It’s a common experience—you must tell a customer service representative your account number moments after you inputted it into the IVR system. You have to explain to a contact center agent about the failed website self-service experience that prompted your call. You respond to a direct mail or SMS promotion, only to find a clueless representative on the other end of the line.
Every day, customers share streams of information about themselves in their omnichannel interactions. They rarely use just one channel to complete an interaction, and many end up in the contact center. Fifty-seven percent of inbound calls to the contact center come from customers who first attempted to resolve an issue on a company’s website, while 30 percent of callers are still on the company’s website when they speak to an associate, according to the Corporate Executive Board.
Yet few companies integrate that information to create a superior customer experience. Even those with “multichannel” operations rarely connect customer data and follow the customer path across channels. Customer experience breakdowns are commonplace as customers move from one channel to the next. It can be extremely frustrating for customers to have to repeat the nature of a support problem with a contact center associate. Or when it’s clear to a customer that the associate doesn’t know much about her or the channels she most recently visited in an attempt to solve a problem. This may help explain, in part, why 62 percent of customers have switched brands in the past year due to poor customer service, according to Accenture.
Instead of bringing the conversation back to square one and aggravating the customer, contact center associates can use the customer data being generated across various touchpoints to deliver prompt, personalized, and relevant support. Voice, mobile, web, social, chat, email and other channel activity can be combined with transactional, sentiment, demographic, and other data to arm contact center agents with appropriate information. In addition, CRM data can add insight about which products a customer currently has, how valuable a particular customer is, the stage of the lifecycle a customer is in, etc. This data allows organizational leaders and customer-facing employees to deliver interactions that customers expect. It’s a necessary evolution for the contact center to transform from a cost center to a superior customer experience creator. And it has real impact on the success of the business (see Figure 1).
What does it take to get to this advanced state of omnichannel evolution? A good starting point is to pick a particular area of support (e.g., chat) and run a pilot to determine what common channels feed into this area, as well as how processes, data integration, and support can be improved to generate better customer experiences overall.
Let’s use a hypothetical example from a consumer bank: Analysis of customer sentiment and feedback from a retail bank reveals that a higher-than-normal share of customers is dissatisfied with customer support between the hours of 5 p.m. and 9 p.m. on weeknights. A deeper dive shows that a large percentage of these customers use SMS texts to try to obtain information about their balance during these hours. However, contact center associates working in the SMS channel don’t have access to account information and are unable to help them. Organizational leaders can act on these insights and take steps to ensure that associates are provided access to customer account information on a 24/7 basis. After implementing these changes, customer satisfaction rates and NPS scores for this time period rose over the next several months. Taking these actions to improve the customer experience will also likely reduce call volumes to the contact center.
Contact center associates can also interact with customers and recognize the customer’s interaction journey across other channels (e.g., “I see that you were attempting find additional information about your account on our website. How may I assist you?”). Simple acknowledgement like this will go a long way in showing customers that you value their time and understand their issues.
Evolving the use of data
Of course, data is critical for these advancements in service quality to occur. There are numerous ways that organizations can use customer data to gain deeper insights into customer behaviors and customer sentiment to drive improved outcomes.
Predictive analytics help determine the reasons why people use certain channels. Executives can act on these insights to craft the best intra- and inter-channel experiences. Customer data and predictive analytics can also enable customer experience leaders to identify the aspects of a product that customers need support for. Our research finds that 20 percent of all calls made by customers occur in the first month after purchasing a product or service. Associates should be provided with insights on the type of support these customers are likely to reach out for. Armed with these insights, associates can be prepared to address customer inquiries immediately. Having this knowledge can help contact centers reduce the number of repeat calls on a particular issue while improving NPS.
When associates can deliver these types of experiences based on a customer’s entire channel usage, it demonstrates to the customer that the company knows who they are and is able to provide them with intelligent support to address his needs and preferences. And this level of advanced knowledge and relevant support can help to strengthen trust and loyalty and increase customer lifetime value.