In the world of today, chatbots are commonly implemented to answer repetitive questions. Nonetheless, the AI capabilities of chatbots increase constantly and we are beginning to experience new possibilities for how companies deliver services.
Modern chatbots are being used more and more for customer enablement, whereby customers can receive services from a company just by having a conversation with the bot. This type of software interface, known as a conversational UI, is already ubiquitous in the home with the widespread use of Alexa, Google Home, and various mobile phone-based assistants.
Nowadays, more customized versions of these assistants are being developed by businesses for providing narrow services. As businesses discover the benefits of conversational UI, we can expect to see customer enablement use cases for chatbots eclipse other forms of customer service.
Customer service chatbots are chatbots that act as automated customer support agents. These chatbots allow customers to seamlessly interact with them through text messages and by speaking through common communication channels, such as phone calls.
The creation of customer service bots is made possible thanks to the most recent advances in artificial intelligence (AI). Thanks to natural language processing (NLP), a field that mixes linguistics and cutting-edge computer science techniques, chatbots for customer service can understand, react, and learn from human interactions.
Currently, the most common use of chatbots is to enable text-based conversational experiences. AI-powered chatbots capable of text-based messaging, usually through webchat, have become very easy to implement and use. More complex chatbots can communicate with customers through the phone and are seen as a viable replacement for interactive voice response (IVR) systems.
Chatbot technology continues to develop and new improvements are always around the corner. In the near future, customer interactions with chatbots will be easily delivered through smart speakers such as Alexa, Siri, and Google Assistant. Customers will only need to speak to their devices to access information and get help with products and services.
A chatbot works 24/7 and provides quick answers when it knows the answer to the question. While this is not applicable to every query, a material number of queries can be answered very quickly and accurately at any time without the effort of engaging a human.
Chatbots make asynchronous communication possible. This means that it is much easier for the customer (and support agent) to multi-task. Moreover, this is a more convenient mode of solving queries than a synchronous conversation. This is particularly important when a live answer from a human agent is not possible.
Thanks to chatbots, businesses can offer their customers goods, services, and help without having to lift a finger. In this digital self-service environment, chatbots offer customer experiences almost indistinguishable from human agents, while also being able to handle multiple customer queries at once.
One of the greatest benefits of chatbots is their ability to respond instantaneously. Chatbots completely eliminate wait times and ensure every customer receives fast support.
Chatbots empower companies to scale their operations without ballooning their support costs. This can lead to substantial headcount savings or more agent time dedicated to customers with more challenging queries. Chatbot implementation can minimize customer service costs while also increasing customer satisfaction at the same time.
Advances in processing power and algorithms as well as increases in the availability of data have led to improvements in speech recognition and natural language understanding (NLU). This makes it feasible for chatbots to answer certain types of questions asked using everyday speech.
Nowadays, companies can set up customer service platforms to easily respond to simple, repetitive questions without any need for interaction with human agents. Since these questions make up the majority of the help desk queries, automating their answers allows companies to interact with more customers in less time. Every customer can be greeted by a help bot in order to streamline the user experience.
Chatbots are able to handle a considerable percentage of inbound queries. It is estimated that up to 70% of queries can be solved by a chatbot alone. Since call centers have the information to easily estimate what the operational cost per incident is, it is fairly simple for them to calculate the return on investment of chatbot implementation. This makes it much easier for sponsors of customer support chatbots to get approval for a project.
While the economic advantages of customer service bots are obvious, what is less obvious is why this will result in better service to the end customer. One obvious answer is that there will be more time for human agents to deal with more complex queries if the bot takes some of the repetitive queries off their plates. However, that assumes that the human agents continue to increase as the number of queries grows.
More often than not, companies that implement a virtual chat assistant expect to hold the headcount for human agents at the same level and meet the additional demand by scaling the chatbot. While this is logical from an economic point of view, it means that at some point the agents will reach their capacity again in terms of the time they can spend on certain types of queries.
The real difference in customer satisfaction after chatbot implementation is that customers have easy access to customer service agents via chat. Instead of having to phone in, the customer can instantly get help over chat. Of course, there have been cases where a chatbot is implemented poorly, leading to a poor customer experience. A badly designed customer service chatbot, for example, is designed to cover too many topics. It may also not have a method for quick escalation to a human if things go wrong.
