Chatbots have become very common nowadays, so common that it is now easier than ever to develop chatbots. Chatbots may differ in terms of quality, and not all chatbots will work the same. What is it that makes an artificial intelligence to be the most effective? Find out more about the essential qualities that a successful chatbot should have.
The most effective AI chatbots are useful for a reason.
Chatbots should be created with a specific goal in mind, and that purpose should be at the core of its functions. The most effective AI chatbots were typically created to help companies. There are many ways that an AI chatbot can help you, so let’s take a look at some examples.
Relieve Customer Service department
This is the most frequent use case for AI chatbots. They are used to help clients find answers on the internet rather than calling support for customers.
In fact one of the most annoying aspects of being a customer is having to wait for a long time in order to be able to contact customer support when you need answers to a minor problem. This tool allows clients to solve their problems online. The customer can then concentrate on more difficult issues and the customer service staff will be able to focus on solving the issue.
Help the HR department
Chatbots aimed at helping HR Departments are here to handle repetitive inquiries collaborators often face regarding HR issues, thereby reducing the burden on the HR team and allowing them to be free to concentrate on the human aspects of their work.
Typically, an HR chatbot will be able to address simple HR queries like an employee’s annual leave, for example, but not only. It could also be used to be a fantastic onboarding tool, become an internal communication channel communication, and act as a way for team members to manage shared resources such as setting up a meeting space, or even serve as an organizational binder for social gatherings, encouraging employees to talk about their hobbies or even a coffee break.
Supplement your Sales department
Chatbots can aid your sales team in two ways:
By helping qualifying leads so that your Sales Representatives can concentrate on leads that are mature enough and are getting to the bottom of the funnel, i.e. are in a position to convert.
Even better, you can let potential customers go through the entire sales cycle without having to talk to a human!
Answering questions regarding the product a web user is looking for This type of chatbot, often referred to a transactional chatbot, will assist in removing any doubts a customer might have, slowly guiding him down the route to conversion and eventually offering him the chance to make a transaction within the chatbot. It is possible to prompt matching products. This can lead to an upsell.
The most effective AI chatbots are built to serve a particular purpose. It could be freeing employees’ time or improving customer interaction. They can to make your customers and colleagues their lives easier, but they’re not much superior than any other site or app.
Technology used by the most effective AI chatbots
As I mentioned earlier, all chatbots are not made equal, particularly when it comes to the software they employ, and therefore the user experience they provide. Let’s explore this further.
Conversational AI chatbots with NLP technology
As discussed in a prior article about the difference between different types of bots, there is a big gap between button/menu-based chatbots that are the simplest bots that you can find in the market, keyword-based chatbots and the most elaborate type of bot, the artificial intelligence chatbot.
The chatbot is based on Natural Language Processing technology, which allows it to recognize the user’s queries, even if they’re not correctly spelled.
Integrations with platforms of third party platforms
You can see that the most popular AI chatbots are able to connect to third-party softwares for example, such as an HR or CRM platform as well as inventory management tools.
This feature allows the bot to access HR data to answer an employee’s query, customer history to help the customer with a specific question about his account, or to check availability of products for a sales chatbot. If you look at this final example, a bot for sales needs to have access to your inventory information in order to succeed.
Imagine you run an Shopify clothing website and a customer is looking for a size 10 red dress is available. The chatbot connects with your inventory database to determine category of products and the levels of stock. It informs the user of the available options in a single, quick chat.
Available on multiple channels
The world is now flooded with to get information in the touch of the button. Your chatbot needs to be available on various communication channels and social media platforms in order to meet this. Your platform must allow your bot to connect seamlessly across all channels. It must also be able to store details and context for seamless interactions. The bot should be able transmit that information to an agent in the best cases.
The ability to elevate a living agent
As with all things technological, even artificial intelligence chatbot have their limits, meaning that the bot isn’t able to respond to the user’s question.
It must be able to call back to an agent on the human side if needed. In order to make the process of escalating as easy as it can be it should be able to relay information about the conversation and other important information to the user in order that he doesn’t become annoyed by repeating the same thing.
Best AI chatbots’ design
While the designs aren’t endless in the realm of Artificial Intelligence Chatbot but you should be aware of this feature. A simple design and an intuitive interface can make your chatbot more appealing to users.
Now, you now have an idea of the many factors that determine the top AI chatbots that are available on the market. It is important to keep these in mind when designing your own chatbot.
If you’d prefer to take it further, our book will outline the essential elements to complete your AI chatbot project, starting from the thinking phase to the operational implementation.