Responsive and prompt customer service ensures the satisfaction of your website visitors or your mobile app users. They expect all their answers to be found in one place and don’t wish to navigate through a maze of links and menus.
In the past, live agents at customer support centers have acted as the one-stop point of contact for companies and that largely remains true today. This service, however, is increasingly augmented by IVRS systems that divert the calls to a dedicated team of agents. Online live chat also provides the same services, but in a more cost-effective way as a single agent can simultaneously handle multiple incoming requests.
Moreover further reduce costs, increase responsiveness, provide round-the-clock and multilingual services, companies are integrating AI-enabled chatbots with their websites and apps.
- Operate 24/7 with very little overhead cost.
- Guide users to the immediate information they need
- Provide customer service from tracking queries to taking bookings, payments and scheduling appointments
- Conduct customer surveys
- Answer their questions
- Automate the user’s request with backend systems such as a CRM system.
Since the COVID era, Chatbots have become an integral part of modern and effective digital communications strategy.
Designing an AI-enabled chatbot is no longer a challenging task because of the availability of many programmer-friendly languages and tools.
When you design a chatbot, there are some key points you need to keep in mind:
- Understand your target audience
- Access the best dataset for the target natural language
- Comprehend the sentiments of the end-users in a proper way
- Formulate appropriate responses
- It should support advanced UI features
Finding the right chatbot development language can be tricky, as there are too many options available. Each language has its own set of features, advantages, and limitations.
If you are about to design a chatbot and don’t know which programming language to choose, this blog is surely for you. Here are the top 5 programming languages for chatbot development:
Python has a minimalistic framework, boasts simple syntax and has the support of the most advanced AI libraries.
It is easier for developers to define strategic roadmaps for the chatbots to take under different scenarios. Python’s ability to develop throw-away prototypes helps zero in on the final specifications early and refined iterations of the accepted prototype.
It facilitates dynamic, high-level, modular, and interactive code that integrates seamlessly with AIML (or Artificial Intelligence Markup Language). The research in other areas of artificial intelligence and machine learning in Python enriches its library.
· Quick development time
· Support for throw-away prototyping
· Interactive development
· Modular and dynamic code
· Support for NLP in many languages
· Versatile language with very simple syntax.
· Integration with other AI and Data Analytics needs of the website easier
· Supported on all major platforms
Clojure is a functional and modern dialect of Lisp used for general-purpose programming. As Java is its primary platform, it can access frameworks built for Java as well as ECMAScript and .NET.
When you access Java frameworks running on the JVM, Clojure empowers you to create code in the form of multiple functions, a robust macro system, and a code-as-data viewpoint.
With its reactive agent and transaction memory system, you get an error-free, clean, and multi-threaded design and code. It allows using higher-order recursive functions to replace looping having side-effects.
· It allows the writing of clean and error-free code.
· It is multi-threaded, so the chatbot system can handle many queries at the same time.
· Clojure has a transactional memory system and a reactive agent system.
· Easy to use due to availability of higher-order recursive functions
Ruby is another powerful open-source language to make your job of building an efficient Chatbot system effortless and easy. It looks very similar to Python in its syntax. It supports dynamic programming, where the code can adapt at run-time to accommodate the system’s changing needs and has an automatic memory mechanism.
The adaptability makes it ideal for any chatbot development company to build AI-enabled chatbots. Writing code for chatbots using Ruby might be a bit costly as need its license.Its framework comes with many tools and a library for building sophisticated chatbots.
· Robust and rich library
· Superb performance due to optimized opcode
· Clean and precise syntax
Lisp is the second-oldest high-level programming language, developed in 1958, still being used extensively. It has undergone multiple layers of evolution to emerge in its modern, highly efficient, and dynamic avatar.
Lisp has been used in the development of intelligent systems since its early days. Therefore, it is being used in many AI projects, including the smart and responsive Chatbots.
The throw-away modeling and prototyping are used extensively in chatbot training, designing, and developing multilingual abilities. Programs written in Lisp can process symbolic information relatively quickly with the help from its rich library.
Additional dynamic features like interactive expression evaluation while development and file recompilation are going on during a running program make it a desirable language for chatbot training.
· Dynamic prototyping capabilities
· Processing of symbolic information intelligently
· Adaptive to specific issues
Java has become the default choice for many programmers, given its clean syntax, strongly typed type-system, high-performance, functional support, rich library, and easy integration with existing systems.
It is an Object-Oriented Programming language that is platform-independent and portable. The JVM memory footprint is so small that it can easily fit even a mobile SIM chip.Its features like multi-threaded support and automatic garbage collection are added advantages.
Learning and in Java is extremely easy and many students are taught this language at high-school level as their first programming language. It is therefore provided with one of the largest populations of programmers proficient in any language.
· Highly scalable.
· Inbuilt garbage collection
· Platform independent and portable
· Small memory footprint
· Very rich library and third-party support
· Java is excellent for easily coding algorithms with advanced features.
Finding the right fit
All the programming languages discussed above have a proven record of developing intelligent systems, including sophisticated and powerful AI Chatbots. However, not every language may fit your specific needs or may have tools to support your vision.
As discussed in the beginning, listing all the essential requirements, constraints, and features needed for the platform beforehand is a better way to find the right fit. Do you need the chatbot delivered quickly? Do you need advanced capabilities, like multiple scenario processing, in it? Or Do you want it to support various natural languages?
Answers to these questions will affect your choice of the programming language for chatbot development.
One crucial factor you cannot ignore is the familiarity of your developers with one of the options. Or their ability to quickly learn and switch to a better option.
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