New Oracle Fusion Cloud Service integration drives personalized, informed, and efficient customer engagements
Oracle has updated Oracle Service to embed data from Oracle Unity Customer Data Platform (CDP) to help customer service agents gain a complete view of the customer, improve agent efficiency, and enhance service quality. Part of Oracle Fusion Cloud Customer Experience (CX), Oracle Service and Oracle Unity CDP leverage artificial intelligence to help organizations deliver more personalized, informed, and efficient customer service engagements.
Every customer interaction matters, with one in three people saying that they would never shop with a brand again after a bad experience. Yet customer service remains a frustrating and painful experience for many consumers. In fact, a CRM Essentials survey recently revealed that people would rather sit in traffic (15 percent), clean the bathroom (15 percent), wait in line at the DMV (12 percent), or argue with a significant other (8 percent) than interact with a customer service agent.
“Service agents frequently work from a patchwork of systems and rarely have the right data in front of them to solve customer problems efficiently and effectively,” said Jeff Wartgow, vice president product management, Oracle Advertising and Customer Experience (CX). “By embedding data from Oracle Unity within Oracle Service, we can give service agents real-time customer insights and recommendations within the tools they already use. This will help brands drive positive engagements by making sure their customers feel heard, helped, and appreciated.”
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The new integration between Oracle Unity and Oracle Service will enable:
- Personalized Agent Routing: Customer service agents can now be assigned to customers based on an understanding of customer history, loyalty status, and product usage. For example, customers who search for or purchase items for dogs can get directed to an agent who is passionate about dogs, or a customer interested in items for cats can get directed to an agent who is passionate about cats.
- Service-aware Marketing: Customer service agents can now easily add a customer to a targeted marketing campaign with one click. For example, if a customer expresses interest in a product or service but isn’t ready to commit to a purchase, the agent can add the customer to a follow-up marketing campaign to receive relevant offers and discounts. In addition, customer service information can be used to improve marketing programs and even suppress customers from receiving marketing messages if they are having service issues.
- Proactive Service: Customer service agents can now spend less time searching and sorting through customer information and more time focused on the customer with quick access to relevant insights. Service agents can also use data to proactively engage customers through the most appropriate and efficient channel (e.g., live chat, digital assistants, video chat). For example, with knowledge of previous customer activity, such as recently viewed pages on the website, an agent can deliver more relevant service information without having to ask questions upfront.
- Intelligent Recommendations: Customer service agents can now use a new Insights Panel on their desktop for recommendations on what a customer might be looking for or additional products they might be interested in. For example, based upon what is already known about a customer, their service agent can see they recently purchased a Macbook and can therefore recommend an Apple-compatible keyboard.
Oracle Service gives organizations the ability to predict the need for service, automate processes, and deliver tailored responses, while balancing self-service and assisted customer service models. It offers powerful and intelligent B2B, B2C, and field solutions that helps organizations give their customers the service they want, when and where they need it.
Oracle Unity provides business leaders with everything they need to manage customer data. It brings together online, offline, and third-party customer data sources and then applies built-in machine learning to prescribe the best next action within existing business processes.
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