3 Ways Machine Learning Will be Game Changing for Customer Support

AI is all over the news, and with it a growing sense of how it could change our world. Organizations are rushing to create new applications and revolutionize age-old processes. A recent Economist Intelligence Unit survey found that three quarters of surveyed firms expected to have AI “actively implemented” within just three years. Customer support is no exception. In this blog, we take a closer look at how machine learning, a key part of AI, is being applied to customer support.

But first, how is machine learning related to AI? Machine learning essentially makes AI more efficient. You could get AI by creating a complex algorithm with millions and millions of lines of code. But this would take a huge amount of effort and yield a static outcome. What machine learning does is take an algorithm and teach it how to improve. It is fed huge amounts of data, and over time learns how to react and deal with increasingly sophisticated situations. Precision improves, as does the usefulness of the algorithm. This can be applied to customer support by automating the process of finding problems and suggesting solutions. This helps support centers improve in the following ways:

1. Faster Problem Resolution 

Customers want answers to their problems as fast as possible. Often, a significant portion of representative time is spent looking up fixes. What if this lookup process could be a lot faster? That’s what AI powered by machine learning promises. Several companies are already starting to use algorithms that analyze voice interactions between customer and representative to offer suggestions in real time on the screen. This cuts down on call time and frees the agent to help the next customer in line.

 2. Reduced Costs

It has been estimated that machine-learning-powered chat bots will save businesses more than $8 billion by 2022. A recent study by Juniper Research suggested that these human-mimicking computer programs could soon amount to 75% to 90% of all answered queries. This is especially apparent in the healthcare industry, where the same study estimates a $.50 to $.70 cost savings per interaction and four minutes of saved time.

As machine learning continues to improve the usefulness of these bots, we can expect that their scope will grow. While now they might have only a small range of issues they can deal with effectively, over time, their precision will grow until the user likely can’t tell whether they are interacting with a person or a bot.

3. Better Customer Satisfaction

One of the big worries of AI has always been user acceptance. Will customers mind interacting with a bot? Will they miss that human touch? Right now, the AI enabled by machine learning is not always good enough to come across as human. The customer often knows they are interacting with a bot or automated service. But the surprising thing is that they often don’t mind. Studies have shown that customers like interacting with automated services better than representatives. They get the job done more quickly, giving the customer more time back to do things they enjoy.

AI has been around for decades. But it has only more recently become mainstream with the deployment of machine learning and other tools. Customer support has a lot to gain from this technology, particularly in the areas of resolution time, cost, and customer satisfaction. Companies today can harness the power of machine learning and AI to reach their ultimate goal of happy, satisfied customers.