Customer Service in the Time of Corona

How to overcome unpredictable setbacks with elastic customer service

Most of us have learned about supply and demand in Economics 101. In a perfect world, increased demand leads to increased supply, and equilibrium is reached. Nevertheless, our world is far from being perfect, and friction comes into play. Think of the old days of ordering a taxi. Remember? You left a restaurant after a fun Saturday night, called a taxi and was promised it would be there in ten minutes. Twenty minutes later it started raining and your ten minutes became an hour. It is no one’s fault — it is a simple case of fixed supply (taxis) and  elastic demand (Friday night + rain). We accepted taxi’s unpredictability as a given and just complained about it to our friends – that is until Uber came along and invented surge pricing.

Uber added important elements that changed the supply and demand curve. It added vehicles and drivers (more supply), but also created a mechanism to incentivize drivers to leave their homes and drive when they’re most needed, by paying them more in times of high demand. Now, when demand increases, supply increases as well, until equilibrium is reached, and you can be picked up from this same restaurant in 5-10 minutes as expected.

So, why can’t your call center be elastic? I’ve spent years thinking about this. Why can’t you have trained agents that are called to work during peak hours? Flight cancellation due to the coronavirus? No problem. Just pay 1.5X, and agents will be there. But the reality is far more complex than that.

Agents are not drivers. Driving a car is a generic skill that doesn’t require specialization. Google Maps gives drivers the ability to navigate any city regardless if they’ve been there or not. Drivers can easily move between cities, and even switch between driving tasks (i.e. delivering takeout, transporting people, or picking up packages) as demand changes. 

Agents on the other hand, are highly specialized and require company specific training. Agents need access to internal systems, constant updates on protocols and scripts, and high speed internet access with a quiet work environment. And, to achieve the same elasticity as Uber, agents would have to train with dozens of different companies, which is not realistic, of course.

So what can call centers do to achieve greater elasticity during times of uncertainty?

  • Invest in workforce management software and best practices: Your first line of defense is implementing workforce management (WFM) software. WFM may not help with unplanned spikes but it can help create a solid baseline and prevent things like long wait times on a Monday morning when customers tend to call in on their way to work. If you are understaffed due to a lack of detailed planning, your ability to deal with spikes is limited at best which is why you need the right infrastructure in place.

  • Have a work from home contingency plan: The coronavirus crisis is a perfect example; imagine you’re an airlines company – if there’s an increase in call volume from customers calling to cancel or reschedule their flights and your agents can’t come to work due to exposure risk, you now have more demand, less supply, and the result is tweets like this. Before asking people to work from home, you should 1) know who can work from home and 2) set agents up for success when they do work from home by ensuring access to high-speed internet and quality hardware and software.

  • Develop a Maslow’s hierarchy of needs for customer service: Just like emergency rooms triage and prioritize patients, you should plan in advance for the types of calls that are most important to your business and customers. This means preparing agents to receive the highest priority calls, and deflecting the less urgent ones. Conversational AI (more on this below) can help to fully resolve a variety of transactional calls so that your agents can focus on the most important issues. 

  • Use Artificial Intelligence (AI): Conversational AI on the phone (AKA Virtual Agents) is an efficient way to resolve repetitive calls which are usually the exact types of calls you get during call spikes. For example, a food delivery company may get hundreds of  “where is my order?” calls during bad weather. Or in today’s case, airline companies are getting bombarded by calls from customers asking to rebook or cancel their flights with the outbreak of Coronavirus. Similarly, a utility company may get calls about power outages following a major storm. These are precisely the types of calls that AI-powered Virtual Agents can answer with zero wait time regardless of call volume, allowing human agents to focus on more complicated cases. Conversational AI can act as your first line of defense, offering elasticity, resolving cases faster, and sending the most complex issues to your less overwhelmed customer service agents to increase customer satisfaction. 

  • Prioritize self-service: Now is a great time to ask, “does this need to be a call?” In many cases, there is no symmetry between a revenue generating  transaction (i.e.ordering an item, booking a flight) and a cancellation (i.e. returning an item, canceling a reservation). For example, it took me 2 minutes to order a Nest Lock online, but to return it, I had to call customer service and spent 15 minutes on the phone with an agent. It takes 1 minute to set a password in a bank app, but it requires calling a bank to reset it. In both cases, a small investment in self-service like increasing in-app functionality can pay off handsomely and eliminate unneeded calls for your agents.   

There is no one strategy to deal with expected and unexpected call spikes, but deploying these strategies can help provide better customer service year round so that you can weather this storm and the ones to come. Have you implemented any of these strategies? Have you tried any others? Click “Let’s talk” on replicant.ai to drop me a line, I’d love to hear your thoughts.

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