Continuous Improvement In Customer Service Requires Digital Disruption

continuous improvement

In his well known Harvard Business Review article on rethinking continuous improvement, Ron Ashkenas states that too many continuous improvement projects overly-focus on gaining efficiencies rather than challenging the basic assumptions of what’s being done. He says that organizations would do better to question whether their processes should be improved, eliminated or disrupted. Once that’s decided, only then should they proceed with their continuous improvement focus.

Modern customer service aligns perfectly with Ashkenas’ position. Customer service leaders must improve, eliminate or disrupt their customer service processes now to satisfy the modern consumer – and digital disruption is the most seamless path to achieve a state of continuous improvement in customer service.

Going digital is fundamental to better customer service

When customer service becomes digital, an organization can pivot to managing much of its customer traffic via asynchronous messaging, which opens up a world of positive process disruptions. What is asynchronous messaging? It’s the opposite of synchronous messaging. ‘Synchronous’ requires real-time discussion, while asynchronous messaging can be real-time or time-lapsed. As a result, asynchronous messaging happens in the same way most of us communicate in today’s popular messaging apps like WeChat, iMessage, WhatsApp, etc. We start a conversation, leave it for a while and return later to complete it. It’s convenient and allows for ultimate flexibility.

Once your customer service team gets comfortable with asynchronous messaging, you can quickly introduce natural language processing (NLP) and machine learning (ML) into your customer service processes. Suddenly, you will have made another leap forward in continuous improvement in customer service. Now, rather than bogging down live agents, you can let an answer bot serve as the first point of contact with your customers.

How an answer bot functions is not a black-box invention or feat of complex programming. You need to appropriately tag all of your typical customer service issues – the ones you and your staff practically know by heart – and develop content that can answer/resolve those issues. Most organizations do this by optimizing knowledge articles so that the artificial intelligence (AI) that drives the bot can route customers to the most relevant self-service content.

Your knowledge base is continuous improvement in customer service

The more you develop and improve your knowledge base content, the better bots are able to provide content choices that drill down deeper into the specifics of customer problems. So, as you periodically review the wealth of discussions managed by your chatbot, you can fine tune your knowledge content and continuously improve the self-help processes you have in place. As you can see, modern self-service is characterized by activities primarily driven through answer bot, combined with in-app and web portal knowledge articles. 

Machine learning makes your bot better over time

Today, it is quite easy to blend machine learning with an answer bot so that your bot responses continuously improve. After just several months, your bot will make more intelligent suggestions for helpful content and it will do so with ever-increasing speed and accuracy. Soon, your continuous improvement in customer service will be measurable in how quickly your ticket backlog shrinks. Every accepted ML-driven suggestion becomes another ticket deflected away from costly live-agent support.

At this point, with your organization already using AI, ML and bots, your customers will have already noticed your new and improved levels of customer service. They will also understand better how to resolve issues, which will further optimize your overall agent productivity and time to first response. 

Automation extends the improvements

Once an organization has lived with AI, bots and ML for several months, the benefits of automation will crystallize in everyone’s mind. Imagine having all the frequently asked questions and common ticket use cases managed automatically. Automation comes in handy as a way to create workflows that align with your various use cases, optimizing the time that agents spend in customer conversations. 

You will further ensure continuous improvement in customer service when you integrate back-end systems with your customer service via automated workflows. For example, when a customer complains about a product they received, your bot can query them for the order number and/or customer name. From there, an automated workflow can perform a data pull from the CRM system, enabling the bot to progress the conversation – in full context – without any human intervention. 

Continuous improvement is virtually unlimited

As you can see, the opportunities for continuous improvement in customer service are almost endless when you modernize with the right customer service tool. Helpshift combines AI, bots, knowledge base capabilities, ML and automation to help you disrupt the way you do customer service today and provide a superior, innovative customer experience.

Published September 4, 2019
block background image