Nothing kills a business quicker than knuckle-dragging customer service. In the digital world, where we have so many options available to us, customer loyalty balances on a knife-edge. This poses the question: how do organisations react before it’s too late?
It has been said over and over. Today’s customer is demanding and expects to receive an immediate response on the channel of their choice. An organisation can no longer dictate which channel they want to use to engage with customers and prospects. Otherwise they lose out - the customer will simply move to a competitor who is willing to engage with them on their channel of choice. And, if your customer chooses to switch channels during or between interactions, you will need to keep up.
Now, step back and think about what kinds of queries your customer service teams are answering most of the time. The majority of their time will be spent in answering the same types of questions – simple questions with simple answers.
A much smaller proportion of the time is spent on resolving complex issues which either require specialist skillset or provision of field service by a skilled technician. So, you can publish the common questions with common answers across all possible channels and hope they don’t end up with the contact centres, right? That’s what FAQs (Frequently Asked Questions) did, and it doesn’t suffice anymore; today’s customer isn’t very likely to go digging for answers from a list on your website.
They expect a personalised service provided to them on the channel they use the most, even if, to you, those needs are often the same as many other customers' needs. This begs the question - do you spend your resources fielding armies of customer service agents in every possible channel imaginable to provide a personalised experience to all your prospects and customers? That would be nice except most organisations don’t have infinite budgets. This is where automation comes in.
The age of automation
For most of the simple and repetitive queries, you can still provide a personalised experience to your customers using automation and free up valuable contact centre resources to handle more complex issues. Think of a chatbot which can handle generic customer queries and respond to them instantly on any channel, be it on your website or on a social media platform.
This doesn’t have to be limited to a pre-defined list of questions either. With machine learning, computer systems can be trained over time to provide better responses to more queries automatically, improving from the previous interactions.
And, when the query gets more complex, the chatbot can transfer the query to a customer service agent to resolve the issue. For the customer, this means no more waiting in long queues for a response; basic queries are answered instantly, and more complex ones are attended to quickly as more customer service agents have increased availability. For the business, it means increased efficiency and customer satisfaction.
Real world examples
There are many such use cases in the service industry where machine learning can help. When a ticket is created, it can automatically be categorised and assigned to the correct team from the beginning. Where field service is needed, it can propose the spare parts that might be needed based on an analysis of similar past tickets. In both cases, valuable time is saved both for the customer and the business. Again, these are examples of how we can make customer service more efficient, without impacting our relationship with customers.
For clarity, this is not about replacing humans with machines. It’s about moving the repetitive, mundane activities over to an automated service (such as a chatbot) and focussing the human resources to deal with the complex and unique issues of the customer. In case of chatbots, it’s like re-introducing FAQs but on steroids.
Want to find out more about automating service with SAP? Watch our latest feature
with our Head of Customer Engagement and Commerce Thierry Crifasi.