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How to improve customer service with call deflection

The key to providing world-beating customer service is to ensure your team has the time and the bandwidth to deal with every customer’s issue effectively. That means ensuring call volumes are reduced and customers are able to self-serve. That way your team can focus on customers that need their time the most.

Call deflection is one method of ensuring that your agents are able to deal with urgent queries effectively. Here we’ll look at how it can be used as a strategy to reduce agent stress and increase customer satisfaction. 

What is call deflection?

Call deflection is a method of relieving the strain on your customer service team. It focuses on resolving a large volume of queries without the need for human interaction, providing customers with the information they need quickly and effectively using automation to provide resolution. The result is improved customer service and a less stressful environment for your customer service team. 

Why use call deflection?

Let’s look at the reasons customers are contacting you? In one form or another, they’re looking to resolve issues. Finding out what their issue is would be the first port of call for any human agent and it’s no different when you use automation. However, automating that process by screening calls to determine intent means that not only can you ensure your customer service agents are only dealing with issues that require human intervention, you can also record that data to influence future customer call flows. For example, if you find that a lot of your customers are trying to access information about their accounts, you could put that option front and centre on your IVR or voicebot solution. 

You can use pre-live chat surveys, MPS surveys and data captured from your voicebot and chatbot solutions to determine where you should weight your content and even what elements of the customer journey could be removed to make it a more seamless experience. Mapping each contact back to the beginning of their journey will give you a wealth of information about how easy (or otherwise) it is for customers to find the information they need. 

Case study: Missguided

UK fashion brand Missguided experienced a large uptick in customer queries and its customer service team was finding it difficult to cope with the sheer volume of calls it was receiving. Realising the solution was to automate elements of customer service, Missguided came to us to create a chatbot solution. 

During the first few weeks, engagement with the new chatbot via the help page hit 65%. Eleven months later, the engagement level had reached 80%. The result? A 14% reduction in contacts and costs. 

Read the full case study

Automate early, automate often

Using the information you’ve gleaned from your automation solution, you can also look at areas you can automate earlier in the customer journey. 

You can discover areas where you can reduce call volume with other automations solutions: FAQ chatbots, customer service chatbots, voicebots, live chat, AI chatbots, and the like can all help you to reduce the volume of calls your customer service team receives. 

Creating a culture of self-service among your customers improves the experience for both customer and customer service teams, so it’s something you should pursue wherever possible. 

When we can reduce call volumes and encourage self-service, it serves to increase the efficiency of customer service agents, reduce customer frustration and allow us to lower customer service costs by limiting the hours we need human agents to be physically available. 

Case study: NI Water

Recognising that its millions of customers needed a quicker way to get the information they needed, NI Water came to us for help in creating the ‘Ask NI’ chatbot solution. From day one, the chatbot was able to handle 70% of customer queries, rising to 93% two years later. 

NI Water also used our Conversational AI Cloud solution to build a knowledge base to address the issue of knowledge leaving the business and to help bring new staff up-to-speed.

Read the full case study

Human or ‘bot?

Knowing when to hand over from automation to a human agent is vital to ensuring automation doesn’t cause more frustration than it removes. It’s not always about the intent of the call. Sometimes a customer may appear to have a relatively simple query that evolves into something more complex as the conversation goes on. That’s why having the ability to continually assess the flow of the conversation in order to hand over to an agent where appropriate is so important.  

Even in situations where your automation solution has to hand a query to a human agent, it can do a lot of the heavy lifting beforehand; getting name and account info, for example, as well as discovering the reason for the call. All of this reduces the handling time for your agents.

Case study: VIVID

Housing association VIVID decided to automate its call centre to give its customers more contact options. Using our Conversational AI Cloud solution to deploy a chatbot and voicebot to relieve the strain on its CS team, VIVID was able to improve customer satisfaction and give its agents the breathing space to deal with more complex queries more effectively. In addition, its voicebot solution allowed VIVID to offer 24/7 customer support for the first time. 

Read the full case study

Get in touch

If you’d like to find out more about how call deflection can help your customer support team improve customer satisfaction, get in touch with us and we’ll talk you through our suite of cloud-based customer service solutions

Find out more about how call deflection can help your customer support team.

Conversational AI Cloud Speak to an expert

Find out more about how call deflection can help your customer support team.

Conversational AI Cloud Speak to an expert
Theresa Bullock
Theresa Bullock,
Technical Consultant

Theresa is a Technical Consultant for the UK&I. She is passionate about NLP, cutting-edge solutions and conversational AI technology. As an expert in her field, Theresa guides customers in implementing chatbots, voicebots and SaaS solutions.

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