A chatbot is a kind of computer program that simulates the speech and correspondence behaviors of a living person using predefined settings. Eliza, the first of the kind, was created back in 1966 to simulate the activities of a psychologist. Eliza emulated the method of active listening by repeating phrases like “Please, continue” from time to time. Modern chatbots are more like virtual toys. You can conduct comical dialogues with them and use them as advanced search engines.
Nevertheless, the most rational of such programs are used for support purposes. Probably everyone today encounters contact dialog boxes on business sites. Such software helps ensuring instant interaction with the clients who apply for help (most often applied to financial institutions’ websites) and are called upon to solve the most frequently encountered problems without the need to take time away from real employees. What does the implementation of chatbot provide in practice? First and foremost, it entails a qualitatively new level of service, more productive work with the client base, improvement in sales, acceleration of the user interaction process, and, as a consequence, a reduction in purchase time.
What does a chatbot operate on?
In general, a chatbot is a primitive interpretation of an artificial intelligence assistant. The program is a sort of semantic analyzer that parses user input and finds answers in the attached knowledge base. This procedure can be carried out either through keyword, phrase (taking into account the order of words) or context recognition or, in more complex forms, through self-learning algorithms and virtual neural network systems (such as Watson, Deep Blue, api.ai, etc.).
The simplest can be created in a matter of hours. In turn, an artificial intelligence chatbot will take some time. As for the "lightweight" chatbot versions, you must consider whether it really would be helpful to users and convenient in interaction. The functions of many support assistants entail a multi-stage task implementation scheme (as it happens, for example, with the abovementioned financial sites). Developing such a complex function in just a few hours is close to impossible.
How to develop a chatbot: 7 steps
1. Determine the target audience and required functionality
Sometimes, the initial view of artificial helper’s capabilities differs greatly from the released product. That is why, as we’ve previously mentioned, it is important to determine who will use the chatbot and what kinds of tasks it should perform, before choosing the appropriate tool for chatbot creation.
Suppose we are talking about a simple online store with a small assortment of product. In this case, you probably do not need a complex chatbot based on machine learning. In turn, stand-alone applications (for example, the popular pBot for iOS or roBot for Android) need a more thorough approach, employing the use of self-learning mechanisms.
2. Choose the tools (platforms)
This point should be more interesting for developers, rather than owners of commercial ideas already operating business organizations, or for startups. The knowledge of the applicable tools will help to understand the principles behind development of such programs. Below is a list of the most popular platforms for chatbot creation.
- IBM Watson. Watson is a complex architecture platform that does not require knowledge of code, and was originally intended to build artificial intelligence based software solutions. Developed using Java, C ++ and Prolog, this system offers an incredibly convenient graphical interface for the organization of the machine learning processes and construction of logic chains in streaming dialogs. Watson has a single distinctive feature. It employs not the complex logical operations (which, due to the unpredictability of interactive user interactions, can lead to erroneous and illogical responses) but high-performance multitasking. Characterized by extreme efficiency, IBM Watson simultaneously implements multiple algorithms for the examination of user input with the help of a high number of validation parameters.
- Telegram. To build a chatbot for Telegram, you will need the Botfather bot, which will create a new application in the shortest possible time. This bot uses the Python development language (although Java, PHP, and Ruby are also suitable for this purpose) and, accordingly, pyTelegramBotAPI. What else might a bot developer need? A basic knowledge of Linux shell, MacOS Terminal or Windows Command Prompt, as well as SQL knowledge.
- Pandorabots. The integrable Pandorabots platform is designed for the development of complex software solutions based on self-learning algorithms and virtual neural networks. AlaaS (Artificial Intelligence as a Service) specialized tool, which is a part of this platform, allows for the creation of highly intelligent software solutions. The support for Java, Ruby, Go, PHP, Python, and Node.js provides abilities to interact with I/O devices through APIs and connect external libraries and additional functionality modules.
- Motion.ai. Motion.ai is an incredibly simple and intuitive tool for the creation of chatbots that requires no programming skills and is among the best for beginners. In particular, the development of a simple interactive module will take no more than an hour. In order to build a bot, you just need to construct a flowchart that describes the stages of the user dialogue using a WISYWIG editor. In addition, the ability to compile the Node.js code directly helps to integrate Motion.ai projects with any API.
- Facebook Messenger. Facebook Messenger is a popular platform used by many chatbot developers. To create a chatbot for Facebook Messenger, you will also need the machine learning systemsWit.ai, Send/Receive API, Node.js, and Google App Engine.
We should note that, to decide how to build bots for Messenger, you will also need some knowledge of JavaScript. Despite the apparent complexity, working with Facebook Messenger is justified. The abundance of plugins, as well as the carefully thought-out functionality for the conversion of user-entered information into structured data, open up truly vast opportunities for developers, helping to build a new chatbot for Messenger from scratch in a relatively short period of time.
3. Create the necessary interface attributes for the future chatbot
A really qualitative assistant should have the following interface attributes:
- Short greeting, containing the basic pleasantries and the list of problems which it can assist in resolving.
- Menu or a list of links leading to ready solutions for the most trivial tasks.
- Means for connection with real employees.
