In today’s digital age, consumers are increasingly seeking more personalized products and services, and a customized experience. And although personalization is nothing new, it has evolved radically in the last 30 years with large businesses able to use AI and technology to cater to these demands. Just look at the latest frenzy, GPT, to get a sense for how technology is accelerating its impact on marketing, customer service, and personalization.

Already a wide variety of personalization techniques are employed by businesses to tailor to individual preferences and improve the customer experience. It’s been 30 years in the making, starting with early adopters using simple techniques such as addressing a direct mail letter with first name rather than “Current Resident,” to today’s savvy enterprises using massive databases of consumer behavior and advanced analytics to provide hyper-conditional content, individualized promotions, and concierge-like digital services.

But a counter dynamic is also at play. As personalized products and services have become more prevalent, consumers have also awakened to how their data is collected and even misused. Because of this some are less likely to share information, push for more legislation, more frequently opt out, and even ask for their data to be deleted. Clear battle lines have been drawn between hyper personalization and privacy.

This presents a dilemma for businesses, as they attempt to balance providing personalization in a responsible and controlled manner. Consumers are fickle. They want great experiences, but they also expect that any data they turn over is secure and is used in compliance with their wishes. In this context, it’s crucial for companies to strike the right balance between personalization and privacy protection.

The Value of Personalization

When asked, consumers repeatedly respond that they want more personalization (in many cases greater than 75%), especially younger people. [i] When they see customized ads fitting their preferences and behaviors, they’re more likely to engage and then purchase. This benefits both the consumer, who gets offered interesting products or services, and the company, which increases its revenue and profits. Moreover, personalized recommendations can create a sense of loyalty and trust between the consumer and the company, leading to repeat business, long-term customer retention, and positive word-of-mouth marketing.

Personalization has become a principal factor in consumer decision-making. A study by Epsilon found that 80% of consumers are more likely to do business with a company if it offers a personalized experience. [ii] Personalization has many benefits for consumers, such as saving time and increasing convenience. For instance, personalized recommendations on e-commerce websites can help consumers find and then ask for products that they may not have otherwise considered. Similarly, personalized apps can help users achieve their goals by providing services like tailored financial plans and wellness insights & activities.

Some consumers may view the collection of their personal data as a fair trade-off to get more personalization. They accept that the exchange of their data is worth getting good recommendations, more perks, and a better overall experience. And these consumers assume and inherently trust that businesses will use their data responsibly and will take the necessary steps to protect their privacy.

But not everyone thinks that way about turning over their data and trusting businesses.

The Need for Privacy

There is another camp of consumers that prioritize privacy and may view personalization as a threat to their rights. They hold that their personal data is being exploited without their consent and that businesses are profiting from their information. And they are very vocal about this, and are influencing their friends, followers, and even law makers.

These consumers are skeptical of businesses’ ability to protect their data and worry that their information could be used against them in the future. As a result, they have pushed for more protections and use various mechanisms (ad blockers, opting out, surfing incognito) to avoid sharing personal information.

They are very hesitant to share what they consider extremely personal information, such as their location, browsing history, or purchase behavior. And they are not a small faction. In fact, a Pew Research Center study found that 79% of Americans are concerned about the way their personal data is being used by companies beyond what they intended.[iii] Years ago, the Cambridge Analytica scandal highlighted these fears, when the data of millions of Facebook users was harvested without their consent and weaponized for political purposes.

Consumers believe they have a fundamental right to privacy and are increasingly demanding more control over their personal data. In recent years, there have been several high-profile data breaches and scandals involving the misuse of personal data. These incidents have increased consumer awareness about the importance of privacy, and they are becoming more vocal about their concerns. Consumers want to know how their data is being used, who has access to it, and how it is being protected.

Consumers are also becoming more aware of their digital footprint and the potential consequences of sharing personal information online. They’re concerned about identity theft, fraud, and other forms of cybercrime. In addition, they worry that their personal information could be used against them, such as by insurance companies or potential employers. As a result, consumers are becoming even more cautious about sharing personal information online, and as such only do it with businesses they trust.

The Role of Trust & Regulation

Trust is a crucial factor in the relationship between consumers and businesses. Consumers are more likely to share personal information with businesses that have not breached that trust and that prioritize their privacy. Even so, trust is fragile, and businesses must work hard to never violate it and always maintain it.

