A Time for Action: Establishing Ethical Guidelines for Modern Data-Driven Marketing

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A Time for Action: Establishing Ethical Guidelines for Modern Data-Driven Marketing

An Acxiom White Paper

Over the past decade the rapid emergence of big data, while clearly demonstrating obvious value for consumers and businesses alike, has sparked concerns over the ethical use of consumer data in modern multi-channel marketing. In this fast-evolving environment, the absence of established ethical guidelines has led to anxiety among consumers and confusion among marketers — who are some of the most aggressive users of data and are also some of the quickest to adopt new data technologies.

In September 2014, Acxiom Corporation hosted a unique forum at the National Press Club in Washington, D.C., to address the ethical challenges of big data in today’s data-driven marketing ecosystem. Indeed, it was the first gathering of its kind to discuss these important issues in depth. The select group of 30 invited participants included government regulators, academics, industry trade association executives, legal experts, think tank officials, consumer privacy advocates, and business leaders.

At the outset, Acxiom established three main areas for discussion where gaps in ethical guidelines exist in the United States and abroad:• Sharing data for marketing and advertising purposes (both personally identifiable information

and anonymous information)• Employing sensitive data for marketing and advertising purposes• Applying robust analytics (e.g., big data analytics) for marketing and advertising purposes

During the day-long series of meetings, discussions, and presentations relating to these focal points, the group identified five distinct areas where stronger ethical principles should be introduced in marketing, and developed the following broad recommendations (which are presented in greater detail at the conclusion of this paper):1. Maximize transparency and choice. Privacy policies of marketers must be clearer about the use

and sharing of consumer data.2. Classify data and mitigate use risks. Marketing data should be classified to identify various types

of risks, and appropriate mitigations for these risks should be put in place. 3. Limit downstream risks. Data brokers should have contracts with all downstream users of the data

to ensure it is always used appropriately. 4. Help enforce ethical practices. Everyone in the marketing ecosystem should assist regulatory

authorities in enforcing ethical practices by reporting bad actors to the appropriate enforcement bodies. 5. Educate consumers about common marketing practices. The marketing industry should support

and engage in developing education for consumers about common marketing practices.

Acxiom firmly believes the time to act on these recommendations is now. It cannot be stated often enough that while much marketing data is not sensitive, it can become sensitive when combined with other data or through sophisticated analytical processes, especially if it falls into the wrong hands. We must never forget that big data for marketing purposes demands equally big security.

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“Big data for marketing demands big security.”

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Establishing Ethical Guidelines for Modern Data-Driven Marketing

BackgroundEthics are the moral principles that govern behavior. In other words, they help people or groups distinguish between right and wrong. Many religions and professions have devised formal, specified ethical codes, including: medicine, accountancy, the law, journalism, finance, and the military.1 Ethical codes go back centuries to places like Egypt with the Maat2, and modern-day Israel with the Torah3, representing the earliest and best preserved ethical codes.

There are several different ways to think about ethics:

• Virtue-based ethics emphasize the importance of character and good habits in driving moral behavior. This is where the idea of “fairness” comes into play.

• Duty-based ethics focus on obligation as the basis for ethical behavior. One branch of this field is the “rights theory,” which considers rights as natural (not invented by man), universal (not cultural or country-specific), equal (for everyone regardless of gender, race, age, etc.), and inalienable (they cannot be sold, bartered or renounced). As an example, Europeans generally believe that data protection is a fundamental human right.

• Outcomes-based ethics determine the rightness or wrongness of an action based on a cost/benefit analysis of an action’s consequences. An action may be regarded as morally right if the consequences are more favorable than unfavorable or if it promotes the greatest utility for the greatest number.

When considering ethics, we often view them through one of these lenses; however, we should employ a combination of all three to achieve the best outcome.

Understanding Different PerspectivesWhile we won’t over-emphasize the differences in these ethical frameworks, acknowledging the philosophical paradigms that people embrace helps us better understand their different perspectives. Purists may assert that privacy is a human right, can only be compromised if the individual provides consent, and can’t be trumped by major public interest. Conversely, pragmatists might regard privacy from a cost/benefit perspective, where privacy may be priced, traded or suspended in the interests of the collective good.

Ethical codes of conduct are typically adopted by organizations to help them understand the difference between “right” and “wrong,” and apply that understanding in their decision-making. Often the phrases “ethical code,” “moral code,” “code of conduct,” and “code of practice” are used interchangeably, but there are some distinctions between them.

