As concerns of further spreading the pandemic took hold, many companies quickly moved staff home. Despite the many challenges this created, it allowed businesses to remain active and viable–to a limited extent–in all areas, including customer service.
Now, countries around the world have started taking steps towards lifting stay-at-home mandates and to restore some aspects of professional and private lives. Government guidance is available, yet businesses remain cautious. With an early study (in a South Korean customer service call center) showing the risks of close seating in the COVID-19 era, some companies are electing to maintain a work-from-home stance. This leads many to believe it’s here to stay.
These are challenging times for any business. Understandably, there remains a lot of uncertainty about the right time and pace to resume regular office operations. Customer service relies on people and collaboration to function. The safety of staff has always been important, and today’s environment introduces even more challenges to employee well-being in a contact center setting.
Despite the shutdowns that occurred across the globe, the volume of requests in customer service has not subsided. Add to this the workforce uncertainties as a result of the pandemic that will remain for the foreseeable future. This is a challenging time to be in customer service, and to know when is the right time to return to the contact center and to manage that transition. But just as it has helped address heavy workloads with limited staffing prior to these extraordinary times, automation (in its many forms) is the solution for picking up the slack in customer service.
When the term “automation” is used, workflow is typically one of the first concepts that come to mind. It ensures reliable, repeatable movement of case work between customer service agents. It ensures work isn’t lost or stalled by routing and detouring work to the agent or teams necessary for timely resolution.
Sometimes the solution to a customer’s problem is found beyond the confines of customer service. Finance alone can address billing issues, engineering or manufacturing must handle product issues and defects, etc. Using workflow, these issues can be routed to the appropriate teams for review and disposition. By automating this collaboration process, work flows across departments as a solution is sought. Staffing on teams outside customer service are also potentially limited or working out-of-office, so workflow’s routing and rules ensure issues aren’t lost or delayed, unlike when manual processes are used. Status and accountability are maintained.
Service level agreements
Speaking of delays, time plays an even more important role when service level agreements are involved. Though some companies may have renegotiated them in light of current challenges, customers still expect a timely response.
On this front, workflow can automate the process to ensure forward progress occurs. Timers can be set as cases are created for customers based on their service level agreement. If a case is not advancing towards resolutions, it can be reassigned or escalated.
Customer self-service exists in many forms: knowledge bases, online communities, task automation, and chatbots are among the most common that can take advantage of automation in some fashion. Consider:
- Customer feedback on inaccuracies or clarity issues in knowledge base articles can trigger a review process with editors
- Online community posts that have gone unanswered for a specified time period or posted by certain customers can generate a case for a customer service agent to review and respond to
- Community questions marked as solved can be automatically harvested for consideration as new knowledge articles
- Common tasks such as registering a product, opening a new account, or resetting a website password can be automated through online form submissions
- Chatbots follow scripted conversations that triage the customer’s issue and then refer them to solutions (and can also direct them to knowledge articles and automated tasks)
Self-service channels are useful, but they don’t always address every problem. In some cases, customers also might bypass them and create a case themselves. That case must be directed to the appropriate agent. By relying on machine learning, this process can also be automated.
By relying on prior case routing history, machine learning breaks down the various attributes of the case. This includes such details as the type of problem and its priority (which might be related to the severity of the issue or the customer). Other criteria such as the customer’s geographic location, if they receive priority service, receive aid from a particular team, and preferred language can also be considered. Using this information, machine learning automates the process, ensuring the case is routed to an available agent best-skilled to assist.
Managing the transition
Many questions remain on the safest way to bring employees back into the office. In fact, what we once knew may never return as many businesses consider offering staggered returns or a combination of in-office and work-from-home to open up spaces.
While for many customer service has continued to operate in some capacity, companies are looking for the best path forward to return to some semblance of normal. Automation–in its many forms and already utilized by many businesses in some manner pre-pandemic–provides assurance and continuity to businesses as these issues are unraveled.