and supply the processed data to other firms for their marketing efforts. Concurrently, the influx of data has resulted in the United States leading the world in having data scientists in being able to model consumer behavior sophisticatedly. This enhanced targeted information based on data mining is sold to marketers who want to improve their marketing capabilities. Estimates have these marketing exchanges projected to account for up to 70 percent of the economic impact of the data driven economy (Deighton and Johnson 2013).

The authors of the 2013 study suggest that their findings are conservative and the economic impact could be larger since they focused on expenses and not benefits. The innovation of data-driven marketing has provided substantial benefits to many businesses. Due to the availability of data, small businesses and start-ups have low barriers to entry. Advertising is easier and access to consumers continues to grow with the growth of ecommerce. Competition in markets is also increasing as businesses are forced to be more consumer centric. Start-ups that deliver such value are able to compete effectively with big established businesses. Overall this leads to more efficient markets, making the process of marketing more efficient—with pin point segmentation, targeting, and measurement. All of this ultimately benefits the consumer by offering them more targeted choices.

Personal Data Ecosystem

Personal data is data about consumers. It can be individually provided by consumers through photos, blogs, e-mails and tweets, or through online transaction data, such as a job application or registration for a website. It can be observed through internet browsing records, surveillance videos, location data from cell phones, or detailed call records. It can be inferred through credit scores, consumer profiles, predictive traffic flows, and targeted advertisements. Of interest is that fact that collection of observed and inferred data is increasing the fastest and is being acquired without consumers being aware.

The personal data ecosystem is a network of businesses that collects and processes personal consumer data and uses it to target consumers with marketing and other actions. This ecosystem, which contains consumer personal data, functions because of data exchanges among:

• Data collectors (sources),

• Data brokers, and

• Data users.

While most people are aware of data collectors and data users, the role and sheer number of data brokers that exist are not well understood. Figure 1.1, adapted from the FTC report, “Protecting Consumers in an Era of Rapid Change,” highlights the various entities that are involved in the personal data collection and dissemination business (Federal Trade Commission, 2012).

Figure 1.1 The personal data ecosystem

Figure 1.1 shows the path of how an individual’s data get acquired by companies who use the data. One path is shown by the solid black lines that indicate data from individuals are acquired by data collectors who then pass it on to data brokers and then to data users. Other paths show data transfers between consumers and data users as well as between data collectors and data users. The ecosystem is complex in that for data collectors, data brokers, and data users, there are many sectors and actors. As a more specific example, the figure shows dashed lines that indicate data is collected from social media networking sites that forward the data to information brokers, who then repackage the data to pass it on to marketers who use the data for targeting and advertising purposes. While only an abstraction of some major types of organizations in the data ecosystem, the figure nonetheless illustrates that there are many organizations in the data environment that are working behind the scenes of most consumers’ knowledge.

Data Collectors and Sources of Data

As shown in the figure, the sources of the data used by the data collection come from the following sectors:

• Internet,

• Medical,

• Financial and insurance,

• Telecommunications and mobile,

• Retail, and

• Public sector.

The sectors shown in the figure are known for their information intensity. The data available in these sectors is of value to marketers because gathered data can enhance the marketers’ efficiencies, effectiveness, and provide new income streams.

As an illustration, marketers are much interested in digitized medical data, as well as financial and insurance data. Websites that collect data about the consumers who seek content on diseases and loan rates are able to sell and transfer this data to companies looking for leads. Data from the telecommunications and mobile industries is also sought, not only for the communication patterns based on smart phone usage but also from geographical positioning information transmitted by the phone. Retail data, both offline and online, is sought by marketers to help customize and target future communications with consumers. Finally, many marketers are able to gather data from public records, such is the case from the real estate industry and court records. Both marketers and consumers use People finder services, which aggregate much of the public data and make dossiers on people available for sale. Increasingly, across all these data sources the data is observed or inferred. This suggests that a great amount of data is acquired through various data collectors without consumer awareness.

In addition to the lack of consumer awareness, some of the data gathered can be quite sensitive. In the medical sector, there are lists that contain sensitive information such as genetic diseases sufferer’s lists, dementia sufferer’s lists, Aids and HIV infection sufferer’s lists, and the addictive behaviors, alcohol and drugs mailing list (Dixon 2014). Similarly, data from financial lists, such as the Derogatory Credit Consumers mailing list, can be harmful to consumers. Data from insurance lists can reveal lifestyle characteristics. Even data gathered from public records can be problematic for individuals who wish to keep their lives private. In these situations, consumers find it difficult and costly to remove their names from online white pages and in the end may find it nearly impossible (Labrecque et al. 2012).