Phone-based chatbots are particularly vulnerable to poor customer experience because they tend to feel very slow in receiving information and responding. This problem is made worse by designers making them too verbose and making it difficult for the customer to reach a human operator if things go wrong. If your customer wants you to bring back the IVR, then that’s a clear indication that your chatbot is in dire need of some revisions.
There are different types of customer service chatbots and these handle their assignments in different ways. Some bots have been designed to provide information while others perform tasks for customers. Regardless, most types of bots must be integrated with internal and external systems to be useful.
The simplest class of chatbot is the FAQ chatbot. This chatbot solution provides information and doesn’t require any integration with internal or third-party systems. The most simple versions of this chatbot only offer static information. However, more complex FAQ chatbots can provide dynamic information, especially if they can retrieve it from other systems. Generally speaking, FAQ bots are very simple to set up.
As chatbots become more advanced, they may be able to showcase the following features:
Human in the loop
This is a bot’s ability to escalate queries to a human customer service agent in case it can respond on its own. Not only is this functionality useful by itself, but it also allows chatbot designers to minimize the customer frustration caused by an ineffective bot.
Customer service teams can rely on the bot to solve the most common queries while they handle the more complex ones. Moreover, through machine learning implementation, a bot can learn from a query it wasn’t able to fulfill in order to better assess the same question in the future. Modern customer service chatbots tend to have some human in the loop capability. This means that customer support teams have a way to access a back end where they can respond to escalated queries.
Machine learning is a part of AI developed to help software applications process information in meaningful ways. Through this competency, chatbots can learn from customer interactions and improve their customer service performance without any other human input.
Custom conversation flows
More often than not, a customer will not provide a chatbot with enough information for it to fulfill a query. When this happens, the bot can use a custom conversation flow to ask for the information it needs to provide a solution.
When processing a query, chatbots can send or receive information to and from multiple internal or third-party systems. Chatbots can provide users with a friendly interface to multiple systems.
Information like user details, device, previous communication, and data leveraged from other systems can provide the bot with the context it needs to make better decisions. Bot designers can use this data to manually design conversation flows. Likewise, the AI can learn what to do or say in the appropriate context.
A chatbot is capable of taking action based on the conversation at hand. It is able to produce digital widgets, graphics on a screen, or similar interactions. It can communicate with internal or third-party systems for this purpose.
The best customer service chatbots will have some of the features mentioned above. These operate in narrow topic domains where they have a very high probability to respond usefully to every customer query. This way, they are capable of offering the best customer service experience.
The most reliable way of creating a customer service chatbot is to make use of a chatbot building platform. With the right platform, chatbots are simpler to deploy and integrate with other systems. Additionally, chatbot building software contains several features that make building conversational AIs faster and easier.
Companies considering implementing a chatbot must assess the economic impact of their chatbot solution. Likewise, they must also consider if and how the chatbot will integrate with their existing systems and processes.
Customer service processes will change once AI chatbots for customer service are deployed. Since the response times of chatbots are instantaneous, companies can introduce new processes that would be impossible with a purely human workforce. Chatbots are useful customer service tools for both customers and human agents.
For example, an agent for an airline company working with a customer over the phone can forego loading up the booking system and instead rely on a chatbot. By simply asking the bot “bring me to the last booking”, the bot can either look at the correct screen or just give the agent the requested information. In the future, both the agent and the customer will be able to interact with the booking system using a chat software solution where they may see the results.
The capabilities of a chatbot are determined by its complexity. A chatbot designed to provide information may only be able to access pre-recorded data when solving customer queries. In contrast, a more powerful chatbot can read through vast volumes of data and use NLP techniques to offer fluid and comprehensive answers.
A chatbot’s design is just as important as the technology platform used to design it. A simple but succinct, intuitive, and well-designed chatbot will function much better than a complex chatbot that has been poorly designed. Since a chatbot will be responsible for handling most customer interactions, it is important for them to be as refined as possible.
Empower your business’s customer service capabilities with Botpress. When working together with Botpress’s chatbot building solution, you can create chatbots with a state-of-the-art platform that enables the best design practices. Botpress allows companies and entrepreneurs to build conversational AIs faster than other platforms while providing all the tools needed to design customizable conversational experiences.
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