4 Things to Get Right When Implementing AI For Customer Service

 | 
May 8, 2023
May 8, 2023
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Read time: 
5
 min
4 Things to Get Right When Implementing AI For Customer Service

The recent focus on AI has led to renewed questions about how AI can be used for customer service. And while there are many products that offer a range of services, the truth is that AI is best used to simplify customer service through improving the customer experience, in turn reducing costs.

There are a range of technologies that are available to do this, but regardless of the exact technology stack, there are some considerations you need to make and some things that are vital to get right when implementing AI for customer service.

Discovering Customer Needs

Many businesses have at least an inkling about why customers reach out to them and over which channels, but they need to truly understand their customers before they can meet their needs. The focus has to be on creating excellent experiences that customers find productive for their specific needs.

So how do you understand why your customers reach out for service? If you have data already then you can analyze that. If not, then you need to do some digging and find out if you can either acquire that data or speak to the people that run your customer service operations.

You also need to dive deeper to understand why your customers are reaching out in the manner they are. For example, do you have some reasons that can only be achieved through a certain channel currently? Are there trends in demographics as to why someone would reach out and does that result in them using a certain channel more, or are they just more comfortable using that channel?

Once you have an understanding of this, you need to translate these needs that people are calling for into “intents” and create conversation flows from there. Much like the process of discovering the intents, these conversation flows should be designed with the customer in mind, both in terms of ease of use and language they will easily understand.

Decide If You Want to Build or Buy Your IVA

Someone needs to communicate with the customers and that’s where the intelligent virtual agent (IVA) comes in. So how do you select which technology to use for your IVA?

You have several options to pick from. Some, such as Five9 and Avaya, are largely standard out-of-the-box options that you can configure but don’t offer a great deal of customization options. Others, such as Amazon Connect and Twilio offer you the chance to build much more of your solution, but require the skillsets to do so.

The question largely boils down to whether your needs - your environment, your demands, or the flexibility you need to serve customers - are unique enough that building a solution is right for you, or if you think a relatively standard offering will suffice.

Set Yourself Up For Self Service

Determining your customer needs and choosing the right build or buy platform will position you to start enabling self service, but there’s more work than that to do to actually make it happen.

Along with building your conversation flows and determining what use cases are achievable for self service, you also need to think about your backend systems and how you’re going to integrate your customer service platform with them. For instance, for self service around order tracking, you’re going to need information from your order management system to update your customer.

Systems you need to think about include your CRM, content management systems, knowledge bases, and any other potential enterprise systems that you need data to flow to and from.

Enable Insights and Proactive Care

Having self service isn’t enough - you need to think about how your customer service interactions can improve and how you can enhance the customer experience over time.

To do that, you need to design and implement a unified data model to generate insights in an insights portal that you can react to and improve your customer service.

Creating an impactful insights portal ultimately comes down to who is going to use it and how. Research who they are, what information they need generally and what’s most important, how they’re likely to use it, and how they want to track data over time.

Crucially, those insights can help you explore where you may be able to use AI/ML to implement proactive care, improving the customer experience, while also lowering costs and flattening out potential contact spikes.

If you need help considering these things, we help enterprises consider their approach to AI for customer service, focusing on the people, the business, and the technology. We also have a recommended framework for AI-Enabled Customer Service, which you can read more about here.