• An ethical or moral code starts by setting out the underlying values for the code and describes an organization’s obligations to its various stakeholders. It is addressed to the public. It explains the organization’s activities and the way it does business. It includes specifics on how the company plans to implement its values and vision, as well as guidance on ethical standards and how to achieve them. Ethical codes may also apply to the culture, education, and religion of a whole society.

• A code of conduct is generally addressed to and intended for employees or members. It usually sets out restrictions on behavior, and will be far more compliance or rules focused than value or principle focused. Codes of conduct are often adopted by companies not to promote a particular moral theory, but rather because they are seen as important for effectively operating an organization in a complex environment where moral concepts play a crucial part.

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• A code of practice is a code of conduct adopted by a profession or an organization to regulate that profession or its membership. It addresses difficult issues, including tough decisions that often need to be made, and provides a clear account of what behavior is considered “ethical” or “correct” or “right” in the circumstances. In a membership context, failure to comply with a code of practice can result in expulsion from the professional organization.

Observations on Ethical Marketing and Advertising The fields of marketing and advertising have been guided by codes of conduct for many years. For marketing, one of the earliest codes in the U.S. is the Direct Marketing Association’s Ethical Marketing Guidelines4, which dates from the early 1980s. More recently, in response to fresh advances in data and technology, newer codes have been developed, including: the Digital Advertising Alliance’s Self-Regulatory Principles5, the Interactive Advertising Bureau’s Member Code of Conduct6, and the Network Advertiser Alliance Code of Conduct.7

There are also numerous advertising codes in the U.S. and abroad. Here at home, there is the AAAA’s Standards of Practice8, as one example. Abroad, there are several more, including: the NZ Advertising Standards Authority Code of Practice9, the UK Advertising Code of Conduct10, and the Advertising Standards Authority of South Africa11.

Like any industry, advertising needs to operate under standards and codes that ensure the rights of consumers are protected. Worldwide advertisers must comply with the law, be truthful, not mislead or deceive, and be socially responsible. Other guidance applies when advertising to specific audiences, like children, or for specific products, like alcohol, health, and financial products. For the most part, these older codes apply to the content of an advertisement, but do not usually address the data used to determine who is presented with the ad.

New Challenges

As the world of traditional direct marketing and advertising merges into multi-channel marketing and targeted advertising driven by much richer data on individuals and devices, gaps in the ethical guidance codes have emerged.

At the September forum, Acxiom identified three distinct areas for discussion where gaps in guidance exist in the U.S. and abroad:

• Sharing data for marketing and advertising purposes (both personally identifiable information and anonymous information)

• Employing sensitive data for marketing and advertising purposes

• Applying robust analytics (e.g., big data analytics) for marketing and advertising purposes

“Marketing and advertising have been guided by codes of

conduct for many years.”

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Establishing Ethical Guidelines for Modern Data-Driven Marketing

Each area is examined in detail below.

Data Sharing for Marketing and Advertising

A Brief History

Data has been shared for marketing purposes for decades in the U.S. and around the world. Personal data has been shared with great frequency in the catalog and publishing industries, as well as other industry segments, such as retail. While most consumers in the early days didn’t mind this sharing, a small percentage objected. So the U.S. Direct Marketing Association (DMA) developed a set of ethical guidelines, which in part required companies sharing their customer data to give notice to consumers and offer them the ability to opt out of that sharing. More recently, the DMA’s Commitment to Consumer Choice12 website, offered consumers an easy, one-stop option to exercise their choice to opt out of receiving direct mail from member companies. Over the years other ethical standards addressing such issues as list rental agreements and data compiler (aka data broker) practices have been incorporated into the DMA’s Guidelines for Ethical Business Practices.

In the late 1980s and early 90s, aggressive telemarketing became a common practice, and states began enacting Do-Not-Call registries where consumers could list their telephone numbers to prevent unsolicited calls from companies with which they did not want to do business. In 2003, most of these state laws were superseded by the federal Do-Not-Call Registry administered by the Federal Trade Commission. One of the FTC’s most successful initiatives, it now comprises over 217 million registered phones. As mobile phones became more popular, the rules were updated, and companies needed express permission to call prospects on their mobile devices for marketing purposes. In addition, robo-call guidelines have also been developed by the FTC.

