In this guest post, Rod Moynihan (pictured below), director of sales for Australia and New Zealand at Zendesk, explains how machine learning plays a critical role in providing a better customer experience with less leg work.
Have you ever wished that you could bottle up your team’s collective knowledge, save it all and access it in an instant?
In today’s world, customers expect information on-demand, and we want our issues to be solved instantly. Unfortunately, businesses are still wasting time repeating themselves, providing the wrong answer or inaccurate information to a customers’ inquiries due to out-of-date knowledge articles, and losing product and client know-how every time a peer leaves the team. The result is a strain on resources increased costs to serve and, worst of all, dissatisfied customers.
Despite the fact that 82 per cent of retailers believe big data is changing how they interact with and relate to their customers, few are yet to unlock the true potential of data.
Thanks to machine learning and artificial intelligence (AI), it’s easier than ever to provide a seamless customer service experience by tapping into collective knowledge to achieve faster support resolution and outcomes from anywhere. If your business isn’t yet up to speed, here’s what you’re missing out on…
New-age customer intelligence
Machine learning technology now has the power to amplify and extend the reach of data analytics to help solve customer service issues much more efficiently. Forward-thinking businesses should be looking for ways to tap into the power of machine learning algorithms to provide customer service in the fastest, most convenient way possible. If you’re not already taking advantage, there’s a good chance your competitors are.
Machine learning also has the potential for businesses to learn more about their customers, delivering contextually relevant engagements, be it from their shopping habits to their various wants and needs. This information creates ‘collective intelligence’ that can then be stored in a central location, which other agents can tap into at a later time.
Data and analytics is the first step to meaningful insights – the second is to make sure your agents are using the knowledge/insights to deliver a truly personalised experience for customers. Analytics should help you to be more proactive and responsive, so your customers know that you care.
Better knowledge-sharing, smarter agents
AI and machine learning have the potential to replace cognitive functions of the human mind. Worker capabilities can be amplified by the information provided through machine learning by arming customer service agents with a wealth of curated information at their fingertips.
As a customer, there is nothing worse than having to repeat your enquiry several times. And now you don’t have to, as there are many ways that AI/ML can predict what the customer might need. The more that can be automated, the more power the customer has, which puts less pressure on customer service agents. This also means that the person-to-person contact the customer does have, is faster and more personal.