Trading Off Privacy for Personalization

Trading Off Privacy for Personalization

Target, Marriott, TJ Maxx, Macy’s, Saks Fifth Avenue and many other major brands have been the victims of data breaches that exposed personal information about hundreds of millions of their customers. The increasing frequency and size of these leaks have resulted in actions to improve privacy protections and ensure tighter security, including GDPR, which is one of the most stringent legal frameworks guiding the collection and processing of personal information.

Yet, despite these issues, consumers still willingly share personal information when they join a loyalty program, sign up for a branded credit card or fill out online surveys.

So what gives? Even though the types of data are very different, consumers may stop providing information about their preferences that benefit marketing if they feel they can't trust a brand to protect private personal data like credit card and social security numbers, or addresses and other identifiers.

Taking Risk for Relevance

Many consumers are willing to trade off their personal information with a trusted brand in exchange for more relevant offers. In our always-on, real-time culture, consumers expect a personalized experience that is frictionless across all channels.

Consumers want brands to understand and anticipate their needs, get straight to the point and not waste their time. According to Forrester, 80% of US adults said they would feel comfortable sharing at least some kind of information in order to have their shopping experience personalized.

Trust is a major component too. Consumers are willing to provide personal data to the brands they trust, and avoid those they don’t. In fact, up to 80% of consumers said they would leave a brand if their data had been misused more than twice. For consumers, it didn’t matter whether a company used data without their knowledge or hackers stole it – either way it ended up being used by someone they didn’t trust with the information.

And questionable tactics using personal data also raised red flags. A March Gartner survey showed that nearly 40% of customers would stop doing business with companies if their personalization was “creepy,” such as using retargeting ads or pushing items left in online shopping carts.

Putting Personalization in the Hands of Consumers

The key to making consumers comfortable with walking a fine line between privacy and personalization is putting the power in their hands. Successful brands give consumers more control over what they share, and how it’s used to deliver a more relevant and personalized customer experience.

There are many brands that effectively use personalization, while maintaining a high level of trust. A SmarterHQ study found that Amazon was the most trusted among major technology companies for responsible data practices, followed by Apple.

Another great example of a brand that balances personalization and privacy is Airbnb. The key to their success: getting users to provide the information proactively. One way Airbnb does this through its Trip Matcher quiz, which allows users to answer targeted questions to personalize their browsing experience.

The Next Step: Harnessing Customer Information With AI

Once they have the customer data – whether it’s the user provided information, like that gathered by Airbnb’s Trip Matcher, or collected from loyalty programs, online surveys and purchase histories – brands need to figure out how to make the best use of it.

Here’s where many brands struggle. Some rely on segmentation, or even microsegmentation, to break consumers into smaller, like-minded cohorts. But these exercises are not effective in reaching consumers on the personal level they desire, and expect. And attempting to dive deeper and do 1:1 personalization with traditional marketing tools is not possible; it requires too much time, effort and manpower for the marketing team to be effective.

Achieving true, 1:1 personalization “is only possible with machine learning and AI — deep learning technology that enables you to not only predict behavior by looking at interaction history, but determine intent by looking for and finding patterns in the data," Michael Fertik founder and managing partner of Heroic Ventures, and founder and executive chairman of Reputation.com wrote last fall in Forbes.

Tools like AI and ML automate the collection and analysis of data from across all channels, throughout the customer journey, and provide the power and intelligence to develop highly relevant offers to each individual at enterprise scale.

With the right tools, personalization and privacy can be compatible. “In fact, [they] can be mutually accretive, if there is a knowing trade between the person/consumer and the company or companies using his or her data,” Fertik noted. “When that happens, you can get the best of both values: Control over your data and far better products, services and experiences.”

If you’re looking at strategies to deliver 1:1 personalization at scale, and deliver the experience your customers desire, download our white paper, “The CX Effect: Why Marketers Need to be More Customer Centric.” There you’ll find six steps that are critical to developing a customer-centric marketing strategy and learn how to implement AI and ML in your business.