In the early 2000s, the practice known as behavioral targeting came into vogue, in which third parties collected anonymous data about the Internet sites a browser visited. This data was used to create profiles that were sold to advertisers for targeting ads to that browser when he or she visited other, unrelated sites. To allay privacy concerns from regulators and consumers about the practice, the Network Advertiser’s Initiative (NAI) was formed. The NAI created a self-regulatory code of conduct for network advertisers — the third-party companies that collected the behavioral data and sold it to advertisers. This is a great success story in self-regulation because over 99% of the industry now participates in the code. The code provides clear, easy-to-use notice and choice mechanisms that vary based on the sensitivity and the proposed use of the data.

In more recent years, the Digital Advertising Alliance (DAA), made up of the seven largest marketing and advertising associations, introduced standards consistent with NAI’s guidance for network advertisers, but which were designed to address the broader advertising ecosystem, requiring the use of the “AdChoices Icon” in ads that were behaviorally targeted. This icon links to an industry website that lists all of the network advertisers, and offers consumers a simple, industry-wide, opt-out mechanism. Over one trillion times each month ads are served with the icon, and 35 million unique visitors have checked out the site, with more than 4 million exercising their choice. The DAA reports that 51% of consumers say they are more likely to click on relevant ads featuring the icon, and more than 73% are more comfortable knowing that the companies abide by the safeguards.

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As we have moved into the era of mobile and addressable TV, the DAA has once again updated its ethical standards, releasing mobile guidelines consistent with their online principles and launching an app for consumers to manage third-party tracking across apps. The self-regulatory and legislative tenets — notice, choice, and security — of the marketing industry, which were built on the sharing of data, have been consistent for decades.

Each month over one trillion ads are served with this AdChoices Icon, which enables consumers to exercise control over behaviorally-targeted advertising. 51% of consumers say they are more likely to click on relelvant ads featuring the icon.

Our Modern Data-Driven Economy

Today we live in a data-driven economy supported by advertising. A study by the Data-Driven Marketing Institute (DDMI) found that in 2012 the data-driven marketing economy (DDME) added $156 billion in revenue to the U.S. economy, fueling more than 675,000 jobs. And 70% of the value of the DDME — $110 billion in revenue and 478,000 jobs — depends on the ability of firms to exchange data across the ecosystem.

Data fuels innovation. And every year more and more innovative products and services appear in the marketplace. Businesses, regulators, advocates — and many consumers — acknowledge the benefits that accrue to the individual and to companies from data sharing. Consumers learn about all kinds of new and beneficial products and services. They receive special deals they are more likely to be interested in and receive fewer unwanted offers (SPAM or junk ads). Companies profit from a greater return on their marketing investment and small businesses enjoy cost-effective access to prospects to grow their companies. It’s vital for consumers and businesses alike that we continue to share data for marketing purposes. The question is: How do we share data in a legal and ethical way when increasingly the data is analyzed — and new insights are derived — with no direct interaction with the individual consumer?

Some aspects of data sharing are important to note. For most individuals, concern grows or lessens depending on whether the data is shared within an organization, with an affiliate organization, or with an unaffiliated third party.

The key concerns that consumers express vary widely from individual to individual. However, most of these concerns relate to an expectation that data will be used solely by the company that collected it (and not shared with others), as well as an absence of knowledge about who the data is shared with, and for what purposes.

“The data-driven marketing economy added $156 billion in revenue to the U.S. economy,

fueling more than 675,000 jobs — and 70% of that value

depends on the ability of firms to exchange data across

the ecosystem.”

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Establishing Ethical Guidelines for Modern Data-Driven Marketing

Also, consumers are apprehensive about their lack of bargaining power with the parties with whom the data is shared (the data is “out there” and the consumer is no longer in control). For consumers, who generally don’t understand the risks involved, this loss of control over their own data feels creepy. And they may also be anxious that marketers know too much about them (a feeling that they are being observed). Consumers may fear both tangible harms (e.g., bodily harm and discrimination) and intangible harms (e.g., reputational or emotional harm).

Lately, these concerns have grown because the amount of data being shared and the number of companies who share data have increased, exacerbating the feeling that data collection truly is “out of control.” Consumers also fear there are more bad actors now than in the past. This has led to a fear of being profiled in a narrow way that may limit, not enhance, their opportunities.

