Customers use a variety of channels to interact with companies today, including voice, web, chat, mobile, social, desktop video, etc. Not only do customers use different channels to satisfy specific needs, they also move from one channel to the next to do so.
For instance, a customer may research a product online and then enter into a click-to-chat discussion with an agent to get answers to his questions.
When the customer does this, he expects to move fluidly from one channel to the next. But he also expects the contact center agent to know the nature of the issue he was trying to resolve online.
If the customer has to repeat information during a live interaction with an agent, he can become frustrated and dissatisfied and decide to take his business elsewhere.
Customers “are not necessarily coming to a single touch point with the intent, or attention span, to complete their goal in a single sitting,” says Forrester Research analyst Ron Rogowski in an article on the topic for Retail TouchPoints. “That is why you see this cross-device behavior with many customers.”
Rogowski points to a Google study that finds that 81% of consumers use their smartphones to look up product information while they’re watching a television commercial about that product.
Customer data and analytics can be used in a number of ways to help customer service agents, contact center supervisors, marketers, and other executives better understand the cross-channel customer journey and use these insights to enhance the customer experience, as well as improve loyalty and business performance.
For example, because of the wealth of data that customers leave as a result of their cross-channel interactions, channel owners and other decision makers can glean insights to identify obstacles that customers may face as they attempt to shift from one channel (e.g., IVR) to another (live agent support).
Business leaders can then use this information to design better process flows for customers by creating or revising customer journey maps. Meanwhile, marketers can use behavioral data from customer interactions in different channels for other purposes.
This includes understanding the channels that customers use for different activities (e.g., company website or online forums to view ratings and product evaluations from other customers) that can be used to determine the type of content that’s most likely to resonate with prospects and increase the likelihood of conversion.
For example, blending big data analytics with behavioral data can inform marketers whether customers are abandoning websites or electing instead to chat with agents at certain stages if that option is available.
A deeper evaluation of customer data can further help marketers determine the root cause for a customer to leave a web page, such as a lack of information about a product that may be preventing him from taking the next step in his journey.