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In today’s digital world, customers have high expectations. They want services to be available 24/7, to have issues solved quickly, and to use the channel they prefer when communicating with you.
In many markets, that can be the difference between making and losing sales. Research by Bain &Company , for example, found that excellent customer experience (CX) was associated with revenues that grew 4%–8% above their market.
Statistics like this could be a result of companies tackling CX directly – yet it could also be because they consider employee experience, which, as Glassdoor research suggests, may be linked to better CX in turn. They found that a 1-point increase in a Glassdoor company rating is associated with a 1.3-point increase in customer satisfaction. A win-win!
No wonder, then, that there has been such rapid growth in conversational AI– as companies look to improve experiences for employees and for customers.
Whether communicating via a text-only chatbot, over the phone, or through an IoT (Internet of Things) solution such as Amazon Alexa, conversational AI allows humans to interact with machines in the most natural way – speech.
It makes sense to consider this technology for your own business – but where do you start?
At FGS, we suggest you begin with a few simple use cases, and aim to become productive with them first. From there, you can expand conversational AI further.
In this blog, we provide six tips on how to find the best use cases for your business, for a successful start with conversational AI.
Begin with the needs of your users. These could be your customers – whom you could reach via a focus group or survey – or they could be your employees. Either way, involve them as early as possible in the project.
I recommend gathering a diverse set of users in a first workshop, and ask them the following:
You will be surprised how many ideas arise from consistently involving users in your thinking. These insights will serve as a foundation for the next steps.
Once you have a few use cases to choose from, figure out which ones to implement first. At the moment, this is about the art of the possible. How can you make the best start?
A simple impact/effort matrix (see diagram below) may be enough for your initial assessment. Try to focus on use cases with high impact but low effort – in other words, the “quick wins”.
That said, to avoid pitfalls and work effectively, you’ll also need to consider other criteria, such as regulation, IT architecture, IT security restrictions, existing business process, and cultural considerations.
At FGS, we can help you work out which conversational AI use cases to focus on – and which should be tackled later for the reasons above.
IMPACT/EFFORT MATRIX
IT has evolved rapidly in the last few years – and conversational AI is no exception. We’re now far away from simple keyword-based chatbots; instead, we can develop complex conversational AI systems, able to simulate natural conversations through a mix of AI and rule-based processes.
We can build conversational AI which understands the meaning of free utterances extremely accurately. With efficient low-code platforms, we can implement various use cases quickly and bring them to production within weeks.
At FGS, we can provide an overview of the possibilities of modern conversational AI in a live demo. To find out what conversational AI is capable of.
Conversational AI’s ability to accurately understand the user’s requests opens a wide range of possibilities to support the user.
Suppose an employee wants to know how she can order a new laptop. The dialog with a chatbot could go as follows:
A smarter way to handle this request is to not just provide the user with a link to the order form, but instead handle the entire ordering process for the user:
In the last dialog, the employee receives quick help for her request and does not have to fill out time-consuming forms elsewhere.
Behind the scenes, conversational AI could be triggering a robotic process automation (RPA) bot to handle the process, or directly creating the order in another system.
This would be a first step from a simple chatbot to a virtual assistant – and ultimately, part of your journey to hyperautomation.
In hyperautomation, multiple automated technologies can connect with each other, helping you to gain higher-level benefits from intelligent automation and meet user needs more seamlessly. It’s also possible, of course, to connect new automated processes with your existing IT systems.
A vision has power to radiate – and defines your ambitions for an excellent product, internally and externally. Once you have a vision, you can plan your conversational AI project by breaking it down into a concrete product roadmap, use cases, and single tasks.
It’s perfectly fine to start with smaller use cases as long as they fit into your overall roadmap and strategy. Such a use case could be a chatbot which answers questions, or one which automatically makes appointments for your clients with your staff.
This approach helps you to quickly provide something of value for your users within a few weeks.
Once the foundation is set, the chatbot can evolve by adding further features.
In the long run, again, you could be working on a journey toward hyperautomation. Of course, the right solution won’t be the same for every organization – and how conversational AI connects with other automated technologies will, of course, depend on your business goals.
At FGS, we can help you use AI to improve customer satisfaction and loyalty – and take your enterprise to the next level, now.
