Customers use a variety of channels for product and service support, including voice, email, chat, IVR, and social media. Customers also have little patience for ineptitude when it comes to customer service. Customers are easily frustrated if they have to repeat the nature of their query or re-identify themselves when they connect with a customer service agent. In fact, 56% of customers will stop doing business with a company after just one bad customer service experience, according to PwC.
One of the main reasons why customers suffer from disjointed customer support experiences is due to siloed data in many companies. In an ideal setting, a customer care agent should be able to access the full range of customer data during a support interaction, including information about their most recent interactions and the channels that they’ve used, their transaction history, and other pertinent information that can be used to provide a customer with the type of personalized and seamless support that can strengthen loyalty and long-term customer value. When agents have to scramble to locate this information by jumping between screens or having to place the customer on hold while they look for it, the customer suffers and the customer’s confidence in the company’s ability to support him effectively deteriorates.
Fast Data offers customer care teams a number of ways to provide customers with immediate, comprehensive, and personalized support. For instance, the use of Fast Data can enable an agent to immediately identify a customer based on customer identification data such as a mobile phone number or an email address and provide them with a personalized greeting.
Fast Data can also provide an agent with a visual representation of who the customer is and the next best action that should be taken to support them. Let’s say a high-value bank customer has called to complain about a check overdraft fee she has been assessed. Visualization and analytics capabilities that are integrated into Fast Data can prompt the agent to waive the overdraft fee after determining that such an action would likely result in higher long-term customer value.
Fast Data can also be applied to provide real-time customized support in other ways. For instance, an agent for a fashion retailer can see that a customer is viewing product information on the company’s web pages regarding cross body handbags. The agent can send a chat request offering to answer any questions the customer might have. This can lead to a highly tailored and efficient interaction to demonstrate that the company values the customer’s time and interest in its brands.
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