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Ryan McEndarfer:
Could you give us a little bit of an overview of what American Express is doing in the marketplace, when it comes to data and personalizing the customer experience?
Anthony Mavromatis:
Using data for American Express is certainly not something new. We’ve been leveraging our data for some time, and over the last couple of years have seen an acceleration in our ability to harness the breadth and depth of data available to us. Combined with technology, the ability to store data and leverage AI and ML has really raised the game in terms of what can and cannot be done. My focus is on the customer: translating and leveraging these technologies to power a more personalized experience across all the digital channels that are fast becoming the dominant way that the customers interact with us.
Ryan McEndarfer:
Could you give us a couple of examples that American Express has put into the marketplace recently, that you could point to that, “hey, we were able to enable this enhancement for the customers benefit, because of the data that we were able to leverage”?
Anthony Mavromatis:
Yeah, there’s a lot of great examples out there. At the core of what we’ve put into place is Orchestra [our in-house, machine learning powered personalization solution], which powers all channel experiences. One of the programs that I think is a real differentiator thanks to the closed loop that American Express has is Amex Offers. Working closely with our partners and merchants, large and small, we’re able to deliver a whole host of offers and benefits to our customers. [Customer can enroll in these offers in email for instance via a one click email.] That’s a great example of where the challenge is to take potentially a couple of thousand different merchant offers and get them to the right customer, at the right time, at the right place. This is also a great use case for what we just talked about, which is the harnessing of data and technologies in a way that augments the customer experience. We continue to learn rapidly and evolve our understanding of the customer’s needs, and it’s really converting what could be a very complex ecosystem into something that adds value to our customers lives and brings the merchant closer to our customers.
Ryan McEndarfer:
In terms of the merchant side of things, having that data and being able to put the correct offer in front of the correct consumer is certainly a huge benefit for marketing minded folks. Right? Because I mean, I certainly think one of the things that marketers talk about quite frequently is media waste saying, ‘hey, you know, we don’t want to have a campaign that’s essentially kind of going out to everybody’. And we spent all this energy and all these resources going out to people, when the end person that receives that offer, you know full well that they’re not going to put any time into that offer there, it’s an instant rejection from that. So instead, it’s better to have the data to say let’s make sure that personalized offer is reaching the right consumer at the right time. And to your point, it’s really because of the advancements in AI and ML that have made that possible.
Anthony Mavromatis:
I think you’re spot on. It’s a combination of rising customer expectations, but also being able to meet those expectations. How do we add value to their everyday life? Amex Offers is just one of those examples. Part of what we’re doing with Orchestra is trying to strike the right balance at the right time within the channel of what the customer’s need are at that particular moment in time. It’s also about being able to do that ideally, on a real time basis, because you have information from a historical perspective, which might give you some inclinations, but then customers are interacting with you in real-time. So you start to learn a lot and, and want to adapt rapidly into that. That’s the place that we’re at right now.
Ryan McEndarfer:
I think a part of what you’re also alluding to, is kind of the breaking down of those data silos, right? Beyond kind of the marketing and then the customer relations side of things, how else is it that American Express is really breaking down those data silos to really add value to the end customer?
Anthony Mavromatis:
It’s important to take a step back and ask what the desired outcomes and first principles are. For American Express, those principles aim to address how do you show customers you have their back? How do you delight them? How do you add value to their everyday experience? Well, guess what? If one channel is not talking to the other channel, you don’t know what just happened in the email channel that brought your customer to your website. That data silo becomes an obstacle you want to overcome.
In the case of Orchestra, as an example, building that infrastructure that is mimicking more of the customer experience, which is breaking down those data silos, so you capture the holistic customer perspective. We’re lucky to have a tremendous set of engineering partners that for the better part of the last two years have been developing that.
I think equally important in that process is making sure you don’t lose sight of what the ultimate experience and first principles of that experience are. What if a customer has a servicing need? How do you resolve it quickly? How do you resolve that maybe even in an anticipatory manner? And how do you deliver from there and further that relationship to deliver additional value that’s relevant to that particular customer? I would say, 80-90% of the effort and the keys to success are what you described, breaking down those data silos. And in many ways, the AI part is relatively, the more straightforward piece. It’s something that will keep evolving, provided you’re still focusing the experience around a core set of design principles.
Ryan McEndarfer:
I kind of want to change gears just a little bit here. Because obviously, you know, it is certainly fine to say, as a company we’re going to collect this data, and we’re going to use it in a positive manner. But there certainly are policies that are out there, such as GDPR, and the right to be forgotten, that essentially allow a customer to say, ‘hey, you know, what company, I no longer want you to have all of this data on me.’ So I’m curious to get from American Express’ side of things of what your organization is doing, in particular, to ensure that those particular customers that no longer wish to have their data collected, essentially have been removed from the system.
Anthony Mavromatis:
Obviously, from a regulatory perspective, we aim to meet the requirements. My observation having worked at American Express for over 16 years is our customers’ expectations are frankly much higher than the regulations in terms of how they expect us to use their data: protect their privacy and use it in a responsible manner. We communicate publicly in terms of what we will and will not use and how we commit to using it. But to give you the inside day-to-day piece, there isn’t one decision where we’re not stress testing our actions against customer expectations again and again. Are we meeting that? And are we reinforcing the brand?
Ryan McEndarfer:
So, shifting back to the customer experience side of things here, I’d be curious to get a forward-looking scope. Could you share with us some of the experiences that might be on the horizon that American Express is looking to bring to its customers?
Anthony Mavromatis:
Looking forward, we want to continue to get ahead of customers’ needs, in terms of what their expectations, and, there’s probably two areas that I’m personally really excited about. One of them is bringing value to customers, even before they might need it. Given that we’ve laid a lot of the foundation, we now have the opportunity to start getting ahead of customer needs, from a servicing and marketing perspective.
And then the second one is to continue optimizing the personalization experience across channels. We’re listening and learning from what our customers are telling us, whether directly or indirectly, and getting into edge cases where we’re able to deliver and enhance the experience, much more that we could in the past. How do we think about the cross-channel experiences? How do we think about a journey that might start in one channel but continues in another channel, so that we are able to delight and surprise the customer. For example, we know that you just did something online or we sent you an email and you clicked through but maybe didn’t finish. That’s part of those smaller moments I would say we’re really looking to elevate and enhance for our customers.
Ryan McEndarfer:
I would certainly say when it comes to the customer experience, the devil really is in the details and it’s certainly difficult to get it correct, right? Anthony, thank you so much for taking the time today to speak to me about data in the personalized customer experience, and I certainly hope to have you back on the podcast real soon.
Anthony Mavromatis:
Ryan, thank you for having me. It’s been a pleasure.