small fintech with a big mission: helping customers restore their credit profiles. Jim Peterson, Mercury’s CEO and a finance veteran, knew from the outset that AI was crucial for creating the personalized customer journeys that would be at the heart of Mercury’s offering. So in 2021 the company began searching for an AI-driven engine that could give every customer the right nudge at the right time through the right channel and in the right sequence.
But AI is probably only about 10% of the secret sauce. The other 90% lies in the combination of data, experimentation, and talent that constantly activate and inform the intelligence behind the system. The technology is merely the tool for reaching it. In this article we’ll present what it means to integrate AI tools and what it takes to continually experiment, constantly generate learning, and import fresh data to improve and refine customer journeys.
None of this is meant to suggest that implementing an AI-based customer journey is easy. And three common shortcomings can make it especially challenging, even when you have the right AI solution.These can occur when a preponderance of the data is unstructured, as in health care, or unrecorded, as in the hospitality industry. No one inputs feedback from the cards left for guests in hotel rooms, which may contain immediately valuable and addressable information.
A company needs “receptors” to capture information about a customer’s every interaction across every channel, and that information must be remarkably granular.
Data from third-party sources, such as weather, power outages, demographic and psychographic data, and general health data about a zip code population, provides further context. The broader and more granular the information, the richer the models can be. That richness fuels your performance edge.
Pointillist, Comcast’s AI decision tool, does double duty. First it matches a customer’s data from across all the company’s systems—its app interactions, the call center, product use logs, and so forth—and creates an integrated view of the customer. Then, operating like middleware, it knits together multiple databases into one integrated database, precluding the need to create yet another, formal database.
When a company sends a test email, it must be able to monitor any variable that could possibly affect the customer’s response.