Employing Sensitive Data for Marketing and AdvertisingHistorically, the marketing industry had simple definitions for sensitive data. It was data about children, data about health, and data about finances. Today there are all kinds of new sensitive data, such as location data and biometric data (e.g., facial recognition data), which can be very revealing about our activities and relationships. What’s more, through sophisticated analytics, companies can take data that is not sensitive at all and predict, to a high degree of accuracy, very sensitive insights about individuals, such as whether they are pregnant, what kinds of diseases they are likely to have or develop in the future, and what their financial situation is.

Degrees of SensitivityThe DMA, DAA and NAI define sensitive data as described below. Each code of conduct has certain restrictions or prohibitions on the use of this sensitive data. • Third-party behavioral and multi-site data used for interest-based advertising that is collected from children

under 13 on child-directed websites must be collected in compliance with the FTC’s Children’s Online Privacy Protection Act (COPPA) and can only be used with parental consent.

• Third-party, multi-site data containing financial account numbers, Social Security numbers, pharmaceutical prescriptions, or medical records about an individual cannot be used for interest-based advertising without opt-in consent unless the records are de-identified according to HIPAA regulations.

• Behavioral or multi-site data used for interest-based advertising is prohibited from being used for eligibility determination for employment, credit standing, healthcare treatment, and insurance underwriting.

The issues become more challenging when companies are able to predict sensitive data from non-sensitive data with sophisticated analytical processes. This practice raises a whole new set of questions about predictive results. For example, should we treat predictive data about sensitive medical conditions different from other forms of fact-based sensitive data? Should the individual have a say in the prediction?

Sometimes it can be difficult to predict the sensitivity of data when it is first created, before all the various applicable uses can be understood. It may take years to fully recognize the resulting sensitivity. Some data may seem non-sensitive at first, but when collected in very large quantities over time, it may become very predictive (e.g., NSA metadata, location data, biometrics, and other tracking data collected over time).

“Today there are all kinds of new sensitive data that can be very revealing about our activities and relationships.”

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For data we identify as sensitive, the industry has historically punted the ball to the individual, asking him or her to grant permission to use the data in various ways, including for marketing purposes. However, this approach isn’t very effective when there are legitimate uses of sensitive data for marketing purposes if effective mitigations are identified to avoid harmful outcomes. For example, some companies classify data elements that they bring to market, both core data and derived or modeled data, as either: (1) Generally Available (or not sensitive); (2) Restricted (with four restricted sub-classifications); or, (3) Prohibited (data that won’t even be collected for sale). The restricted classification has appropriate mitigations in place to make its use acceptable. For example, restricted medical interests must be properly collected and can only be sold to the medical industry.

As with data sharing, consumer concerns regarding the use of sensitive data vary widely from individual to individual, and involve differing degrees of sensitivity according to the circumstances. There is not a static list. It is safe to say, however, that concerns are greater when sensitive data is shared than non-sensitive data — and that the greatest areas of concern over sensitive data relate to whom the data is shared with and for what purposes. There are some situations for consumers in which any sharing of sensitive data for marketing feels disturbing.

The benefits that accrue to the individual and to companies from using sensitive data for marketing purposes are similar to those that accrue from data sharing. Consumers are exposed to innovative and beneficial products and services they are more likely to be interested in, and receive timely information regarding important topics like medicine and finance. Companies gain a greater return on their marketing investment, while small businesses obtain cost-effective access to fresh prospects to increase their revenues.

Applying Robust Analytics and Modeled Data for Marketing and Advertising For decades, the marketing industry has drawn simple inferences from data to better identify and understand their best audiences. If an individual subscribed to a hunting magazine and owned a hunting license, marketers assumed he had an interest in hunting. If a consumer frequented travel websites and made travel-related purchases, marketers concluded that she — or a family member, or even a close friend for whom she bought gifts — liked to travel. These approaches were pretty accurate in identifying what a person shopped for and consequently might want to buy. Overall, they worked well for marketing purposes and were certainly much better than having no data at all.

