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The Impact of Self-Service Channels on Customers

12th Nov 2019
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In recent years, the rapid growth in AI technology has meant the customer experience has changed dramatically. The roles of customer service agents are becoming increasingly specialized, as artificial intelligence is able to deal with ever-more complex customer queries. 

Customer preferences have also changed. These days, more and more customers prefer autonomous shopping experiences - they want to be able to find their own solutions to problems, rather than relying on service agents.

Businesses need to adapt to these changes and optimize their CX around technology while ensuring their service agents are sufficiently trained to solve the problems that AI can’t. In this article, we’ll talk a closer look at the impact of self-service channels and what it means for businesses.

What are self-service channels?

Self-service channels are tools and platforms through which you can provide support for your customers without requiring a representative for your company to actually interact with them.

This includes things like AI-powered chatbots that can answer customer queries and solve basic problems, community discussion forums through which your customers can share knowledge, FAQ pages, and other, similar platforms.

Why self-service matters

Statistics show that the most important part of the customer experience, according to customers, is fast response times. 75% of participants in a recent study from 2016 agreed with this statement.

Not only that, but 40% of customers actually prefer self-service over human interactions. It’s no wonder, then, that 70% of customers now expect to find a self-service application on a company’s website.

This trend towards customer self-service has been driven largely by changing consumer habits. People now spend more time interacting with technology than ever before. We’re used to being able to find answers to our problems and questions at the click of a button, and we demand that same convenience when we interact with brands.

Businesses should take stock of these customer preferences and adjust their customer service model accordingly. Customers no longer necessarily value human interaction above all else. They don’t want you to answer their questions for them, they want to be able to find answers themselves.

This is not only better for the customer, but it’s also better for your bottom-line too. The easier it is for your customers to serve themselves, the less you have to spend on your customer service staff. Having chatbots and AI answer your customer queries should help to reduce your call queues and enable you to cut costs.

Customer journey mapping is important

While self-service technology is now more advanced than ever before, it’s still not perfect. There still is - and will likely always be - problems that AI can’t solve. When AI fails, customers may still need to chat with live agents.

This transition should be as seamless as possible to reduce customer frustration, which means ensuring a smooth transition between your different contact channels.

For example, when a customer asks a question that your chatbot cannot answer, you might want to automatically send them a script asking them to call your service line instead. You could include a contact number for the correct department so that your customer can immediately get in touch with the right person.

In this scenario, your customer might have already explained the problem via text to your chatbot - do they want to have to explain it all over again to your agent? Probably not. 

Therefore, an even better way to improve the customer experience is to make it easy for your agent to see the messages the customer has already sent so that they can more quickly resolve the problem.

Training your service agents

A final point to mention is that the growth of self-service makes robust training for your service agents even more important. The queries that they will have to deal with are likely to be more complex, so you need to make sure they have the knowledge required to answer these difficult questions.

A good idea is to look at the data you have to inform your training. What kind of problems do your chatbots often fail to solve? What sort of calls are your agents getting each day? And at what point do your customers feel compelled to call?

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