A first- (or faster-) time-to-market has been a longtime mantra of most companies. Be it first with a new product or first with new capabilities to an existing product category, speed can help companies capture and maintain a customer base enthralled with owning the latest and greatest.
Companies have also realized that the old manufacturing processes left too much up to chance. Ordering too many raw materials and assembling too many products without matching the market need resulted in waste and loss. Lean manufacturing was born in response.
In the internet age, these notions of fast time-to-market and the challenges of matching production to delivery still exist, though in a different manner. Enter the concept of DevOps, “a set of software development practices that combines software development (Dev) and information technology operations (Ops) to shorten the systems development life cycle while delivering features, fixes, and updates frequently in close alignment with business objectives.” Very similar to agile software development, the DevOps approach is now over a decade old and is used by services companies as they deliver new products and functionality well as by many companies internally to constantly evolve the systems running their business.
What does all this have to do with customer service? In the age of the customer, it’s more important than ever to rapidly respond to the changing needs of customers with respect to customer service and their overall experience. It’s time to take a CustOps approach to customer service.
Driven by data
It goes without saying that every customer call, email, chat–every encounter, across every channel–provides valuable data. What is the issue the customer is experiencing? Is an issue becoming a trend? How was the problem solved? That data drives insight into customer behavior and customer need. It helps determine what common issues are, and the best path forward: permanently solved or addressed using self-service options.
Data can be valuable, but it must be correct and actionable. Collecting data that doesn’t satisfy either is of no use and can bog down real efforts at improving customer service. The right data serves as the fuel to drive other initiatives in CustOps.
Powered by machine learning
Utilizing machine learning in customer service is one area that relies on data. It requires initial data to “teach the machine” how humans interpreted and responded in a given scenario, and then it can continue to learn both from its own work as well as human counterparts.
In what ways can machine learning help customer service? Cases can be classified, sorted, and routed with high accuracy, removing a mundane activity from customer service agents’ workload and improving customer satisfaction as a result of faster resolution time. As agents work with customers, machine learning can offer similar solutions from closed cases, knowledge base articles, online communities, and other sources. And chatbots–becoming more and more common–can also learn from prior interactions to assist customers.
Responding with agility
Like the concept of fast- or first-to-market, customer service must be nimble. It must move quickly to positively impact the customer experience. It must be able to work with other teams to address issues, preemptively notify customers of problems, and adjust as needed to serve customers on their terms.
Connected with other teams
Recurring issues with billing or shipping affecting multiple customers don’t originate in customer service. As these issues develop, they should be evaluated not just for one-time answers but permanent solutions. For this reason, it’s critical that customer service be able to easily connect with departments outside customer service to triage problems and work collaboratively towards solutions.
Workflow is the answer. With it, customer service can assign issues (backed up with the data to explain the problem and the corresponding case volume) to the appropriate team. In this manner, rather than offering workarounds, the root cause is addressed and the customer experience is improved.
Delivering proactive solutions
As customer expectation continues to rise, it’s no longer sufficient for customer service to stand by waiting for calls, chats, and emails. Customers expect companies to notify them when problems are known. Enter proactive service.
Proactive service relies on data that recognizes a trending issue and the likely-affected customers (either a subset or the entire customer base). With those customers identified, solutions to problems–be they steps to follow in a knowledge base article or instructions on how to return and replace a faulty product–can be preemptively communicated to customers before they encounter the issue. While problems disrupt the overall customer experience, proactive service can help to mend it.
Offering the latest service options
Engaging with customers has evolved over the years. While the telephone remains a popular channel, it has declined in favor of more modern options like email and chat. Social media and SMS/texting are more recent additions, and chatbots and even video are also popular. Add to this customers expect to find answers any time of day, no matter where they are.
Agility means keeping up with the times and connecting with customers over their channels of choice. Regardless of where an interaction starts, continues, and ends, the customer experience is continuous, not requiring the customer to reexplain their issue. It means offering anytime, anywhere self-service options like chatbots, an online community, a knowledge base, and automated solutions.
Next generation customer service
While this might sound like science fiction, it’s all possible today. It just requires the right customer service platform, the proper leadership at the helm, and the internal culture and drive to deliver customer service across teams. On the customer experience battleground, it’s all hands on deck. CustOps is the next generation of customer service that can help drive companies to that next level of customer experience.