Today’s analytics have expanded far beyond these simple inferences. Modern marketers are using data to accurately predict things previously unimaginable — if a consumer is likely to be in the market for a new SUV, for example, or shows a propensity to travel abroad, or possesses characteristics in common with those who enjoy fine wine. From an analytics perspective, there are several types of statistical approaches:

• Simple Derivation: a subscription to Golf Digest equates to an interest in golf (widely used in the 1970s–80s)• Statistical Model: people with a certain size house in a certain zip code who subscribe to financial magazines

and have a graduate degree are likely to have an income within a certain range (popular in the late 1980s) • Population Segmentation: people of a certain age, who live in certain neighborhoods and drive certain types

of cars are likely to fall into a certain demographic group, e.g., baby boomers (popular in the early 1990s)• Propensity Score (sometimes known as a look-alike score): a group of people who have predominant

characteristics (certain age, certain income, certain education, certain hobbies) which can then be overlaid on another population of people to find more individuals or households with the same characteristics; for example, people who often travel abroad exhibit certain demographic characteristics, and others with those same characteristics are also highly likely to be interested in traveling abroad (popular in mid-2000s)

“Sophisticated analytics have led to superior data, which has powered innovation and significantly enhanced results.”

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These analytical approaches all result in a prediction and, while they are usually quite accurate, there are always a few people for whom the prediction is wrong. These predictions are, however, effective enough (again, better than no data) for identifying audiences for marketing and advertising purposes. It is important to point out that these kinds of predictions may not be as successful for non-marketing purposes.

Historically, these kinds of predictions were calculated periodically and stored on a file. More often today they are calculated on the fly based on the most recent data possible, possibly data generated minutes or even seconds before the calculation.

Sometimes these analytical predictions are made by the company who will use them. In other situations, a third party makes the analytical prediction and sells it in the marketplace. In other words, a social media site or a data broker may make a prediction with their third-party data about whether a consumer is in the market for a new SUV and sell that prediction to auto dealers with SUV inventories.

Consumer Concerns

Here too, consumer concerns vary widely from individual to individual, but generally involve a lack of understanding of these analytical processes and how they are used. They can sometimes be viewed as a “black box” over which the consumer has no control, and are therefore very scary. The box can’t be transparent about the algorithm or easily challenged if it is wrong. Consumers don’t know who is performing these analytics, what predictions they are making, or to what end they will be used. If analytics of non-sensitive data can create sensitive data, the question arises: Are proper precautions being taken with it? If sharing feels creepy to consumers, then analytics can feel really creepy. Consumers want to know what profiles they fall in, and some worry they are being profiled in ways that limit their opportunities or even discriminate against them.

In just the last few years, the proliferation of analytics and the number of companies who use them have grown exponentially. Sophisticated analytics have led to superior data, which has powered innovation and significantly enhanced results. And while we in the industry understand many of the extraordinary benefits that derive from big data analytics, consumers often feel that these practices have taken data about them to a new level of “out of control.”

Recommendations on Ethical Marketing and Advertising Acxiom believes it is time for a new approach to safeguarding individuals in the era of big data while maximizing the value that appropriate innovation brings. And we believe that the challenge should be viewed through the lens of ethics, not just privacy or data protection.

In the Information Accountability Foundation’s paper, “Big Data Ethics Project: A Unified Ethical Framework for Big Data Analysis,” several ethical values are put forth. The recommendations in this white paper support those values as follows:

• Beneficial – Classify data and mitigate use risks

• Progressive – Educate consumers about common marketing practices

• Sustainable – Limit downstream risks

• Respectful – Maximize transparency and choice

• Fair – Help enforce ethical practices

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In the spirit of not letting our desire for perfection defeat progress, Acxiom has identified five areas where stronger ethics should be introduced into the marketing ecosystem. Some of these are not new, some have already been suggested by regulators and advocates, and some stem from the world of big data analytics in which we live.

Maximize transparency and choice: Privacy policies of all companies across the marketing ecosystem must be clearer about the use and sharing of both personally identifiable and anonymous data, and consumer-facing companies should be clear when data is being shared with third parties, especially sensitive data. Transparency and choice can be aided by the use of more layered notices and pop-up notices. All parties (first and third) should provide opt-out opportunities to the marketing data they use and, where economically feasible, they should also provide access and correction. Where access and correction are not feasible, they should describe the types of data being used and shared.

Classify data and mitigate use risks: Marketing data should be classified to identify various types of risks and appropriate mitigations for these risks put in place. Marketing data should be anonymized wherever possible.

