Facebook recently released a host of data proving the value of chatbots for business:
The utilisation of chatbots has certainly gained momentum in the last few years. With artificial intelligence (AI), it has made chatbots more lifelike than ever before. However, to maximize the ability of AI chatbots to improve service, save money and increase engagement, businesses and organisations need to first understand how these programs work, and what they can do.
In essence, chatbots must understand the intent of the user. There is a need to infuse intelligent quotient into the bot. For instance, if a user asks for a suggestion as to the best place to eat, the chatbot must first understand what the user wants, then provide a proper response.
While building a chatbot, two perspectives come into the picture when talking about best practices – practices for making bot development a success, and practices for assuring a seamless conversation with the user. It is thus important to know the target audience and also to identify use case scenarios, the chatbot development platform, determine how to initiate a conversation, and the tone of the chat, among other requisites.
Chatbot development comes with a unique set of requirements and considerations with a process that follows a pattern similar to the development of a web page or a mobile app.
Design. The chatbot design is the process that defines the interaction between the user and the chatbot. The chatbot designer will define the chatbot personality, the questions that will be asked to the users, and the overall interaction. An important part of the chatbot design is also centered around real world user testing that gives useful feedback for the iterative process of refining the chatbot.
Building. The process of building a chatbot can be divided into 2 main tasks: understanding the user's intent, and producing the correct answer. The first task involves understanding the user input. The second task may involve different approaches, depending on the type of response that the chatbot will generate.
Analytics. The usage of the chatbot can be monitored in order to spot potential flaws or problems. It can also provide useful insights that can improve the final user experience.
Maintenance. To keep chatbots up to speed with changing company products and services, traditional chatbot development platforms require ongoing maintenance with constant manual input. This can either be in the form of an ongoing service provider, or for larger enterprises, in the form of an in-house chatbot training team. To reduce these costs, some start-ups are experimenting with AI to develop self-learning chatbots, particularly in Customer Service applications.
Chatbot development platforms. The process of building, testing and deploying chatbots can be done on cloud-based chatbot development platforms offered by cloud Platform as a Service (PaaS) providers such as Oracle Cloud Platform and IBM Watson. These cloud platforms provide Natural Language Processing, Artificial Intelligence and Mobile Backend as a Service for chatbot development.
APIs. There are many APIs available for building your own chatbots.
Malicious use. Malicious chatbots are frequently used to fill chat rooms with spam and advertisements by mimicking human behaviour and conversations or to entice people into revealing personal information, such as bank account numbers. They are commonly found on Yahoo! Messenger, Windows Live Messenger, AOL Instant Messenger and other instant messaging protocols.
Personalization. The welcome screen should tell the user about features of your chatbot. A user will feel more at home with your service if the chatbot is using his/her name for greeting and interaction.
Bot introduction. The user should be aware that s/he is interacting with a bot from the get-go, so it is a good idea to start with an introduction of the bot.
Chatbot design. A user is more likely to trust a well-designed bot.
Formatting. Use proper text formatting, high-quality links and high-resolution pictures in your chatbot replies.
Information. Ask users for all the information you require instead of asking repeat questions.
Reduce errors. Linking your chatbot with an NLP library can help in minimising grammatical errors.
The main challenge is in teaching a chatbot to understand the language of your customers. In every business, customers express themselves differently and each group of a target audience may speak in a particular way. That is why training a chatbot to understand correctly everything the user types requires continuous effort, using a large amount of data and bot re-training for continuous learning.
Trying to create your own company Chatbot may sound like an exciting endevour that you may want to undertake yourself. It may, however, prove as difficult and expensive as trying to build your own mobile app. Although chatbots do not require a uniquely designed interface, they are more complex than you might expect. The biggest challenge in successfully creating a highly-usable chatbot is getting it do what the user expects it to do. Your company may be better off engaging an experienced solutions provider committed to building, improving, training an maintaining the chatbot to more efficiently and cost-effectively meet your goals and get the results you are after.
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