How far should AI lead your customer service journey?

In today’s environment, to meet customer expectations, organisations should equip themselves to deliver an ‘always-on’ service. Yet, the traditional service hours (9-to-5) are still common practice across industry. No longer do they need to be. With advances in Artificial Intelligence (AI), AI-powered chatbots are empowering organisations to provide 24/7 support and are fast becoming an integral part of the entire customer service ecosystem. 

85 percent of customer service interactions will start with self-service by 2022, up from 48 percent in 2019

Delivering Relevant Content and Knowledge to Customers Is Key to Great Customer Service (gartner.com)

Today, AI and automation is a broad ideal that includes a range of customer service applications:

• AI-powered virtual assistants across the web and SMS that facilitate customer self-service.
• Conversational interactive voice response (IVR) over the phone, matching customer intent with the best available live agent.
• Process automation, e.g. automatic case creation, triaging and next best suggestions. 
• Live agent augmentation with AI-guided scripts and knowledge base.

The ability to ingest and analyse an organisation’s historic and live data has opened new customer service strategies that integrate the best of AI and live-agent experiences. However, AI is not a silver bullet.

Let’s review how AI can benefit your business, and how it can improve your customer experiences.

Knowing when to automate

It’s important to carefully consider the areas that make sense to automate. Repetitive tasks and simple queries for customer service agents are an obvious first choice. For messaging, stick with questions that are frequent and simple to answer. The more complex a question is, the more generic a reply will be given by the AI, and the less personalised the customer experience. 

The importance of contextual data in AI

Data on its own is not enough. Shaping an agile customer experience depends on developing an understanding of how a customer’s entire data footprint relates to a given situation. It means taking inputs like date of last purchase, status of last customer service call, recent attitude towards your company and placing them into a larger picture. Contextual data is at the heart of the omnichannel experience. As a result, it helps organisations get a more up to date, broadened view of the needs of every customer.

Empathetic engagement with AI and automation

Automating simple, repetitive tasks enables customer service agents to concentrate on the more complex cases that require live assistance. Therefore, AI and automation can work in tandem. It can equip agents with the tools and knowledge they need to address issues quickly and empathetically. Contextual information about a customer service case will already have been gathered throughout the customer journey up to this point. For example, if the customer is high value, what their current sentiment is, how many historical complaints they have submitted. This leaves AI to suggest personalised routes that drive faster resolution and increased customer satisfaction.

The importance of ongoing customer sentiment

Your customers are the best source of data for identifying the benefits and shortfalls of your AI integration across your customer service. Using sentiment analysis combined with customer intent and speech analytics, organisations can gain an ongoing understanding of the parts of the customer journey that are working or falling short, without customers having to fill out any kind of feedback form. This is hugely beneficial for an organisation’s long-term customer service strategy. By delivering sentiment in real-time, insights can help leaders to understand blockers in their processes.

Finding the right balance between AI and automation empowers organisations to maintain the human touch across customer service, whilst optimising cost efficiency. It’s crucial that your workforce has the ongoing job satisfaction brought about by handling the more engaging and challenging tasks. With AI as a complementary tool, your agents have the skills and knowledge at their fingertips to deliver first time resolution. As a result, case handling times are reduced and customer satisfaction increased. The key is identifying when automation is appropriate. Getting this right can generate huge value for an organisation. However, getting it wrong can damage your reputation through poor customer satisfaction.

At Microsoft, we work with customers across industries to implement modular AI solutions that fit in to existing customer service ecosystem. This helps to unlock new value from data, create new efficiencies and drive improved customer lifetime value.

Find out more

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About the author

Chris leads the Dynamics 365 Customer Engagement portfolio for Microsoft UK within the Dynamics 365 Business Group. Chris is responsible for developing and orchestrating the go-to-market strategy across this portfolio for the UK geography to generate awareness, create excitement and drive business development. The Dynamics 365 Customer Engagement portfolio is a suite of intelligent front office business applications designed to accelerate digital transformation across sales, marketing and customer service