Limit downstream risks: Data is often shared several times by intermediaries before it reaches the hands of the ultimate user, the marketer. Data brokers should have contracts with all downstream users of the data (marketers or intermediaries) that prohibit discriminatory marketing practices and the use of marketing data for eligibility purposes (e.g., credit, insurance, employment).

Help enforce ethical practices: Everyone in marketing should help the appropriate authority — whether a self-regulatory entity or a regulator — enforce ethical practices by reporting bad actors to the appropriate enforcement body. A defined process for investigating and taking appropriate action should be in place for the whole ecosystem.

Educate consumers about common marketing practices: The marketing industry should support and engage in developing education for consumers about common marketing practices, so consumers can exercise the choices they’re offered in an intelligent way — not because they are afraid of the unknown. One example of this type of education is the Council of Better Business Bureaus’ Digital IQ project.

Acxiom firmly believes the time to act on these recommendations is now. It cannot be stated often enough that while much marketing data is not sensitive, it can become sensitive when combined with other data or through sophisticated analytical processes, especially if it falls into the wrong hands. We must never forget that big data for marketing purposes demands equally big security.

The Digital IQ™ Initiative

In 2014 the Council of Better Business Bureaus (BBB) joined forces with Acxiom Corporation to help consumers develop greater Internet know-how and boost their overall digital competency. Initially, the Digital IQ Initiative is focusing on savvy shopping, but over time it will include broader issues related to the uses of big data and sophisticated analytics that now affect the daily lives of consumers and the important choices they are making. If your organization is interested in supporting the Digital IQ Initiative, please contact Joseph McMahon at BBB (703-247-9387 or jmcmahon@council.bbb.org) or Jennifer Glasgow at Acxiom (501.252.2316 or jennifer.glasgow@acxiom.com).

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Establishing Ethical Guidelines for Modern Data-Driven Marketing

Endnotes

1. A sampling of ethical codes among various organizations includes: – Hippocratic Oath, http://www.medicinenet.com/script/main/art.asp?articlekey=20909 – American Medical Association’s Code of Medical Ethics, http://www.ama-assn.org/ama/pub/physician-resources/medical-

ethics/code-medical-ethics.page – Code of Ethics for Nurses, http://www.nursingworld.org/codeofethics – American Institute of CPAs Code of Professional Conduct, http://www.aicpa.org/RESEARCH/STANDARDS/

CODEOFCONDUCT/Pages/default.aspx – American Bar Association Model Rules for Professional Conduct, http://www.americanbar.org/groups/professional_r

responsibility/publications/model_rules_of_professional_conduct/model_rules_of_professional_conduct_table_of_contents. html

– Society of Professional Journalists Code of Ethics, http://www.spj.org/ethicscode.asp – Code of Ethics of the American Library Association, http://www.ala.org/advocacy/proethics/codeofethics/codeethics – National Association of Personal Financial Advisors Code of Ethics, http://napfa.org/about/CodeofEthics.asp – US DOD Military Code of Ethics, https://kb.defense.gov/app/answers/detail/a_id/461/~/military-code-of-ethics – Golden Rule (Ethic of Reciprocity), http://en.wikipedia.org/wiki/Golden_Rule – Declaration of Geneva (Physician’s Oath), http://en.wikipedia.org/wiki/Declaration_of_Geneva

2. Egyptian Maat (ca. 2375 BCE and 2345 BCE), http://en.wikipedia.org/wiki/Maat

3. Torah, http://en.wikipedia.org/wiki/Torah

4. Direct Marketing Association Guidelines for Ethical Business Practice, https://thedma.org/wp-content/uploads/DMA-Ethics-Guidelines.pdf

5. Digital Advertising Alliance Self-Regulatory Principles, http://www.aboutads.info/principles

6. Interactive Advertising Bureau, http://www.iab.net/public_policy/codeofconduct

7. Networks Advertiser Alliance Code on Conduct, http://www.networkadvertising.org/2013_Principles.pdf

8. AAAA Standards of Practice, http://www.aaaa.org/about/association/pages/standardsofpractice.aspx

9. NZ Advertising Standards Authority Advertising Code of Practice, http://www.asa.co.nz/pdfs/ASA_Codes.pdf

10. UK Advertising Codes, http://www.cap.org.uk/advertising-codes.aspx

11. Advertising Standards Authority of South Africa, http://www.asasa.org.za

12. U.S. Direct Marketing Association Commitment To Consumer Choice, https://www.dmachoice.org

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