What hasn’t COVID-19 affected? The way we work, the work we do, the way we connect.
Connection now resides in video conferencing, virtual happy hours and family FaceTime. In times of social distancing, this is our new lifeline. As a result, we are more dependent than ever upon internet providers, wireless carriers and streaming services.
It is no surprise, then, that communications service providers are fielding a significant increase in inbound contacts from customers. Call center wait times have skyrocketed, as have chat queues. Technical support and network operations are overloaded with requests.
How is this affecting the customer experience?
'Wait Times Are Higher Than Normal'
My personal, albeit anecdotal, experience in the past few days has been as follows: Every account I sign in to, regardless of whether it’s personal banking, wireless or ISP, offers a similar message:
“Extremely long wait times if you call us.”
“We appreciate your patience … wait times are higher than normal.”
“Our wait times are currently higher than usual. Please check back at another time.”
I am a patient customer. I am sympathetic to the demands and monumental shifts occurring within service channels. Yet the opportunity still remains for a better customer experience to emerge.
For service organizations in the midst of this chaos and unpredictability, where are the bright spots? What are some ways to improve/reduce/relieve the overburdened service channels?
Analytics can certainly play a part. There are many simple, short-term solutions to alleviate the strain on your most valuable, trained resources.
Here are four ways to effectively navigate these tidal shifts.
Automate Ticket Alerting Systems to Increase Speed to Resolution
For the network operations team receiving a surge in outage incidents or network disruptions: Do the right parties have access to real-time feedback from your ticketing system? As customers report isolated or large-scale outages and disruptions in service (likely at unpredictable times), your operations center may be working overtime to resolve incoming tickets.
Identify areas for analytical automation in order to improve customer response time, satisfaction and ultimately retention:
- Establish ticket volume thresholds based on new customer reporting patterns.
- Monitor incoming tickets in a real-time, self-service dashboard.
- Trigger automated email alerts when thresholds are exceeded.
- Quickly investigate and isolate common characteristics of reported incidents.
- Establish a feedback loop to take preventative action.
Refresh Root Cause Outage Analysis to Expose Quick Customer Support Wins
A timely and accurate response is what your customers expect — especially in times of service disruption. Is the customer experience deteriorating more when these new incidents occur? A wealth of insight lies in unstructured text verbatims directly from the customer or your internal staff. Technician notes can illuminate a sequential snapshot of incident resolution.
Quickly classify technician notes using text clustering techniques and automatically quantify common and emerging topics:
- Which types of tickets most frequently result in an escalation?
- Do customers in a specific region have to continuously check for updates on their reported case?
- Are your service centers providing the right level of communication?
- Are there any obvious inefficiencies in ticket handling? Sequential pathing, plotted visually, can help you quickly identify operational pain points contributing to poor customer experience.
Related Article: Where Self-Service Ends and Direct Customer Support Begins
Identify Emerging Chat and Call Center Inquiries to Relieve Queues
Call center wait times are high, while live-agent chat queues are maxed out. Trained call center and chat agents are a limited resource. What are your options?
Analyze chat verbatims to identify the most common topics with scalable text analytics.
- What are the emerging topics from customers? How does this week compare to last? How does today compare to yesterday?
- Use these insights to update (or construct) your virtual assistant. The automation and self-service options made available to customers can alleviate the inbound volumes.
Related Article: The New Wave of Web Chat: Here's What Has Changed
Proactively Identify Detractors to Focus Retention/Service Efforts
Is your organization relying on agent-generated dispositions to assess service center performance and inform strategic initiatives? Have you considered the accuracy (or perhaps inaccuracy) of the drop-down pick list?
Agent-generated “reasons for calling/chatting” may introduce bias in understanding the true reason for an inbound contact. Bias from training protocols, incentives to close the session quickly, or design bias from selections made available in the first place.
What if you could use an analytical approach, via text mining, to dramatically improve identification of an unhappy customer? The results may surprise you.
- Consulting engagements have shown agent-selected dispositions are not strongly predictive of NPS (measured by willingness-to-recommend).
- Instead, consider using an analytical approach. Text topic modeling on customer verbatims provides clear delineation between detractors and promoters.
- In other words, the results of this text mining exercise can be highly predictive of an unhappy customer.
Are these solutions groundbreaking? Maybe not. Are they executable with limited resources and the right technology? Absolutely.
Innovation, during these times, can emerge as the simplest solution. “Innovation” does not have to move mountains, break records or shine brightest. If it saves resources/time/money, does it really matter if it’s branded as “a leading-edge AI/ML/augmented/self-learning solution”? And furthermore, does the customer even care?
We can make small improvements and simple adjustments today to make our jobs easier, steady the course of business and reassure customers.