Boosting Customer Satisfaction Through Predictive Service

At Oracle, we think all the time about the customer experience, how data and our connected world are changing customer expectations and enabling businesses to meet and even exceed those expectations.

One of the most important success factors in this changing customer experience is customer service. You can have the best products, the best sales and marketing, the best price, but if you don't have the customer service to match, you will never create the long-term, profitable relationships that build success.

Our expectations are shaped by the smart devices and constant connections we all have. We expect to have information at our fingertips, whenever and wherever we are ready to buy. We have the same expectations when it comes to service: right away, right the first time, whenever we need it, wherever we are, and through whatever channel we choose. Furthermore, people shopping for business products and services expect the same type of easy and satisfying experience to which they've grown accustomed in their personal lives.

This shift has become even more important in a world where purchasing is shifting from cap-ex to op-ex and switching vendors is easy. Customer service is an outsized factor in your reputation and your ability to win and keep customers.

But customer service, especially field service, can be a really big expense for your business. So how can you balance this cost against the need to exceed growing expectations around service? The answer lies in predictive service.

IoT: Smart Devices = Predictive Insights

One huge development that is changing customer expectations is the Internet of Things (IoT). More of the things we use every day are equipped with sensors, internal intelligence, and a communications link to the internet. At home, almost anything that draws power is becoming part of the IoT: Thermostats, televisions, washing machines, refrigerators, EV chargers, security cameras, even individual light bulbs can be connected today.

The same thing is happening in the enterprise. A lot of what customers buy for their businesses today are linked into the ever-expanding IoT. From a single laser printer to vehicle fleet to all the machinery and robots on a factory floor, IoT devices can monitor their status, report errors, and are always searching for and installing updates.

Whether in your home or your business, IoT-connected devices generate an enormous amount of data all the time. Until recently, though, that data has been extremely underutilized when it comes to improving customer service.

That's the idea behind predictive service. IoT allows you to gather data from IoT-connected devices you sell and pull it all together into big data that can be analyzed using machine intelligence. By applying advanced AI techniques to all that data, you can predict when a device is about to fail, when it will need to be repaired, or when it should be replaced. Instead of the customer picking up the phone to call you when a product fails, you can reach out to the customer to solve the problem before it happens.

Think about how that changes the customer service model. With AI and machine learning enabling you to be proactive, we can completely rethink what customer service means. Predictive service has the potential to transform service into a driver of increased customer satisfaction while helping your businesses improve the entire field service process, optimize service resources, and dramatically reduce the cost of service. It can be the foundation for new business models built around service as well.

Connecting the Service Team

Field service can be a major expense for companies. Physically sending technicians, equipment, and inventory into the field requires extensive overhead. As a result, mistakes resulting from misalignment of skills, parts, and materials can be costly and frustrating for customers.

Predictive service dramatically improves field operations by allowing organizations to better understand what is required to complete a service job. This allows service organizations to send the right technician with the right skill, parts, and equipment to complete a job the first time. In fact, AI lets you create entirely new processes for your service teams, helping manage resources far more efficiently. You will also get better visibility into the supply chain and logistics, as well as being able to match the right team skills to the right problems.

Predictive service applies even if your customer service contacts begin by engaging customers via chat bots or live agents on the phone. Again, by applying advanced analytics across all the available data you have on each customer, you can develop a deeper understanding of how best to approach each customer when they are having a problem.

You can use the insights to structure the responses of the chatbot and present a dashboard to a live agent with insights that can guide them more efficiently to a successful resolution. As technology advances, you can imagine a time in the near future where analyzing customers' tone of voice can reveal their mood and offer your team insight on the best way to respond.

In a world of heightened customer expectations and changing purchasing habits, predictive service is an imperative. Data from IoT-connected devices, from your customer interactions, and from social media, along with machine learning and AI, are the essential tools for anticipating customers' service needs before they escalate. Companies that focus on this aspect of the customer experience will find it delivers tremendous value to their businesses, customers, and reputations.

Rob Tarkoff is executive vice president and general manager of Oracle CX Cloud and Oracle Data Cloud. Prior to joining Oracle in September 2018, he was CEO and president at Lithium Technologies. Before that, he held leadership positions at Adobe Systems, EMC, Documentum, CommerceOne, Advent Software, Onyx Software, and Borland Software.