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Context-based Communications: High-tech for the optimal customer experience

Context-based Communications: High-tech for the optimal customer experience

Communication doesn’t work without context. That especially applies for customer dialog: those who don’t know their customer’s history will lack crucial information for communicating with them. How can this be optimized? With a high-performance analytics system, for one.

Do you remember your childhood, when you went shopping with your mother? A slice of sausage at the butcher, some candy at the mom-and-pop store. The sales clerks knew your favorite sausage, or just what your favorite sweets were. Expressed abstractly: Information about you was gathered from a series of – in this case – in-person contacts, to make sure you were a satisfied young customer. Customers used to visit a store once a week; these days they can choose how to get informed, buy products, or file complaints around the clock via countless touchpoints and channels. To manage and organize this flood of information, companies today need a system that merges this amount of data from various sources and makes it usable.

Intelligently integrated information

Indian Arvato subsidiary Ramyam offers precisely that with its Enliven CEM platform (CEM = Customer Experience Management). The system makes it possible for companies to merge context-based information from numerous sources, create comprehensive customer profiles, and ultimately appeal to the customer in a targeted way through their entire lifecycle. Doing so seamlessly integrates various systems and touchpoints in order to compile, measure, and optimize the customer experience.

The vision: Intelligent, learning service bots remedy customer concerns, even in difficult cases, thereby making calls to service centers by-and-large superfluous. Take a customer who, regarding a high cellphone bill, starts up a chat on the supplier website: Thanks to the processing of natural speech, the bot understands the customer’s concern, figures out the reason for the high bill – roaming fees, for example – with the help of cognitive algorithms, and suggests a customized solution for the customer. The bot also “learns” what to do in future cases during this process.

It’s also a benefit for in-person customer support that, thanks to comprehensive information, consultants can immediately get an idea of who their customer is, instead of having to click through various systems. The system’s analytics output offers a 360°-view of the customer, for example showing purchase history, past communication, payment behavior, complaints, service quality, customer segmentation or development, and social media behavior. That way, consultants know who their customer is and what offers could be interesting for them before a conversation even begins.

Comprehensive view of the customer

As an example, Vodafone’s US customer service benefits from this kind of system. The Arvato CRM Analytics solution for this customer combines, among other things, customer relationship management, billing & resource management, document management, and other systems flanked by analytics services. Customer service representatives have all of the important information immediately available and can quickly find and implement cross- and upsell options, as well as next best actions for the customer and company. This has had decisive results: The average service center call time dropped by 27 percent, the conversion rate rose by 35 percent, and customer satisfaction improved by 22 percent. Even though such a complex CEM platform might not have anything in common with the mom-and-pop store from childhood, at its core it’s still about the same thing: knowing customers well and providing individual service.

Author: Editorial team Future. Customer.
Image: iStockphoto/koo_mikko

Tags for this article Analytics (26) Chatbots (32) CRM (104) Customer Service (91) Digitization (162)

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