Balancing personalization with privacy in the age of AI

As customer experience (CX) leaders, we’re always looking to make our customers’ interactions with our brands more personal – and with good reason. Study after study shows that customers spend more money and have a better brand perception when they feel like more than just a number or transaction.

Personalizing an experience while the customer is in your place of business is relatively straightforward. But now more customer experiences take place digitally, which means we need to create personalized experiences online. Many businesses are really good at this type of personalization, serving up relevant offers based on information they know about the customer. And with generative AI, they’re now able to do this even faster, at scale, and across more channels.

Unfortunately, all of this personalization can come at the cost of data privacy and customer trust. In this article, we’ll explore the benefits of personalization in CX, how we enable high levels of personalization, and how we can achieve personalization while prioritizing customer privacy.

The Benefits of Personalization in Digital Experiences

A quick Google search uncovers plenty of compelling reasons to personalize your CX. For example:

• 66% of first-time buyers say tailored messaging influences their purchase intent.
• 78% of consumers say personalized experiences made them more likely to repurchase.
• 84% of customers say being treated like a person, not a number, is very crucial to winning their wallet.

As the Global Analytics Lead at TTEC Digital, I’ve personally worked with many clients to leverage their data to create more compelling and personalized experiences. I’ve also seen the payoff from those personalized interactions. One great example is our work with Chipotle.

Chipotle wanted to increase their brand loyalty and they knew that to do that, they needed to create more personalized experiences for their customers. Working with our partner, Microsoft, TTEC Digital automated customer data collection from a wide range of sources and unified that data into actionable customer profiles. The results were impressive – a projected $280 million in annual sales revenue growth as a result of activating as much as 34% in newly uncovered customers and cross-sell opportunities.

You can read more about our work with Chipotle here.

How Is CX Personalization Possible? Data.

As the Chipotle example illustrates, personalization is made possible with data and analytics. By using current and historical data, we can analyze patterns to predict future behaviors or trends. We can forecast which products a customer is likely to buy, the channels in which they want to communicate, their sensitivity to discounts and much, much more. With that information, we can then curate more relevant and personal offers and experiences.

Using data and analytics to personalize the customer experience isn’t new. Even AI-enabled analytics isn’t new. For many years, TTEC Digital has been using machine learning, deep learning, and other AI capabilities to calculate and deliver recommendations for next best actions, products, services, and more. What is new is generative AI and large language models (LLMs). These innovations are allowing us faster, more accurate, more actionable predictions. The key is ensuring that we’re collecting and using the data that powers these models responsibly. The risk is that if we don’t, we could lose a customer forever.

For more on responsible AI, check out this article from my colleague, Aaron Schroeder.

Best Practices for Personalization that Respects Privacy

As customers, we expect the companies we do business with to have data and to use it to create better customer experiences. A 2022 Gartner survey found 71% of B2C and 86% of B2B customers expect companies to be well informed about their personal information. At the same time, we expect companies to treat our personal data responsibly. A 2022 Cisco survey found that 76% of respondents said they would not buy from a company that they do not trust with their data.

So how do we meet our customers’ desires for personalization and their expectations for responsible data collection and use? Here are four steps I believe companies can take to hit the sweet spot between personalization and data privacy:

1. Only collect data that’s necessary to creating a better customer experience. Just because the data is available, doesn’t mean you need it. Start with the experience or goal you want to achieve and then define the data necessary to create it.
2. Let your customers customize their experience. If possible, give your customers control over how they experience your brand by allowing them to pick how much personalization they want and how much data they’re willing to share.
3. Be transparent. Tell customers in plain language how you plan to collect and use their data. Often, if a customer understands that the data will be used to make their experience better they’re more likely to share that data willingly.
4. Put the customer first. Think about how your data collection and use will benefit the customer – not just your bottom line. If you can’t make a case for how certain data will help the customer, then you probably shouldn’t be collecting that data.

Just about every business should take steps to personalize their customer experience – both for the benefit of the business and for the benefit of the customer. The key is to make sure that personalization always respects the customer and their data.