Forward thinking companies are customer obsessed. Naturally, they are focused on the ways to improve customer experience. Technology, especially automated customer service applications, are a common place to start improving the customer experience.
When this kind of technology, such as Conversational AI, is put into the contact center, it improves many areas beyond customer experience, including agent experience, operational efficiency and costs, and the ability to gather and use data.
However, none of these benefits can be seen without implementing the technology for the correct use case. In this blog, we will refer to a use case as the specific function for which the automation is used. In other words, the task that the automation is taking over.
Use cases depend entirely on the industry and specific business that is being evaluated. Some typical use cases include (but are not limited to):
- Creating and updating accounts
- Billing and payments
- Finding nearest location
- Resetting passwords
- Processing returns and refunds
- Updating shipping information
- Reminding customers about future payments
- Scheduling appointments
- Providing account or order information
- And more
Why is it important to choose the right use case?
Applying Conversational AI to the most appropriate use case can have a big impact on results.
Let’s say your contact center agents spend 5% of their time helping customers reset their passwords. If a virtual assistant is only brought in to cover password resets, then that will only free up about 5% of the agents’ time. Sure, this is an improvement. However, for a truly transformative solution, there has to be more of a change.
It’s also important to consider how well a solution is able to help customers. If the self-service isn’t truly self-service, then customers will end up right back in line to speak with an agent.
Choosing the right use case
Conversational AI is not a one-size-fits-all kind of technology. Designing an application isn’t just about having advanced technology, but also an expertise around where that application should be used. Different industries, and even individual businesses within the same industry, may have drastically distinct use cases and requirements that require the technology to be adapted to their needs to ensure success.
Here are 3 questions to help you begin to choose the best use cases for your application.
Does it follow business rules?
No matter how advanced an application is, there still needs to be business rules and dialog management in place to keep conversations consistent. That’s why standard and repetitive transactions excel with self-service. However, there are occasions where a human is needed to bypass business rules or find an unconventional solution for a customer. If a use case commonly needs this expertise, it may not be the best for automation.
Does it save the customer time?
If the use case in question will actually take more time with automation, it’s not going to improve customer experience. Advanced technology is necessary to ensure that customers don’t spend their time repeating themselves or digging through menu trees. Mapping out the conversation design with a designer who has expertise in customer service and AI can help ensure the customer will have the most streamlined process.
Also, if the Conversational AI technology is not advanced enough, it will result in the customer spending more time on the interaction.
Can it be improved over time?
Use cases can’t be too narrow or too broad, or they won’t collect enough useful data to be improved over time. Also, the use case has to be popular enough to collect training data to create initial models.
Working with a team that has expertise in AI and conversation design can help navigate which of these use cases fits this consideration.
What else is important to consider?
Successful Conversational AI is holistic. Meaning, there is a lot that goes into it. It’s important to look across the entire customer journey in a zoomed out view to understand exactly what use cases will best fit for your industry and business.
There is no magic formula for which use cases are best with Conversational AI. However, working with a managed service, who have years’ of knowledge and experience in AI and conversation design, can help ensure that your Conversational AI implementation will be impactful and successful in the long-term.