Bots and Chatbots: the Future of Digital Marketing
Chatbots are some of the most exciting new tools in the user experience environment.
With the help of bots and chatbots, a company can automate the process of answering recurring customer questions, speeding up customer troubleshooting time, and reducing pressure on agents.
However, bots and chatbots are still relatively new concepts in the modern market. We are still discovering what this technology needs to do and change the CX space.
A bot is a program that automatically completes actions based on specific triggers and algorithms. A chatbot is a computer program designed to simulate human conversations. Users can communicate with these tools via a chat interface or with their voice, just as they talk to other people. A chatbot interprets the words a person gives them and in turn, provides a predefined answer.
Like most common applications, chatbots have an application layer, a database, a conversational user interface (CUI), and an API. Today there are three common types of chatbots:
- Rules-based chatbot: The most obvious option, these bots simply give a predefined answer to very specific questions
- Intelligent chatbot: These types of bots use machine learning or “ML” to learn from user requirements and information.
- Chatbot with AI: These bots combine the benefits of a rule-based robot with the power of intellectually neo-user problem-solving programs
There are three basic classification methods for starting a chatbot:
The first option is to create a robot that matches a certain pattern.
The robots that match the pattern classify the text and give answers based on the keywords they see. In match mode, the chatbot only knows the answers to the questions in its model.
The second option of creating today’s chatbots is the use of algorithms.
A unique table must be provided in the robot database for each type of question to obtain an accurate answer. M. The classic algorithm for NLP and text classification is National Bayes.
The last crucial method of a chatbot is the use of artificial neural networks.
These solutions allow robots to use links and context in data to calculate answers to questions. In an artificial neural network, each sentence of a robot is broken down into different worlds, and each word is used as the input of a neural network.
Over time, neural networks will become more powerful, helping the robot create more precise sets of responses for common queries.
Top three platforms for designing a proper chatbot :
1. Chattypeople
Chattypeople is the best platform for creating AI chatbots on Facebook with an integrated Facebook store. With Chattypeople you can quickly and easily create a Facebook message, no coding required. The simplicity of the platform makes it ideal for entrepreneurs and traders in smaller companies, while technology makes it suitable for business users. You can create a simple bot that answers customer service questions or integrate it with Shopify. ChattyPeople is where f-commerce and ai-commerce come together.
2. MEOKAY
MEOKAY is one of the best tools for creating a conversational Messenger bot. It makes it easy for skilled developers and non-developers to participate in creating a series of simple steps. Within minutes, you can create chat scenarios and build advanced chat dialogues. When you’re done, connect and launch your brand new chatbot.
3. Beep Boop
This is a hosting platform designed for developers who want to create applications specifically for Facebook Messenger and Slack. First set your code using Github, a popular platform for control and hosting services, and then enter it into Beep Boop to connect it to your Facebook Messenger or Slack app. Then the bots will be able to communicate with your customers via chat and real-time messaging.
Conclusion
Minimal human interference in the use of devices is the goal of our world of technology. Chatbots can reach out to a broad audience on messaging apps and be more effective than humans are. At the same time, they may develop into a capable information-gathering tool. They provide significant savings in the operation of customer service departments. With further development of AI and machine learning, somebody may not be capable of understanding whether he talks to a chatbot or a real-life agent.
