If asked what frustrates most about customer service, people might respond with many possible answers. It could be agents with a bad attitude. It could be poor customer policies. These are all definitely impediments, but there’s one thing that’s guaranteed to frustrate customers the most.
Time. Or more appropriately, the passage of time–and the waiting that entails.
As Carol Bruess, a St. Thomas professor specializing in communication behavior puts it:
“Waiting too long in a line is often perceived as a violation of our right to manage and control our time.”
Nowhere is this truer than waiting for an answer from customer service. And unfortunately, the waiting is built-in to several steps of the process. Customers wait in a telephone, chat, or email queue for acknowledgment. Depending on the communication channel, there might be waiting in the back-and-forth as the customer service agent triages the problem. If they don’t have a solution readily available, customers wait again as the agent triages, researches, and possibly escalates the issue to another person or department.
Wait wait wait.
Waiting is not new in customer service. Untold amounts of research have been conducted on how waiting impacts a customer’s perception of service. Similar research has been conducted to find the best methods of mitigating that waiting feeling.
It would seem waiting is unavoidable.
But that’s not necessarily the case. There are many ways time–and the inevitable wait–can be reduced or eliminated in customer service in ways that don’t involve simply adding more staff.
Jump on trends
The place to start is by identifying problems sooner. As agents document their customer interactions in cases, both machine learning and analytics can help recognize the various types of issues customers are experiencing.
Once problems are identified, knowledge base articles can be authored. These can be published online so that customers can access them via self-service–searching the knowledge base directly or having chatbots direct them to the articles. Agents can also refer to articles when working with customers over live channels.
Analytics can also reveal gaps in agent knowledge. Issues requiring additional agent time to solve or frequently escalated to more experienced agents illustrate a need for additional training. Addressing those limitations means faster resolutions for customers.
Optimize agent performance
Know-how and experience isn’t the only thing that can limit agent response time. The tools they use might also be holding them back.
Ensure the agent experience is optimized for their work. Combine the multiple back-end systems (e.g. customer information, case management, order tracking, etc.) agents need to perform their work into a single platform. Observe how agents work and organize data entry and information screens so that commonly needed details are readily available. Put less frequently used information on secondary screens and tabs.
Utilize machine learning
And on the topic of making agents’ jobs easier, give them a knowledgeable sidekick. By tapping into prior closed and solved cases, machine learning can monitor cases as agents work on them and offer potential solutions from such sources as other closed and solved cases, the knowledge base, online community, and other locations. These solutions can then be easily pushed out to the customer by attaching the article to the case, sending via email, or sharing in an online chat.
Machine learning can assist in other ways. Using additional analysis from prior cases, it can assist with the prioritization, categorization, and assignment of cases. This has a dual positive impact on time reduction: first, machine learning can accomplish these tasks significantly faster than a human with similar accuracy, and second, this frees up agent resources to assist customers or to perform other more valuable work.
Connect dots with workflow
Workflow offers a pre-set and repeatable means of completing a single action or several related tasks by individuals or teams. Detours can be established and timers set so that work isn’t delayed or stopped. This allows workflow to speed up customer service in two ways.
Address issues across teams
An error in the product manual means customers are calling for assistance. An erroneous charge was added to customers’ billing statements. These are just a few examples of problems customers encounter that originate as a problem caused by an error in a department outside customer service and affect multiple customers.
In these cases, customer service must work with other teams to identify and address the root cause. Workflow can facilitate this by routing the problem from customer service to the department responsible while keeping all parties accountable and ensuring established timelines are followed.
Manage SLAs
Service Level Agreements (or SLAs), whether formal or informal, define the rules of engagement between customers and customer service. Some SLAs even have financial penalties when a company’s customer service team doesn’t acknowledge and resolve an issue fast enough.
Workflow assists by monitoring cases and rules associated with SLAs. For organizations that offer “follow the sun” service, unsolved cases can automatically be reassigned to other available service centers as agents end their day. When a time threshold in an SLA appears headed for breach, workflow can escalate the case to others.
Control time
Benjamin Franklin once said, “Lost time is never found again.” Customers waiting on hold with customer service might not know the quote, but certainly they feel the sentiment in the moment.
While adding more agents is always an option, it’s not the most cost-effective. It’s time (no pun intended!) to investigate other options. Explore how investing in analytics, agent workspace optimization, machine learning, and workflow can help reduce and even eliminate customer wait.