4. Provide a maximally comprehensive user interaction
In order to increase the productivity of the user's interaction with the chatbot, it is necessary to provide some indirect mechanisms that can guide the activity of a user to the desired area. These include:
Source: https://dribbble.com/shots/2749390-Messenger-Bots-Partial-payment-Concept
(By https://dribbble.com/isiluzum)
- Pop-up hints (for example, when a user asks a question, they are immediately offered a drop-down menu with a list of answers containing the mentioned keywords or phrases).
- Clarification of the subsequent actions (for this, suggestive context-sensitive questions are used).
- Input confirmation (if the solution of the task in question involves several stages, it is necessary to clarify the correctness of the input of previously provided data on each of them).
- Synonyms and misprint processing (users do not always correctly enter their requests and, moreover, the abundance of synonyms in their requests can put the assistant into a deadlock, so programmers often resort to using normalizers like this one: https://github.com/superscriptjs/normalizer).
- Step-by-step information presentation (it is not necessary to display all the information right away if the answer to the question is volumetric enough. The "correct" chatbot should use short words and phrases, consistently presenting the answers found in the database).
5. Create a basic collection of answers to the most frequently asked questions
It does not matter why you make a chatbot - to optimize the progress of your main commercial product or as a stand-alone software. Regardless, you still require a list of standard questions (possibly with a variable word arrangement or usage of synonyms), the answers to which can be determined in advance.
This approach will make your program’s operation more predictable. Note also that for bots, dialogues which allow for informal communication should also include some humorous answers.
6. Polish the functionality to make the bot work correctly
The ultimate goal of chatbots, created to improve the quality of customer service, is providing the right answers and solutions and the most efficient user interaction.
To do this, it is necessary to refine the user interface, and, in particular:
- Reduce the size of input fields to reasonable minimums;
- Create a convenient navigation menu;
- Exclude the use of pronouns when addressing the user; and,
- Provide an opportunity to contact live staff (in case the bot cannot solve the proposed problem).
7. Conduct extensive testing of the bot’s operation with your questions
When the chatbot is finished, it must be tested fully. What kind of questions must you ask to understand how much its activity will be useful within your site? Let us review in detail.
- Standard questions. Sometimes a chatbot "misfires" with the most simple questions, which contain a minimum of words and are responsible for the basic set of services for your business. The reason for the incorrect operation may be a non-standard word order or the saturation of the sentence with pronouns.
Source: https://dribbble.com/shots/2822934-Messenger-Bots-Augmented-Video-Call-Concept
(By https://dribbble.com/isiluzum)
- Complex questions that contain several conditions. Sometimes, chatbots collapse when faced with questions like "How to repay the loan so that no interest would be accrued for its use?" To do this, you need to create a clear mechanism for finding answers, implying the consolidation of several conditions at once.
- Mutually exclusive questions. Many chatbots are stumbled by questions like "either ... or ...". Some of these suggest a disjunction (when the answer to the question would be "both"), and some are mutually exclusive (when only one component of the question can be true).
- Questions arising from the previous dialogue. Test your program with questions related to the information obtained in dialogue earlier. If the chatbot cannot follow up on such questions and answer them correctly, it means that the contextual dependence is planned poorly.
- Illogical questions. In chatbot development, it is also important to work out all exceptional situations when the questions are formed incorrectly or do not belong to the subject area of the created program.
- Loebner Prize questions. If your chatbot is created for in-depth communication with users (in particular, for entertainment purposes), test it with questions proposed at the oldest Turing Test contest - Loebner Award.
Future prospects
What are the most promising prospects for further chatbot development? First of all, it is still the highly experimental technology of neural networks. Many IT experts reasonably suggest that technologies currently used to create advanced artificial intelligence assistants will, in the near future, become more easily accessible and extend to chatbot development.
A major feature of these algorithms is answer forecasting capabilities. Such chatbots will automatically "sharpen" their behavior when interacting with a specific user. This can be explained by the principle of neural networks operation. Remembering the previous stages of dialogue with a specific user, neural network based chatbots will be able to alter further responses, taking into account the subtle specifics of the manner in which its living interlocutor communicates. Strictly speaking, the context capture is the main characteristic that differs chatbots with embedded artificial intelligence from most of the existing analogs.
These technologies are still far from perfection, however. Active users of existing artificial intelligence assistants have noted repeatedly the cases of incorrect and out-of-context responses. In a recently conducted study, 5000 questions in different areas were asked from the most popular assistants, with the following resulting statistics:
To date, technologies associated with neural networks are not perfect, so using them to create chatbots designed to communicate with business customers is not the most reasonable solution; however, we hope that, in the very near future, the neural networks’ principles of operation will be perfected, and the development of advanced chatbots will require far fewer developer interferences.
Summary
A chatbot is a very useful component of any website; however, insufficiently impletmented functionality and tools for user interaction can create a disrepute to the online service and mislead your customers. Therefore, before starting the designing process, it is important not only to carefully follow the above tips, but also to test its performance and correctness of operation. Only in this case, will the chatbot benefit your company.
The cost of chatbot development can vary depending on the complexity of the task. Sometimes, a simple chatbot in design may require the implementation of virtual neural network technologies, and work on this platform may take several months.
Our company offers software development outsourcing services, including those for various profile chatbots. All of them are carefully tested after creation, so we can guarantee with assurance the quality and correctness of our solutions. Note that it is very difficult to accurately calculate chatbot development costs. You can request a quote today and learn more about the price of a final product after discussing the details with our project manager.