Data Brokers

Across all these information sectors, there are data brokers—the hidden layer that is generally unknown to consumers. Data brokers function as middlemen to aggregate and compile data in a usable form to sell to data users. They can be classified in terms of:

• Information brokers,

• Websites,

• Media archives,

• Credit bureaus,

• Healthcare analytics,

• Ad networks and analytics,

• Catalog co-opts,

• List brokers, and

• Affiliates.

Data brokers are in the position to gather data and repackage and resell it to others. Data brokers (also referred to as Information brokers) collect and sell information used for targeted ads, market research, and customer scoring. Their customer files and contact information are often sold in lists, which are organized by demographics or behaviors. It is estimated that there are between 3,500 and 4,000 data broker companies (Dixon 2014). While this industry has a few large companies, such as Acxion, there is a very long tail of many other smaller companies. Interestingly, the business models of data brokers vary considerably. For example, Acxion, a very large data broker, hosts some of its own data collection and also buys original data. Other companies, such as Datalogix, primarily score existing consumer data. Others, like Itellius, sell data online. Broadly speaking, the activities of data brokers include list brokering, data analytics, predictive analytics and modeling, scoring, CRM, online, offline, APIS, cross channel, mailing preparation, campaigns, and database cleansing (Dixon 2014). In their 2012 investigation of data brokerage companies (FTC to Study Data Broker Industry’s Collection and Use of Consumer Data, 2012), the FTC focused on nine: (1) Acxiom, (2) Corelogic, (3) Datalogix, (4) eBureau, (5) ID Analytics, (6) Intelius, (7) Peekyou, (8) Rapleaf, and (9) Recorded Future. These represent some of the largest and well-known companies. Nonetheless, there are many others.

The data gathered by the data brokers are gathered from public and non-public sources and often are resold to other data brokers and eventually to end users. In turn, these users will incorporate the purchased data in the target marketing and data processing activities. Besides marketing efforts, the uses of data include processing records to determine eligibility or whether the records need to be suppressed and specific processing algorithms for authentication, anti-fraud detection, and identity verification, and back ground lifestyle checks. The algorithms for these techniques rely upon a range of data including proxy credit scores and medical data (Dixon 2014). Of concern to privacy advocates is the use of proxy scores, which is an approach to circumvent existing privacy laws. This practice is unfair, in part to the difficulty for consumers to opt out of the data compilation reports and the lack of consumer rights and knowledge of consumer scoring algorithms that are used to make decision about the type of relationship consumers have with data users.

Data Users

According to the FTC ecosystem, the data users include:

• Marketers,

• Media,

• Government,

• Lawyers/public investigators,

• Individuals,

• Law enforcement,

• Product and service delivery,

• Employers, and

• Banks.

Data users rely on information to create efficiencies and more effective decision making. Some examples include marketers use GPS location transmitted by cell phones to send geographically targeted advertisements, media companies help websites serve up advertisements targeted to individual consumers based on the past websites they visited, the government monitors social media and phone communications for national security, individuals check out other individuals prior to meeting them the first time on social and work occasions, law enforcements use predictive analytics to determine prisoner paroles, delivery companies use GPS for improving deliveries, employees track keystrokes to measure employee productivity, and banks track credit card usage to thwart fraud. To date much of the focus has been on the data users. However, as apparent through seeing the data ecosystem, there are many parties involved in the collection, trading, and use of information.

In response to this unregulated data ecosystem, the FTC report suggested that data brokers need to make disclosures with regard to type of data they collect and sell. These include (1) the nature and source of information, (2) the use, maintenance, and dissemination of information, and (3) whether consumers have a chance to correct erroneous information. Not surprisingly, the industry lobbyists are trying to stop such requirements citing it would be too cumbersome and expensive to implement. Whether or not this suggestion eventually is enacted into law, there are reasons for both marketers and consumers to be aware of the information flows that are occurring.

The studies, Data Driven Marketing and the FTC Report on Privacy, suggest two important points. First, that data driven marketing will continue to grow and prosper. Second, given the externalities of privacy issues that continue to be raised in public discourse and by regulatory bodies, it is incumbent on both marketers and consumers to better understand the ramifications of information exchange.

Technology Is...

Table of contents

• Cover
• Half Title Page
• Title Page
• Copyright Page
• Dedication
• Contents
• Introduction
• Chapter 1 The Information Environment and the Privacy Problem
• Chapter 2 Why Privacy Is Needed
• Chapter 3 Perspectives of Privacy: Technology History and Academic Theories
• Chapter 4 Information Exchange and Privacy in the Marketplace
• Chapter 5 Information Based Privacy Harms
• Chapter 6 Forms of Protection
• Chapter 7 The Future of Privacy
• References
• Index