How AI and automation drive better customer service

A UK police force, for instance, used service design to discover that a large number of 999 calls were mere requests for information and were hindering call handlers from helping citizens truly in need. Additional research showed that fragmented processes and workarounds for existing blockers were reducing efficiency and visibility of the process for citizens. The solutions focused on better access to information rather than automation.

Forrester’s third tip is to prioritise opportunities that benefit both customers and employees. For each opportunity identified, evaluate who will benefit and then prioritise those that benefit both employees and customers.

One company that tried this approach is BT, which used AI to improve customer service by focusing its field engineers on the right job at the right time. Instead of using the workforce management system to assign jobs only to local engineers, the company used fuzzy logic to enable field engineers to cross regional borders, resulting in better service, increased productivity, reduced travel costs and improvements in employee well-being.

The fourth recommendation is to identify the right technology. The terms cover such a broad range of capabilities that the help of a subject matter expert might be needed to define what’s right for a particular company, depending on its existing systems and use cases. However, there’s one technology that’s fundamental for the contact centre – speech recognition.

Dutch telco KPN, for instance, used speech recognition to reduce its average hold time by 30 seconds per call and increased its net promoter score by 17 points. The customer begins by stating in their own words why they are calling. AI authenticates the caller, recognises their intent, and automatically answers or routes them to the right agent. When it does so, it pulls out the customer’s details and call history and transcribes their own words so the agent immediately has the right context.

Next is to make emotional connections beyond empathy part of the requirements of the AI and automation project. Subtle changes in words can improve customer experience by creating a positive emotional connection with customers. Content strategists know that what you say and how you say it can be a powerful differentiator. AI can generate emotionally engaging content, but you need to ensure its emotional capabilities.

For example, the team building Capital One’s AI assistant, Eno, focused on developing its emotional intelligence. As a result, the bank saw customers sending Eno gratitude messages after using it as if they had experienced a positive interaction with a real person.

Forrester’s final recommendation is to align success metrics for the end-to-end journey. Finding the right metrics to measure the return on investment of automation and AI requires a careful assessment. Avoid isolated metrics. Rather, define a set of journey-level quality metrics to measure impact correctly.

One story of woe is that of a telecoms company which had focused on reducing call times in its service centre when onboarding new fibre network customers. But when the firm partnered with McKinsey & Company to analyse journey data, it found that reducing call times caused more follow-up technician visits. This cost the firm between 10 and 20 times what it had saved by shortening call times.

This article is based on an excerpt of the Forrester report, “How AI and automation drive better customer service experiences”. Karine Cardona-Smits is a senior analyst at Forrester. Ian Jacobs is a principal analyst at Forrester.