How banks have stopped thinking in products and started thinking in customer journeys
- As banks weave AI into their customer experiences, many are looking for ways to translate years of customer data into a more complete picture of each customer's needs and context.
- The difference isn't the data itself, but how well a bank makes sense of a customer's context and goals and builds the right response around that.
One of the largest U.S. consumer financial services companies, Synchrony, with more than $120 billion in assets, faced a problem that had little to do with the amount of customer data it had and everything to do with what it could do with it.
The company had spent decades building relationships through private-label credit cards, co-branded cards, installment financing, healthcare financing, and savings products. Every application, purchase, and payment added another data point to a customer profile. Yet when customers arrived on Synchrony’s digital channels, much of that knowledge remained disconnected from the experience they were having.
A prospective customer exploring healthcare financing wasn’t necessarily looking for another credit product. The challenge wasn’t understanding who Synchrony’s customers were. It was recognizing what they needed in that moment and translating years of customer data into an experience that reflected their immediate goals.
Since 2020, Synchrony has worked with Dynamic Yield to tackle the problem. At the time, Dynamic Yield was an independent personalization and decisioning platform owned by McDonald’s that helped banks, merchants, and brands use customer data and behavioral signals to personalize digital journeys and optimize customer decisions.
Mastercard acquired Dynamic Yield in 2022 after announcing the acquisition in late 2021. The company saw that the future of payments wasn’t just about processing transactions, but about helping institutions understand customer intent before a payment, delivering the right experience during it, and building a more relevant relationship long after the transaction is complete. Dynamic Yield gave Mastercard a way to advance that broader vision as industry priorities evolved.
Together with Dynamic Yield, Synchrony began combining its customer data with real-time behavioral signals and continuous experimentation to tailor experiences around customer intent.
Six years later, the tech matters less than the problem it was built to solve. As banks layer AI into their customer experiences, many are grappling with the same challenge Synchrony set out to solve: how to turn years of customer data into a deeper understanding of each customer’s context.
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