Chatbot Tech
Chatbot as a concept
A chatbot is artificial intelligence (AI) software that can simulate a conversation in natural language with a user via messaging apps, websites, mobile apps, or phones. The main motivation in chatbots is that people using the bot do not understand that they are talking to the computer and fulfill their wishes as if they were talking to an individual. Chatbots specially designed for companies to carry out their operations on a specific scenario and conditions. However, when thinking about chatbots, it should be noted that it is not a structure that only follows the rule flow sequential operations system. It is also worth emphasizing that chatbots based on NLP work with a deep artificial intelligence algorithm.
So why are chatbots so important?
For many companies, customer acquisition and maximum observation of the existing customer experience is one of the most important issues. If someone who was not your customer before can receive the most accurate guidance and information when they reach you, this will be one of the most important reasons for choosing you. Or, if your existing customers can get the most accurate and fast answers to their post-product support and questions, their satisfaction will increase, and parallel to this, customer loyalty to you will increase.
It is seen in the studies about the customer that the customers talk to a real individual and expect more flexible guidance. Therefore, one of the most important aspects of chatbot designs is to minimize the understanding that the other party is talking to a machine :)
When describing RPA and Chatbot technologies, I carefully avoid using the phrase “taking over manpower”. Because as I am actively making such designs, I can easily state that this type of design is needed to help us, not to eliminate human power. We should not be afraid of transferring this type of work to robots.
Chatbot types
We can list the most used chatbot types today as Word Based Chatbot, Rule-Based Chatbot, NLP (Natural Language Processing) Technology, and Chatbot with AI Infrastructure.
Word / Choice Based Chatbot
Chatbots developed based on word/selection do not contain natural language processing algorithms. This type of chatbots responds to the user over the rules written according to the entered words. These answers given to the user are pre-prepared, pre-prepared responses. It would not be right to call these types of chatbots primitive, in fact, chatbot designs are designed according to the needs. However, the operation, maintenance, design, and updating of word-based chatbots without NLP is very difficult; Because not every user can enter the sentence and word correctly, it is very difficult to give output according to the combination of each word. In fact, because of this problem, chatbots that include decision trees have been developed in the step of using chatbots based on selection more effectively.
Rule-Based Chatbot
As an upper version of word-based chatbots, rule-based chatbots are used. In rule-based chatbots, the rules are embedded in the chatbot with a tree structure and the chatbot responds to the users through this draft.
For example, Hipmunk application as rule-based Chatbot:
Hipmunk is a location-based platform that allows people to search for travel deals, and many users set up their services such as flights, hotels, and rental cars from this platform. “Hello, chatbots” created by Hipmunk can be easily integrated via Facebook, Skype, and Slack. Hipmunk proactively promotes and informs and also simplifies a comprehensive and exhausting process for users.
Chatbots with NLP
Everything we express (verbally or in writing) carries a large amount of information. The topic we choose, our style, our choice of words, everything adds some kind of information that can be interpreted and valued. Theoretically, we can use this information to understand and even predict human behavior.
Data generated from conversations, notifications, and even tweets are examples of unstructured data. Unstructured data does not fully fit the traditional row and column structure of relational databases and represents the vast majority of data found in the real world. It’s messy and also difficult to manipulate. Nowadays, it’s no longer about trying to interpret text or speech based on its keywords (the old-fashioned mechanical way), but about understanding the meaning behind those words (cognitive pathway). In this way, it is possible to detect speech patterns such as irony and even to analyze emotions.
Here in these studies, it is called NLP. Natural Language Processing, or NLP, is a field of artificial intelligence that gives machines the ability to read, understand and extract meaning from human languages.
In fact, the more effective the use of NLP, the more effective it will be to distinguish whether the person speaking is a robot or a human. Therefore, NLP is used in a chatbot :)
Actually, I have published articles about NLP and its techniques before :) But it is worth mentioning that technology is advancing rapidly in this direction.
So on which platform and how can we develop Chatbot?
In fact, there are many professional institutions dealing with Chatbot today. For this reason, these experienced companies prefer to benefit from the chatbot cloud structure. But you can even develop a chatbot in Python to gain knowledge and experience like me.
Chatbot Platforms
Watson Assistant
Offering solutions on artificial intelligence technologies, IBM is one of the most advanced artificial intelligence-supported chatbots in the market with its Watson Assistant product. Communicating directly with customers, IBM Watson records past chats and offers a more personalized chat experience for the next chat. In order to further customize the chat experience, Watson also directs more detailed questions to the customer.
AWS Chatbot
AWS Chatbot is an interactive chatbot tool that makes it easy to monitor and interact with our AWS resources in Slack channels and Amazon Chime chat rooms. With the AWS Chatbot, we can receive alerts, run commands to return defined information, call AWS Lambda functions, and create AWS support cases.
Bold360
Used by customers such as Intuit, Edible Arrangements, and Vodafone, Bold360 is a solution that can perceive customers’ expectations and give them the most accurate answers without the need for keyword matching. It also has its own natural language processing technology for more accurate answers
So are Alexa and Siri Chatbot?
Chatbot is a virtual assistant that can chat. Assistants such as Alexa and Siri are chatbots that can recognize voice and speech and respond by voice.
In my next article, I will share a detailed article explaining the working algorithm of Alexa and Siri.
I hope you read it with pleasure :)
