The GDPR is in effect in the European Union. This regulation is meant to protect not only consumer privacy and consumer data, but also the processes that use this data to make decisions about consumers.

Marketers may think that if their data practices are compliant, then they can move forward without worrying too much about GDPR, but that’s not the case. New technologies and techniques that use consumer data must also be put through the privacy lens. That includes looking at complex processes like AI and machine learning as well as everyday marketer activities like campaign targeting.

The Right to Opt Out of Machine Processes

The GDPR regulation not only requires consent from consumers before their data can be used, it also requires that they consent to “profiling.” The regulation specifies profiling as a “procedure which may involve a series of statistical deductions … often used to make predictions about people.” This includes any technical process that uses machine learning, algorithms, or even simple rules to put people into buckets or make decisions about them. Use case examples cited most frequently include processes that automatically qualify people for certain products, such as credit cards. While profiling people in a way that hurts individual's ability to obtain credit lines or even medical procedures can have unsettling outcomes, marketers selling much less sensitive products should consider the far-reaching consequences of their marketing activities as well. 

The typical retail marketer uses consumer shopping data to determine which product images to include in any email marketing campaign. People who shopped for patio furniture might be shown an offer for an umbrella, while people who shopped for a new doormat might be shown an ad for a new mailbox. If this type of “profiling” is occurring in your marketing team, it is likely necessary to obtain consumer permission.

The Difference Between Targeting and Discrimination

Targeting is an important element of digital marketing. Not only does targeting increase the chance of marketers getting relevant communications in front of consumers, it also decreases the chance of wasteful campaign messaging and unnecessary media spending. However, not all targeting is equal in the eyes of the EU privacy regulation. Even for companies that do obtain permission to profile, marketers must continue to be aware of every campaign and remain sensitive to “safeguards aimed at ensuring fairness, non-discrimination, and accuracy in the profiling.”

Using profiling to determine if someone might want an umbrella or a mailbox is one thing, but consumers may see these forms of targeting as discriminatory if targeting is based on sensitive factors such as income or race.  For example, imagine if a machine learning algorithm determines that a certain target demographic prefers a fast-food value hamburger meal compared to another demographic which prefers salads. If those recommendations align such that a lower income group or certain race is targeted with the hamburger, that could be seen as discriminatory because the hamburger is a less healthy item.

More Accuracy Is Good for AI and People, too

The GDPR push for more accurate profiling provides marketers with the chance to evaluate the source of their data as well as the processes they use to target and profile consumers. A Deloitte study found that only 29 percent of third party data vendors were accurate more than half of the time. In other words, only 29 percent of these vendors were better than the flip of a coin. 71 percent were actually worse than guessing! Data accuracy can be enforced by testing partner vendors frequently and by working hard to collect and refresh first-party data more often. This increases relevance and decreases third party data costs -- a win-win.

Deploying more accurate and precise AI algorithms should be a focus area for marketers. The more you can pinpoint valuable data points, the less you have to rely on having massive volumes of data. Ultimately, GDPR and regulations like it are great for AI, marketers, and consumers alike.  In a quest for relevance, many relationship marketing programs are likely to be as off track as the well-known Gillette targeting debacle that failed to reach its target audience.

The good news about the GDPR rules is that it should align with everyone's best interests over time. In the near future though, marketers will find that they're better off shifting some marketing goals away from short term gains like scale or sales in consideration of longer-term goals like lifetime customer value. Since it is these short-term goals that inflate the value of third party data, make AI less accurate, or even discriminate against consumers, we can all say “good riddance.”


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Be Human and Turn GDPR To Your Advantage

With its built-in accountability principle, the GDPR presents an opportunity to win customers’ trust – and outperform the competition – by creating transparent data collection policies. Find out how you can take advantage of the opportunity to become more "human" in collecting data with this Selligent Marketing Cloud white paper

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