Sam Ngo, director of product marketing at customer data platform BlueConic, says there has been a shift in consumer expectations when it comes to personalization. “The every-day consumer might not know exactly how their data is collected, but they know it’s happening and have some expectation for how it will be used,” she said.
Some of the benefits of personalization include emails with accurate recommendations that mesh with your interests. “Most people appreciate this level of personalization, as long as companies are fully transparent about how their data is being used and it creates a continuous value exchange between brand and consumer,” Ngo said.
BluConic is a sponsor of CMSWire's summer Digital Experience Summit, taking place as an online event on July 29. Sam Ngo is hosting the breakout session, “Beyond the Cookie: Personalization for 2022.” Ngo spoke with CMSWire about balancing personalization efforts to benefit both consumers and companies.
Striking the Balance Between Personalization and Data Privacy
CMSWire: How much personalization do consumers want in their experiences with a brand? Is there a limit?
Sam Ngo: If personalization is helping a customer achieve a goal, that’s great. Companies should strive to deliver great personalized experiences, but not at the expense of privacy and transparency. If companies can provide value to customers from using the data in meaningful ways and improving overall UX, that can go a long way.
For example, you may log into a news site to see personalized content or sign up for a loyalty program so you get free shipping and returns. I think we’ve gone beyond personalization being “including your name in an email” to providing the right experience dependent on who you are, what your preferences are and where you are in a customer lifecycle.
CMSWire: How do you balance a user’s desire for personalization with their preference for some amount of data privacy?
Ngo: It’s less about personalization for personalization's sake and more about driving value for the customer. First-party data is foundational to personalization, and we’re seeing more companies invest in cross-channel lifecycle personalization strategies. But rather than gathering this data just because they think they need it, companies need to be transparent in what they are collecting and what they are using it for.
The Evolution of Digital Experience and the Role of AI
CMSWire: How do you see digital experiences evolving in light of the pandemic?
Ngo: Two trends come to mind: omnichannel acceleration and direct-to-consumer diversification. When you think of all the technology that’s needed to get these kinds of growth initiatives up and running, it’s mind-blowing. During the pandemic, retailers, grocery stores, restaurants and many other companies were able to set up curbside pickup in a matter of weeks and enable customers to use a mobile app to alert staff when they arrived.
But the larger trend that’s really happening here is this blending of online and offline experiences. When you’re picking up curbside, it becomes part of the digital experience because you’re using the app at the same time that you’re physically there. There’s now blurred lines — buying online isn’t just buying at home. It’s truly an omnichannel experience that companies are now creating.
CMSWire: What advancements or trends in omnichannel are you especially excited about? Why?
Ngo: A lot of the innovations that came out of the pandemic aren’t just convenient for customers, but they also offer companies opportunities to collect new kinds of data. For example, curbside pickup gives companies opportunities to understand things like how long it took a person to get there and how long after they ordered did they actually arrive to pick it up. This type of data can change the entire supply chain and how companies better communicate with customers in the moment.
QR codes are another example of a trend that accelerated during the pandemic. They’ve been around for a long time, but they’ve hit their heyday in a number of ways. Many restaurants now have QR codes on their menu so customers can order at the table and pay the check through the app. It’s another example of the blurring lines between online and offline experiences.
CMSWire: How do you see AI influencing the user experience?
Ngo: AI and machine learning play an important role in understanding a customer and being able to present them with relevant offers and products in real time. Over the last few decades, marketing and ad technologies have incorporated machine learning models in their platforms to drive things like product or content recommendations, next-best action, probabilistic identity matching and more.
What’s trending now is a creation of more and different kinds of data — whether it’s [from] virtual assistants like chatbots or digital assistants [like] wearable devices. In aggregate, this data can be used to better understand segments of customers to design better experiences.
CMSWire: Some of the constructive criticism regarding the role of AI making decisions for a business is the fact that in many cases, training data is limited and does not appropriately account for underrepresented groups of people. How can businesses use AI ethically and efficiently in their DX strategy? Where are the opportunities and where can they be more thoughtful?
Ngo: Being aware that algorithms and humans have biases is a great first step. Understanding where the data comes from and how it’s being used to train a machine learning model is so important to prevent or rectify unintended consequences from biases. There’s been some interesting work around codifying 'fairness' into machine learning models to account for biases that already exist in a system.
On the other hand, it’s important that we continually examine the output of modeling and algorithms to notice patterns stemming from bias that the model doesn’t recognize. For example, a technology company discontinued development of a hiring algorithm based on analyzing previous decisions after discovering that the algorithm penalized applicants from women’s colleges. When it comes to using machine learning to drive experiences and digital strategy, it’s important to look at the entire customer lifecycle and understand if all segments of customers are being treated fairly.
CMSWire: Considering the steps of your career and the positions you’ve held leading up to BlueConic, what lessons have you learned about the digital experience from working at these various companies?
Ngo: I’ve learned that being customer-first really requires having the right technology in place to make different systems work the way they are supposed to. A real-time capability in whatever platform you’re using is meaningless if you don’t know who you are targeting from a customer identity perspective and if you don’t have access to unified, persistent data that you can actually use.
Companies have been focusing [so much] on optimizing for channels, but now omnichannel is really bringing to bear that the customer needs to be at the center. As an organization, that means having the right technology and the right processes in place. If you don’t have the technology that enables you to keep your customer data in one place and actually use it for activation, then you’re not going to be able to deliver anything in real time. Technology that enables these kinds of efficiencies is what’s making real time an actual reality.
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