Last updated: Customer service automation in 3 steps with AI and machine learning

Customer service automation in 3 steps with AI and machine learning


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Lately we have been hearing the word “automation” a lot in the context of digital disruption. It can apply to customer service.

  • Automate processes.
  • And automate delivery.
  • Don’t forget to automate your front office strategy.

Yet, automation can be a very scary word in customer service. In truth, customer service has been automating processes for decades. Unintelligently.

In the old method of customer service, automation was used by service organizations to buy agents time.

  1. You send an email to customer service and you receive an immediate, automated email response: Dear Valued customer, we have received your message. We will get back to you in 24-48 hours. You call customer service and you hear an automated operator: Your call is important to us. You will be connected to the next available operator. 
  2. When customer service tickets come in and the service queue is backed up, or it’s outside normal operating hours, automated messages were created to make customers feel heard while allowing agents ample time to answer questions and solve problems without being overworked.

Poor, unintelligent automation has been the mantra of customer service for too long, so it’s natural for anyone in the customer service space to be hesitant when hearing “Automation is the future,” or even scarier, “Automation is now.”

The reality is that customer service is in automation recovery. Decades of poor automation has left this line of business scarred and in desperate need of rehab. Service managers need to let go of what they think they know about automation and refresh and rebuild their service organizations to use automation intelligently.

It’s time for a customer service recovery.

A three-step plan to intelligent customer service automation and recovery

  1. Strike a balance
  2. Let data lead
  3. Build connections

Get ready to launch 3 steps to achieve customer service automation

STEP 1: Find a Balance

Believe it or not, not everything is appropriate to be automated. Most companies cannot rip and replace all their processes with machines, but are looking to strike a balance between what tasks an agent accomplishes and what can be handed off to intelligent solutions. Chatbots are the perfect example of how companies can strike a balance in automation.

Customer service needs are 24/7. Your agents are unlikely to maintain 24/7 coverage without incurring outrageous costs to your cost center, nor will your customers be happy to keep their service needs within your hours of operation. How do you solve this conundrum? Chatbots. Chatbots never sleep and are easy to scale. And once your agents wake up, they can pick up where the conversation left off.

Automation no longer means a generic message given to each customer who interacts with your service teams. With chatbots and intelligent automation, the service is much more personalized based on the customer’s needs, history, and specific asks. Chatbots will still struggle to identify and solve those more complex questions, but they then can transition to live agent support and save the conversation so an agent can pick up the conversation seamlessly with the customer. Find the right balance.

STEP 2: Let Go of Control

You are no longer in the driver’s seat: Your data is. Machine learning has opened the door for automation that is intelligent and has also cut the time in half for-if not completely replaced-many manual processes. Machine learning has become the lifeblood of an intelligent and contextual customer service organization.

Tasks like categorizing tickets, routing to skilled agents, recommending solutions, and recommending equipment for technicians (just to name a few), can take valuable minutes away from resolution times when done manually. Now with machine learning, your service solutions remove this responsibility from you. The more data your company has to work with, the more the machines learn, the smarter and more accurate the algorithms become, fewer are the manual steps that need to be done by agents. Machines do most of the thinking and your agents can focus on more complex tasks. Let go of control.

STEP 3: Make Connections

IoT is a cute little acronym that’s been making huge waves the last few years. The core of IoT is about connections: Connecting things so they can work together, alert each other, and operate automatically without (or with minimal) assistance from humans.

Connect. Sense. Act. Store. Analyze. Control. Share.

This is basically the opposite of what customer service has represented in the last few decades. Customer service is a siloed organization known for siloed processes. By making an investment in IoT and smart technologies that are powered by sensors, manual processes such as monitoring equipment health, taking measures, recording data, scheduling repairs, and ordering parts become proactive, preventive, and predictive.

Imagine the trust your customers will develop with you when you recognize a failure in their equipment or a shortage in their supplies before they do. IoT affords machines the ability to self-diagnose, and in many cases self-repair. Suddenly customer service becomes a proactive part of the organization, rather than the reactive part which it is known as today. Make connections.

Poorly used, automation tools can have the opposite effect of what you desire: High costs and customer frustration instead of streamlined bottom lines and satisfied customers. However, automation that is done intelligently can drive revenue and be the true differentiator of your company.

No matter where you are in building your service organization, it is not too late (or too early) to start customer service rehab. Leave those bad habits behind and create a service organization that operates intelligently.

The future of sales and service, today.
(So you can keep your customers tomorrow.)
Learn more HERE.

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