As we shared in our first post on digital-first service, businesses today compete on customer experiences. It’s what differentiates them from their competitors, and these days, long-term survival depends on being able to stand out from the crowd.
But moving away from the traditional customer service strategy—one that’s static, reactive, and focused on efficiency rather than the customer—to a new digital-first approach that offers memorable, standout experiences requires a shift to a new set of priorities.
Digital-first service is built on three tenets: offering predictive, unique, and hyper-convenient service experiences. In this blog series, we’ll take a closer look at each of these principles and how to apply them to create the service experiences customers have come to expect.
Now let’s dive into the power of predictive customer service.
To put it plainly, predictive service allows a company to take the initiative when solving customer problems.
Customers get frustrated when they must initiate contact with a service team for help, especially when their problem was caused by the company. Rather than simply responding reactively, service teams should be reaching out to customers proactively or in the moment to create quicker resolutions and eliminate frustrating customer experiences.
Whether this means appearing at the right time and place on the website or sending a text when something may not meet a customer’s expectations, the end goal is making your customers feel appreciated and satisfied by a service team that understands them and can easily resolve their concerns.
With that being said, achieving effective predictive service requires a lot of data from many different places, including browsing data, event data, asset data, transactional data, profile data, and more. And in order to act on this data, service teams need to be able to access it in a system that creates a unified customer profile, tracks their relationship and interactions with the business, and assesses relevant data to determine how and when they will need your help.
This isn’t easy. Collecting and consolidating a variety of data points into actionable insights is a challenge. Luckily, this is exactly where Oracle’s strengths lie.
We’ve established that predictive service can take multiple forms—from a properly placed pop-up to sending a text when something unexpected happens. But how can an Oracle customer do this?
Let's start with an analogy. Imagine a customer is wandering aimlessly through a store. An employee notices they may need help and remembers helping the same customer with a purchase during a previous visit. The employee greets them. “Welcome back! Do you have any questions about the item you bought, or are you looking for something new?” From there, the store employee can address their questions on anything from additional product information to issues with a recent purchase to how to make a return.
Now apply this analogy to a digital experience. A customer is unhappy with a recent purchase. They visit the company’s website and begin browsing knowledgebase articles on the item they just bought. After lingering on one article for a while, a chat invitation appears with a specific greeting. “Hi! It seems you may have a question about a product you recently purchased. Would you like to talk with a digital assistant?” As the customer responds, Oracle Digital Assistant can then provide helpful knowledge articles, pull relevant customer information to provide contextual advice, and more. Sounds very similar to the in-store experience, doesn’t it?
By drawing on customer data, such as browsing history, transactional data, and recent customer service interactions, the system is able to trigger a relevant, predictive service engagement. The digital assistant acts very much like the in-store employee, offering personalized, proactive assistance to resolve the customer’s issue, thanks to the context a unified system can provide.
In-store employees serve as both sales reps and service providers. They connect with customers to understand their needs and set to work meeting—and ideally exceeding—them. In the digital realm, an automated platform like we’ve discussed can easily be configured and leveraged to serve customers in the same way, facilitating a variety of sales and service functions to offer the stellar experiences customers crave and set your service organization up for success.
We’ve only scratched the surface of the many applications of predictive service. And while it may look different across industries and from B2B vs. B2C, the essence of “predictive service” remains the same. It’s essential for digital-first service and creates opportunities for teams to elevate the standard of customer service they provide.
Learn more about how Oracle Digital Customer Service can help you deliver innovative support experiences at the moment customers need help.
Take a quick self-guided tour to see Oracle Service in action.
Hear from innovative customer service leaders at Razer and Turning Point who are driving change with digital-first service in this video from the Oracle Virtual Summit, “Deliver Service That Meets the Moment,”
Piers Conway comes from a strong background in digital transformation. Having spent the beginning of his career at Forrester Research helping companies adopt essential businesses practices, he transitioned to work at Amazon Labs to work on a new product, the Astro. Piers joined Oracle working under Daniel Foppen, Director of Outbound Product Management, to build and manage the digital-first service strategy.