Are Hyper-Personalization and an Individual's Control of Data at Odds?

Individuals want to control their data, but they also want their interactions with brands to be relevant. Businesses bear the burden of striking a balance.

Lisa Morgan, Freelance Writer

June 10, 2024

6 Min Read
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Polarmouse / Stockimo via Alamy Stock

Are hyper-personalization and user control of data at odds? In a word, yes. The more data businesses have on customers, the more personalized their offers can get. But with laws such as GDPR, CCPA and increasing regulation in general, businesses must find a way to meet their own goals and satisfy customers while staying compliant. 

“When I was with Lenovo and General Motors, I witnessed firsthand the delicate balance organizations must strike between leveraging data for personalization and respecting user privacy,” says Professor Timothy E. Bates at the University of Michigan in an email interview. “The rising user control over data presents a nuanced challenge for hyper-personalization efforts. It restricts the breadth and depth of data available for creating highly personalized experiences, potentially diluting the effectiveness of these initiatives.  

However, there is an opportunity for innovation when it comes to how data is collected, processed, and utilized.  

“At Lenovo, we leaned into transparent data practices and user consent mechanisms, which not only complied with regulatory requirements like GDPR but also fostered trust among our user base,” Bates says. “This trust, in turn, often led to users being more willing to share their data, knowing it was being used responsibly and with their consent.” 

Related:What the American Privacy Rights Act Could Mean for Data Privacy

Organizations are addressing the dilemma by adopting privacy-by-design principles, where data privacy and user control are not afterthoughts but foundational elements of product and service development, Bates says. This approach involves anonymizing data where possible, enhancing data security measures, and providing users with clear, accessible options to manage their data preferences. 

From an IT perspective, Bates outlines several strategies to support hyper-personalization -- commonly defined online as how a business draws on customer data to craft contextual communications -- in the new data landscape: 

  • Invest in privacy-enhancing technologies (PETs): Technologies like federated learning, differential privacy, and homomorphic encryption can enable data analysis and personalization without compromising user privacy. 

  • Enhance transparency and user control: Develop and implement clear user interfaces that allow users to easily understand and manage their data preferences and consent. 

  • Foster a culture of data ethics: IT teams should champion the cause of ethical data use within organizations, ensuring that all personalization efforts are aligned with ethical guidelines and respect user privacy. 

  • Leverage AI responsibly: Utilize AI and machine learning algorithms to identify patterns and insights within the constraints of available data, optimizing personalization strategies within the boundaries of user consent. 

Related:How AI is Reshaping Retail

“By prioritizing user trust and ethical data use, organizations can navigate the evolving expectations around hyper-personalization and data privacy, ultimately finding creative solutions that respect user autonomy while delivering personalized experiences,” Bates says. 

Cookies Anyone? 

Google began sunsetting use of cookies this year. For large, global organizations, implementing technologically challenging solutions is achievable, but doing so proves more difficult for smaller organizations with fewer resources and smaller tech teams, according to Rico Dittrich, project lead and privacy ambassador at data company fifty-five

“The currently known workaround is to place information in the browser that adds users to an affinity or in-market category rather than a unique ID value. This is technologically challenging, and smaller players will not be able to compete with the larger players to build resilient solutions that browser developers (read: Apple, Mozilla, and Google) and lawmakers will consider compliant and transparent,” Dittrich says in an email interview. “The biggest opportunity for new players is to innovate on how to detect and identify valuable user behavior that qualifies to be included in a segment that will then be used for targeting purposes. Being truly innovative and incorporating AI/ML technology should enable even the smaller players to add value to business customers.”  

Related:OpenAI's ChatGPT Violates GDPR: Italy's Data Watchdog Says

Customers and prospects are more willing to share data with companies they trust. One way to get them to share more information is to explain why sharing the data is in the customer’s best interest. For example, a lot of retail brands offer a 10% discount if a user agrees to share their email address and mobile number.  

However, the implementation of progressive consent may be at odds with the customer’s expectation and preferences. For example, some retail brands appear to offer a 10% discount if the site visitor shares their email address, but that’s only the first step in a two-step process. The following screen requests a mobile number for text promotions, which may seem to create more digital noise. 

“[T]he legacy approach was a terms and conditions or a preference center that was a big, long document. Nobody's going to read that,” says Ray Velez, CTO for customer data at digital business transformation and consulting company Publicis Sapient. “[T]rust provides a value proposition and helps you [to} kind of progressively or incrementally improve that relationship with the customer. So, we can use your location data, because that will help us provide offers in your region or it will help us drive better shipping to your location. Whatever it might be, communicate that value proposition and be transparent in that trust, and make that part of your new progressive content strategy. [T]hat helps you build your zero-party and first-party data.” 

Velez uses multivariate tests to determine what will yield the highest opt-in rates.  

“So, you take an experience and maybe I'm asking for five or six different data attributes that will help me personalize your experience, but I notice when I ask for a birthday, nobody finishes it. [M]y multivariate test informs me to optimize that progressive consent form and now I have my highest opt in rates,” says Velez. 

Modern content management solutions also enable compliance reporting. Specifically, they help users structure metadata and data attributes so they can get the right type of reports. 

“Because data structures and databases have predefined schema and taxonomies you can interrogate those schemas and taxonomies and you can notice, for example, that somebody is in Salesforce and they created a new campaign that captures zip codes and I’m not sure it’s compliant,” says Velez. “So, you run this capability that interrogates these data structures, finds an issue, raises a flag, runs a report [so] somebody [can] make sure that the zip code capture is in compliance or not compliant.” 

Bottom Line 

Though user control of data makes hyper-personalization more difficult, there are ways to approach the problem that increases user consent without running afoul of privacy regulations.  

About the Author(s)

Lisa Morgan

Freelance Writer

Lisa Morgan is a freelance writer who covers business and IT strategy and emerging technology for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include big data, mobility, enterprise software, the cloud, software development, and emerging cultural issues affecting the C-suite.

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