Businesses can build trust with consumers by being transparent about their data collection practices and providing clear explanations of how they use consumer data. They should obtain explicit consent from consumers before collecting any personal information and should provide consumers with the option to opt-out of data collection. And they must ensure that data is protected from data breaches and cyberattacks.

Privacy concerns can also impact consumer behavior in a more general sense. A review of the literature by Taylor and Francis Online found that online privacy concerns can lead to reduced trust in online transactions and lower engagement with online platforms.[iv] This can have significant consequences for companies that rely on online channels for marketing, sales, and deepening relationships with existing customers. What’s more, privacy concerns have a ripple effect across businesses and industries, as consumers become more skeptical with each new incident.

Best Practices

Here is a baker’s dozen of best practices to effectively balance personalization and privacy.

For Personalization:

Rollout individualized personalization – Individualized personalization uses preferences and behaviors of individuals (not segments they belong to) to custom tailor products, servicing, and messaging. It affords numerous benefits, including increased convenience, engagement, and ultimately overall satisfaction. And done right, it will build long-term trust. When personalizing for pre-login purposes (such as for unknown browsers or mobile devices) pay careful attention to whether adtech data collection vendors are using tricks, like cname cloaking, to mask a 3^rd party domain still receiving data when the end consumer may not approve of this. Using a trick like this might erode trust and ultimately backfire.
Build cross-functional personalization teams – Personalization requires input and collaboration from multiple departments within an organization, including marketing, IT, data & analytics teams, and customer support. Building cross-functional teams can help companies break down silos and ensure that all stakeholders are aligned on personalization goals and strategies.
Adopt agile methodologies for feedback and testing – Agile methodologies enable companies to iterate quickly and respond to changing customer needs and preferences. Adopting agile methodologies can help companies test and refine personalization strategies and ensure that they are delivering the right content and experiences to the right customers at the right time. Pick an agile personalization platform. It should be capable of always-on variation testing (runs champion / challenger experiments automatically) and able to deploy necessary adjustments to programs in a day or less not weeks.

For Privacy:

Appoint a Chief Privacy Officer – Appointing a Chief Privacy Officer (CPO) is a critical organizational change that can help companies balance personalization and privacy. The CPO is responsible for ensuring that the company’s data privacy policies and practices align with industry standards and regulatory requirements, while also driving data-driven innovation and personalization.
Establish a clear data governance framework – Companies must have a clear governance framework for data management that outlines data privacy policies, data protection practices, and compliance requirements. This framework should be regularly reviewed and updated to ensure alignment with changing regulations and best practices.
Use privacy nudges – Nudges can be an effective way to help consumers make more informed choices about their data privacy, while still allowing for customization. Privacy nudges are interventions designed to influence behavior without restricting freedom of choice. For example, a company could use a privacy nudge to encourage consumers to read the privacy policy before accepting it. A study by Balebako et al. (2015) found that privacy nudges can be effective in improving privacy outcomes for consumers on social media platforms. [v]
Conduct regular privacy impact assessments – Privacy impact assessments (PIAs) can help companies identify privacy risks and implement appropriate controls to mitigate these risks. Conducting regular PIAs can help companies stay ahead of changing privacy regulations and address potential privacy concerns before they become major issues.
Foster a culture of privacy first – A culture of privacy first starts at the top of the organization, with senior leadership setting an example and emphasizing the importance of privacy in all aspects of the business. Companies can also provide privacy training and awareness programs to all employees, to ensure that everyone understands the importance of privacy and how to protect it.

