Big Data, Big Value, Big Leap Forward for Customer Experience
In the 2002 neo-noir thriller Minority Report, technology has as big a role as the film’s star, Tom Cruise. In one scene, as Cruise’s character cruises through a retail store, a series of holographic clerks greet him by name, recount his recent visits to their department and offer personally relevant products, which also take into account his disheveled appearance.
Image courtesy of 20th Century Fox / DreamWorks Pictures.
The technology designs in the film have proven prescient. The kind of real-time, big data analytics required to accomplish this is no longer just imagined, it’s happening now.
The hard part is taking the first step. So what you need is a very actionable, two- or three-stage strategy, which can help you start operationalizing customer response excellence. You need quick hits, so those phases are self-funding. And you want each action you take to pave the way toward analytically driven, big data-fueled interactions. It’s not science fiction – just hard work, creativity and a strong customer focus.
Managing the context surrounding customer response is proving to be a viable first step to enable communicating with customers based on insights into their true needs. This requires instant access, filtering and preprocessing of the right contextual data.
Contact center agents often lack full access to customer data across the organization. Putting a ubiquitous context management capability in place can enable the optimal customer experience across media types while providing your customer response specialists with the context that they need to work more effectively, collaborate with leaders and subject matter experts, and personalize the interaction.
Inference is another angle on operationalizing customer response excellence. Context, big data and analytics are all essential to these efforts. For example, a huge advancement in contact center efficiency is the ability to separate out which customer conversations, in whole or in part, are issues-based interactions versus relationship-based interactions.
By applying context management and “next-best-step” analytics to customer conversation threads, these transactional types of interactions can be shifted to the most effective and appropriate interaction channel.
Tools such as speech analytics can help quickly detect repeated issues-based conversations, so you can figure out why they are happening and come up with an effective strategy to either prevent them or deal with them through automation.
An important side benefit of all this is improving the experience of contact center agent and other specialists involved in customer response. Issues-based interactions wear down agents. Meaningful, relationship-building interactions are uplifting. Uplifting experiences lead to lower employee turnover and big savings. They also help build intellectual capital, which can be monetized, as well.
Each of these actionable steps can have a profound impact on the most basic and essential goals of customer response: First-contact resolution, reducing customer effort and strengthening lasting and loyal relations with your prized customers.
Having addressed issues-based interactions, you can focus on relationship-based interactions, which is where the real value will be. Think about a mash-up of real-time analytics and real-time customer interactions.
Whether online, mobile, SMS, chat, video or voice, you’ll soon be able to use real-time analytics to inform any customer interaction through current intent and recent or past interactions going on around the customer. Finally, companies will be able to monetize their customer and related data by using it to interactively inform and enhance the customer journey.
If you would like to learn more about how you can maximize your Customer Experience Management efforts with every customer, I’d suggest the Avaya CEM Guidebook.