Learning from machines: The customer service shift
Customer Service

Learning from machines: The customer service shift

This is a contributed piece form Adrian McDermott, President of Products at Zendesk

More and more we’re seeing machines become part of our everyday lives, in particular as customers. Looking back, it’s difficult to think of a time where scanning your own shopping wasn’t an option, or when getting in touch with a brand didn’t involve some sort of automated service.

As we continue to demand quick and easy information and solutions, machine learning is becoming a sought-after option for business in their mission to maintain a strong relationship with customers.

That being said, the advances of machine learning won’t just affect the business/consumer relationship, but will completely revolutionise the way companies approach customer service itself.

Although many businesses are collecting information about their customers’ preferences, few are able to translate this into a better relationship. Businesses that are forward thinking enough are now tracking engagement history, purchase behaviour and support tickets, providing a greater overall view of the customer.

One key development in this area will be the ability to integrate separate information sources to build this view. Machine learning technologies amplify and extend the reach of data analytics, meaning they can help solve customer issues much more efficiently. This not only results in a quicker, more detailed end solution, but also reassures the customer that you understand their preferred outcome.

Even where machine learning is unable to directly resolve customer issues, systems will augment the experience and intuition of highly trained customer service agents by providing a wealth of curated information at their fingertips. Not only will this result in rapid customer service, it means the human element of interaction won’t be lost.

The integration of artificial intelligence into the customer service workflow will reduce the quantum of low-value repetitive work, allowing human resources to focus on high-value, complex service tasks that require a personal touch.

The age of artificial intelligence/machine learning has the potential to replace cognitive functions of the human mind in many business decision-making contexts.  As with all previous technology shifts, we will not replace ourselves completely. More likely knowledge worker capabilities will be massively amplified. We are entering a major technology inflection point.  

The human brain functions as a pattern matching machine; machine learning computing has infinite memory capacity for patterns via modern big data storage, and effectively infinite capacity for pattern discovery and matching - way beyond the capabilities of the primate mind. We are just beginning in our journey to use these now accessible techniques in everyday business problems.

The next ten years will possibly see machine learning systems capable of understanding the nuances and intricacies of human languages. We will also likely see the democratisation of machine learning. Currently there are few companies that have machine learning intrinsically baked into their DNA; as these technologies become more accessible more companies will embrace the revolution and leverage these technologies to maximise efficiency and quality.

Having an effective, but also adaptable customer service function has never been as important as it is right now. As customer data, analytics and automated technologies continue to develop and progress, so will customer demand and expectations.

Businesses need to find new ways to cater to a constantly changing audience. It’s clear that we’re facing a revolution in the way that businesses serve customers, as technological advancements make it possible to replace people with intelligent algorithms. The scale of change at hand makes machine learning a priority not only for global businesses such as Netflix and Facebook, but also for all companies.

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