For making the right technology choices:

Invest in a consent management platform – These platforms allow companies to manage user consent and data collection preferences, enabling users to choose what data is collected and how it is used. Consent management platforms can also help companies comply with regulations such as the GDPR and CCPA, which require informed and explicit user consent for data collection and processing. Invest in a customer data platforms (CDPs) only if first-party data and device identity management is scattered or missing. CDPs are a centralized system combining customer data from multiple sources (such as transaction & behavioral data), device identity, and consent. Companies must be transparent about their data collection and usage practices and provide clear and concise information about how data is being used. This can be accomplished through user-friendly privacy policies, clear consent mechanisms, and open communication channels.
Leverage the right artificial intelligence (AI) – AI can help companies analyze vast amounts of customer data and identify patterns and trends that can inform personalization strategies. Companies can use the right AI for the right job do better.
- For example, firms using Bayesian models to deliver personalized next-best-action recommendations tailored to each individual customer (that adapt in real-time as preferences shift) report up to 6x lift in response rates. [vi]
- They also enjoy an added advantage that these models are transparent and can be pre-checked for bias, responsibly deployed, and explained. Compare that to this statement in a recent research paper on using GPT: “We do not intend for the model to be used for harmful purposes but realize the risks and hope that further work is aimed at combating abuse of generative models.” [vii]
- Use other responsible techniques, such as federated learning and homomorphic encryption, which enable machine learning models to be trained on user data without accessing or exposing individual user data.
Use anonymization and pseudonymization techniques – These are methods of data de-identification that can be used to ensure that sensitive personal information is protected while still allowing for effective analysis to improve personalization. Anonymization removes all identifying information from a dataset, while pseudonymization replaces identifying information with a pseudonym, allowing for the data to be re-identified if necessary. If data is shared externally with other parties, use clean rooms.
Consider differential privacy algorithms – Differential privacy is a technique that adds noise to a dataset to protect individual privacy, while still allowing for effective data analysis and personalization. Differential privacy algorithms can be used to provide personalized recommendations, while still ensuring that individual user data remains private.
Employ secure data storage and transfer protocols – Companies must ensure that user data is stored and transferred securely, to prevent unauthorized access or data breaches. Technologies such as encryption, secure sockets layer (SSL), and transport layer security (TLS) should always be used secure data storage and transfer.

Conclusion

Being customer-centric is about adopting a mindset that improving customer experience is paramount to business success. Personalization is an essential strategy for businesses to improve the customer experience. However, as personalization becomes more prevalent, consumers are also becoming more concerned about their privacy.

As the debate between personalized products and services and data privacy rages on, companies must navigate a delicate balance between meeting consumer demands for customization and respecting their privacy. Failure to do both right could have profound consequences, including loss of trust and customer loyalty, as well as legal and regulatory penalties. However, those companies that can offer personalized products and services while also prioritizing transparency and data privacy will be well-positioned to succeed in the digital age.

The future belongs to those companies that can harness the power of data-driven personalization in a responsible and transparent way, while respecting the privacy and autonomy of their customers. In short, the choice is clear: companies can either embrace data privacy as a core value and use it to build lasting relationships with their customers, or risk being left behind in an increasingly competitive market.

[i] Capco. (2021). Insights for Investments to Modernize Digital Banking. https://www.capco.com/Intelligence/Capco-Intelligence/Insights%20for%20Investments%20to%20Modernize%20Digital%20Banking

[ii] Epsilon. (2018). The power of me: The impact of personalization on marketing performance. https://www.epsilon.com/-/media/files/epsilon/whitepapers/emea/the-power-of-me.pdf

[iii] Pew Research Center. (2019). Americans and privacy: Concerned, confused, and feeling lack of control over their personal information. https://www.pewresearch.org/internet/2019/11/15/americans-and-privacy-concerned-confused-and-feeling-lack-of-control-over-their-personal-information/

[iv] International Journal of Human-Computer Interaction. (2020). Online Privacy Breaches, Offline Consequences: Construction and Validation of the Concerns with the Protection of Informational Privacy Scale. https://www.tandfonline.com/doi/full/10.1080/10447318.2020.1794626

[v] Balebako, R., Danish, R. K., Hong, J. I., & Cranor, L. F. (2015). Privacy nudges for social media: An exploratory Facebook study. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, https://dl.acm.org/doi/abs/10.1145/2487788.2488038

[vi] Pegasystems. (2022). Coutts: Delivering world-class banking experiences at scale. https://www.pega.com/customers/coutts-customer-decision-hub

[vii] Semantic Scholar. (2023). Structure and Content-Guided Video Synthesis with Diffusion Models. https://www.semanticscholar.org/paper/Structure-and-Content-Guided-Video-Synthesis-with-Esser-Chiu/07be0ec1f45e21a1032616535d0290ee6bfe0f6b