Chatbots are automated systems for replicating human behavior during communication through text or voice chats. Generally, businesses get lots of customer requests and queries on a daily basis, and handling all of them at once is a tedious task. So, for handling such a huge amount of requests on a daily basis chatbot is a viable option. Nowadays, many companies are deploying chatbots on their websites to communicate with their customers on a real-time basis.
One of the quote regarding future prospects of chatbot is shared below:
“80% of the business to customer communication is going to be done through bot messengers within next three to five years”
– MIKAEL YANG (MANYCHAT)
Some of interesting statistics regarding usage of chatbots are as follows:
- ● 60% of millennials say they have used chatbots. 70% of them say they had a positive experience. (Forbes)
- ● Virtual customer assistants help organizations reduce by 70% call, chat and email inquiries. (Gartner)
- ● 90% of businesses report recording large improvements in the speed of complaint resolution. (MIT Technology Review)
- ● 23% of customer service organizations are using AI chatbots. (Salesforce)
- ● 80% of customers who have used chatbots report the experience as positive. (Uberall)
- ● 65% of consumers feel comfortable handling an issue without a human agent. (Adweek)
- ● 82% of consumers claim that instant responses to their questions are very important when contacting brands. (Business 2 Community)
But the major challenge in using chatbots is that they are generally rule-based which gives the feeling of an automated bot and sometimes people don’t feel satisfied during their interaction. So, for simulating actual human behavior, many chatbot frameworks have been developed recently. In this post, we will discuss about top paid chatbot development frameworks on the basis of the level of imitating human behavior, their integration with different channels, ease of use, programming language support, and pricing.
Below is the summarized details of top paid chatbot development frameworks so that you can choose as per your needs.
Microsoft Bot Framework provides a set of services, tools, and SDKs that helps developers in building a rich conversational chatbot. Some of the key benefits of the frameworks are listed below:
1. It helps in creating a bot with the ability to speak, listen, understand, and learn from users with MS Azure Cognitive services.
2. It is very user friendly to the developers.
3. It also supports multiple languages which makes it a competing chatbot solution worldwide.
4. Another advantage of the framework is that its chatbot has the capability to understand speech using their machine learning-based speech to text service named LUIS
Microsoft bot framework is a viable option for you if you like to use Microsoft services as it provides integration with almost all of the Microsoft services such as Cortana, Skype, MS Teams, etc. Some of the downside of the framework is that developers have to choose either NodeJS or C# for development or customizing their chatbot and it requires too much coding even for building a basic functioning chatbot. Another drawback is that most of the robust features are available within Microsoft toolset. Apart from that Azure documentation regarding bot framework require improvements.
DialogFlow is the product of Google for building custom chatbot solutions. Its standard edition is free to use, but if you require to handle lots of queries on a daily basis then you have to switch to their paid plans. Following are the benefits of DialogFlow:
1. It’s chatbot solution supports both voice based and text based assistants
2. Very easy framework for developing chatbot, even beginners can build chatbot with ease
3. One of the best feature of dialogflow is that it offers 33 pre-built agents already trained on different knowledge domain for basic tasks means what you have to do is to customize it as per your needs.
4. It supports more than 20 languages all over the world
5. It offers sentiment analysis for every query raised by user. This is one of USPs of dialogflow
6. It provides small talk functionality which comes pre-programmed for basic remarks made in almost every conversation which helps in emulating autentic human interaction.
7. It also offers live analytics reports means once your chatbot is deployed you can see how your chatbot is performing.
8. It also supports Internet of Things (IOT) integration for home automation
Now, some of the drawbacks of dialogflow are that if you have a limited number of intents for a basic application then it’s a good solution but if you have a requirement of advanced application with larger number of intents and complex conversation flow then it will be messy which results in misunderstanding the user requests. Another drawback is that it has the limitation to handle synonyms and hyponyms which makes the life of developers too difficult it means you have to train the bot for almost all the common synonyms which is practically hectic and time consuming. Apart from that it only supports one webhook per project i.e., you cannot choose multiple webhooks on intent-by-intent basis. The major drawback of dialogflow is that it does not provide live customer support service even for enterprise edition means you have to fill out customer support ticket and wit for their response.
IBM Watson is the most popular chatbot framework as it offers advanced functionality and features for the developers like automated predictive analysis, tone analysis of the user query, visual recognition security, multiple language support etc. It also offers Watson Assistant GUI for non-technical business users for handling queries. One more interesting feature of Watson bot is that it doesn’t collect the data for building bot instead allows developers to use private cloud for storing data, hence maintaining confidentiality and data security. As far as pricing is concerned it comes with wide options like Standard, Plus, Premium and Deploy Anywhere.
The major drawback of watson assistant is that is bit expensive in comparison to Amazon Lex and Google’s Dialogflow. Apart from that its tutorials for building a bot are not appropriate.
Amazon Lex is the most advanced chatbot framework as it provides advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text. It is highly scalable due to integration with AWS Lambda. AWS Lamda is the most advanced server less computing platform as it offers full stack backend infrastructure and code. This gives developers time to focus solely on building the application instead of deployment part. It is the most cost effective chatbot solution as it provides a pay-as-you-go pricing model.
One of the drawbacks of Amazon Lex is that it only supports English language. Apart from that it has a critical process flow for integration with web which makes it quite complex in comparison to other bot frameworks. Another drawback is that its data preparation is also very complex task as mapping of intents and entities is somewhat very critical.
Botsify is the drag and drop chatbot building tool which makes it extremely easy for developers or even non-technical business users to build a bot for their customized needs. It also offers human agent handover feature means it allow you to transfer conversations to a human agent at any point in the chatbot-to-human conversation which is not available in any other bot framework. It also offers live chat support for any queries and doubts. It provides the facility of conversational forms means it can collect handful of information like name, address, email, mobile number of the user in the form of good looking forms. It also offers integration with multiple channels like slack, RSSfeed, Google sheets, website, google search etc.
Some of the drawbacks of Botsify are that it uses extremely basic NLP framework for building their chatbot which usually returns odd responses. Apart from that its chatbot builder gives lots of error messages which questions its capability. All in all Botsify is not a desired AI- powered chatbot framework as its just gives a feeling of auto response to some targeted keywords..
Pandorabots is a chatbot platform that enables users to create and publish chatbots on the internet, smartphone applications, and messaging apps such as LINE, Slack, WhatsApp, and Telegram AI-powered chatbots.The Pandorabots chatbot use AIML (artificial intelligence markup language) scripting language for building conversational bots. The major drawback is that it uses AIML scripting which is only used by Pandarobots and apart from that it is quite less accurate in comparison to other competitors in the market.
So, as we have discussed about paid chatbot frameworks and in almost all of the above discussed frameworks one common drawback is that you cannot fine tune internal model for customizing your bot i.e., you can only customize as per your needs and have to depend on its capability for the performance. So, if you want to take full control of the chatbot model in terms of fine tuning and don’t want to spend dollars on building chatbot solutions then you should move towards open source chatbot framework.
I hope this post will help you in choosing the appropriate chatbot framework as per your needs. In the next post, we will discuss some open source chatbot frameworks and will compare them with paid chatbot solutions in terms of functionality and capability.