Why Intelligent Automation Is Imperative In Customer Service

digital tablet in hand with city skyline. There is also a digital tablet and mobile phone out of focus in the background. Image is superimposed on a city at sunset and a motion blurred road with traffic at night. City is Sydney, Australia. Internet speed and connectivity concept

Michael Evans is the Vice President Australia and New Zealand at Pegasystems. In this guest post he explains how customer service is evolving in the digital era.

The global pandemic has heaped pressure on organisations’ customer service more than ever before, so it’s important to get it right. As customer demands rise, a poor service experience with insufficient support or long wait times won’t be tolerated by customers—especially as they are tempted by competitors to take their business elsewhere. The answer to customer service success is intelligent automation.

Customer service has changed throughout the years; the “intelligent” part was once dependent on the intelligence, competence, and expertise of the customer service agent. For example, the best agents quickly figured out the most efficient ways to solve customer issues, understood how to navigate systems, memorised the steps required to resolve common requests, and established best practices. However, this level of “intelligent” customer service is now a baseline of what’s expected.

The next phase of intelligent service saw organisations (and the agents that represented them) try to understand customers and their needs. In doing so, enterprises tried to get a 360-degree view of their customers using agent-driven service. While the idea worked in theory, building a centralised database led to a flood of information that agents simply couldn’t handle. As a result, organisations realised that overloading customer service agents with information was just as detrimental as not giving them enough.

Then customer service was brought into the digital era. No longer primarily managed through phone calls, it expanded to include mobile apps, chatbots and social media. While it meant organisations were a lot more accessible, it was difficult to maintain consistency in interactions across channels. Organisations have always strived (and continue today) to give customers the impression they are always talking to one single customer service entity, even if they switch between multiple channels.

As time has progressed, these challenges become increasingly complex as communication channels become more advanced and tools like self-service portals become more common. The only way to successfully take on these challenges is to empower customer service teams with intelligence. This means being able to offer a contextual and consistent experience for customers. To achieve this, it’s imperative to have two things—customer insights and consistent quality of service across all channels.

Customer insights

Customer insights allow an organisation to really know and understand its customers individually; this includes their contact history with the company, the context of their request, and their current mood. If a customer is already frustrated, it’s important the organisation does not exacerbate their frustration with a poor experience—this means acting with empathy. On the other hand, if a customer is in a highly responsive mood, it may be an opportune time to make a cross-sell or up-sell offer.

To get the most value out of customer data, organisations need to apply predictive analytics to anticipate future trends and determine the next-best action to take. Predictive analytics, when empowered with real-time decisions, delivers cutting-edge customer experiences that capture cross-sell, up-sell, deep-sell, and retention opportunities.

Consistent quality of service across channels

Ensuring quality across all channels refers to the organisation’s ability to always provide an effective response, regardless of the communication used. Regardless if a customer is on the phone, on live chat, or on email, there should be no difference in the quality of the advice, the speed, or the solution.

In order to resolve customer queries in a timely fashion, it’s important customer service teams are able to rely on data quality and availability. Given the sheer volume of customer data generated across various channels and interactions, an AI solution is needed to analyse the data in real-time and make recommendations on the next-best action.

Implementing an integrated solution for intelligent customer service enables organisations to give the impression customers are only ever speaking with that one customer service entity I previously mentioned. Truly intelligent customer service, empowered by AI, will enable customers to self-serve and even learn how to resolve issues in the future without assistance. Autonomous service provides a number of benefits to its adopters, including reduction in cost, lower customer effort and accelerated issues resolution. It takes a journey-oriented approach, providing customer-specific and contextual answers, meaning information is dynamic and relevant. From here, success (i.e. a happy and satisfied customer) is inevitable.

As we progress into a new era of customer service, we will move towards proactive and pre-emptive service. Intelligent automation is being used to enable self-service and autonomous service—a combination of AI-powered proactive and pre-emptive service that addresses issues before the customer is even aware of them.

Intelligent customer service is key to meeting and exceeding customer expectations. It enables organisations to create smooth customer experiences and find relevant solutions in near real-time, regardless of the channel. Above all, it shows customers that the business is committed to them.

 




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