Jean Ortiz Perez, Head of Data and Analytics at Collinson Group’s Valuedynamx, outlines why companies must balance privacy and personalization to drive optimum outcomes with their customer loyalty programs
Companies have been using loyalty programs to improve customer experiences and encourage repeat business for hundreds of years. But it was the dawn of ecommerce that revolutionized this practice and made data-driven loyalty programs accessible to businesses of all sizes.
As a business unit of consumer intelligence specialist Collinson Group focused on the convergence of payments, commerce and loyalty programs, Valuedynamx is on the cutting edge of the latest trends shaping customer loyalty best practices.
According to Jean Ortiz Perez, Valuedynamx’s Head of Data and Analytics, there are two competing forces that will determine the future of these programs.
“For consumers, it is a trade-off between personalization and privacy,” she says. “But when personalization and recommendation engines become customer-centric, you will see greater engagement.”
“We’re seeing that people are more than willing to exchange more data for better rewards”Jean Ortiz Perez, Head of Data and Analytics, Valuedynamx
In this interview ahead of Corinium’s upcoming CDAO UK 2022 conference, Perez shares her views on how companies can provide value to their customers, while being mindful of how comfortable consumers are with exchanging their data for personalized services.
“In the US, for instance, we’re seeing that people are more than willing to exchange more data for better rewards,” she notes. “We’re working on a program where a customer can share what sort of products they regularly buy through our retail partner. Right now, we can only see how much the person spent and then they get a general discount. We’d like to be able to offer them discounts specifically on what they buy.”
Customer-Facing AI Must be Explainable
AI-powered recommendation engines are playing a key role in helping companies including Valuedynmx build a world where customers receive personalized discounts based on what they buy.
This is one area where it’s particularly important for companies to be mindful of the rights and expectations of their customers. That means ensuring AI models source data ethically and treat customers fairly, and that companies can explain how models arrive at specific decisions that impact their customers.
Perez says: “The challenge with AI is making your models explainable. It’s a big challenge with AI in general right now.”
“The challenge with AI is making your models explainable. It’s a big challenge with AI in general right now”Jean Ortiz Perez, Head of Data and Analytics, Valuedynamx
“It’s not that it’s impossible to explain how the algorithm arrived at a certain conclusion,” she continues. “You just need to ensure you’ve taken everything step-by-step throughout the process.
“You should be comfortable that the right decisions were made, and the right technology used, so you can explain at least most of the conclusions. The last thing you need is a customer coming and asking, ‘Why are you selling me this camera for $100 when my wife’s getting it for $89?’ We should be able to dissect that.”
The beauty of loyalty programs is that customers opt-in to share their data in exchange for deals on products or services. In a world that’s moving away from cookies and techniques such as retargeting, this is a key benefit of building CX initiatives around loyalty programs.
But as enterprises build AI into the engines driving initiatives like these, they must ensure they have processes in place to combat AI model bias and ensure that the technologies they’re using for customer-facing initiatives have explainable outputs.
What’s Next for Valuedynamx’s Data Strategy
Since Collinson launched Valuedynamx in March 2020, Perez has been focused on ensuring her fledgling unit has the right mix of funding, skills and technology to execute its data strategy.
Moving into 2022, she says her focus areas span everything from ingesting data more efficiently to upgrading the company’s analytics self-service capabilities and making it easier for non-technical staff to find the insights they need to make better decisions.
“We have very ambitious plans for the 2022 in terms of data engineering,” Perez says. “We’re looking at a major scale-up so we’re organizing data better, decreasing our processing times and enabling real-time analytics.”
“The core of our business is innovation, constantly pushing boundaries and finding what is beneficial for consumers and our clients”Jean Ortiz Perez, Head of Data and Analytics, Valuedynamx
“In terms of data science, we’ve got key algorithms and solutions coming out and next year, which are around a campaign engine and optimization for our products,” she adds. “And in terms of insight reporting, the focus is on self-service.”
“The key element there is enabling people who don’t have any coding background so that they can just do ‘drag and drop’ and effectively self-serve [insights],” she continues.
As she advances these initiatives, Perez says she’ll always be keeping the need for Valuedynmx need to adapt to the changing privacy landscape ‘top of mind’.
But even with consumers waking up to the importance of protecting their own data and lawmakers across the globe passing laws to strengthen consumer data privacy protections, Perez argues that personalization with continue to play a key role in CX initiatives in 2022 and beyond.
“Clients have realized that they also need to invest in the technology to improve CX,” she concludes. “The best way to do that is to make personalized services, such as loyalty programs, truly valuable for consumers and keeping in mind that what’s valuable to one person might not be valuable to the another.”