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Because of the rise in online brand-customer interactions, chatbots have become increasingly popular in recent years. Not only has the number of consumer queries increased, but they've also gotten more complicated. AI-powered chatbots are the ideal option for businesses that wish to meet these client demands 24 hours a day, seven days a week. It's less expensive and more efficient than recruiting more agents to deal with clients 24 hours a day, seven days a week.

Robotic Process Automation (RPA) and artificial intelligence (AI) enable chatbots to provide intuitive and seemingly natural responses to the most frequently asked questions by customers, making this technology a must-have for any company looking to provide a more exciting customer experience while reducing errors and inefficiencies caused by human agents.

What Does an RPA Do?

RPA bots can be built to do pre-defined activities such as quickly processing pre-provided data, recommending solutions, and, in some situations, actually starting the resolution process. The combination of RPA with chatbot technology is a big boon for finance and insurance organisations, in particular.

Customers can access all the information about their insurance policy by just mentioning their policy or claim number when engaging with RPA bots in the insurance domain, for example. It goes without saying that if you want to stay relevant and gain a competitive advantage, having your own chatbot is the way to go.

Let's look at the 6 most popular RPA tools in the business currently -

IBM Watson

A huge majority of businesses, over 60%, use IBM Watson to build their chatbots. This platform is built on a neural network which has the capability to understand dialogue and intention, thanks to its huge conversation capacity. It has many inbuilt developer tools like iOS SDK, Java SDK, and Node SDK. It supports two languages - English and Japanese. Using this platform you can create bots that are fully conversational, not just answering simple questions.

Such bots are capable of guiding customers through the different steps to complete certain processes. All the conversations with customers are stored by Watson, and become the 'notes'; customer data that can be analyzed at any time to gain deeper understanding of customer behavior and preference. This helps make the bot become more efficient in future interactions with customers.

Microsoft Bot

If you're looking for simple, cost-effective solutions to create bots that can answer common questions or that can be integrated with virtual assistants and enterprise software, this free platform from Microsoft could be your answer. It allows you to build bots on Azure or locally, and they can be seamlessly integrated with several messaging apps like Slack, Facebook, email, and so on.

The bot has the capability of seeing, hearing, and interpreting interactions with humans (customers) thanks to Microsoft Cognitive Services. In addition to understanding speech and voice modulation, Microsoft bots have the ability to recognize photographs, translate languages, recommend stuff, and even to regulate content.

Amazon Lex

Say hello to Alexa's brother! This platform makes use of almost the same technology for deep learning that Alexa does. Lex leverages natural language comprehension and automatic speech recognition to transform speech into text, and also to identify the intent, leading to the creation of a realistic conversation experience. Amazon Lex is ideal for developing bots for transactions, device control, information provision and enterprise productivity.

It has a very simple console, and is therefore easy to develop, test, and deploy your chatbot. It is a wholly managed service, and you can just scale as your business grows without worrying about adding more hardware or infrastructure. You also get both support and protection as it has inbuilt integration with the AWS platform.

Dialogflow

From search engine giant Google, Dialogflow is a chatbot tool that makes use of advanced natural language processing technology to provide excellent text and voice options. Services are available across 14 platforms with a single click, making it one of the simplest chatbots to deploy.

Dialgflow agents are integrated with client apps, and help to handle the conversation and direct its flow to make it appear natural to the customer at the other end. You can also build on top of these agents to develop a tailor-made interface, enabling the technology to scale and transform according to the demands of a business at a given time. However, this platform requires some serious coding skills, so we would advise you to go for this if you've got the chops in place already.

Oracle Chatbot

Intelligent bots from Oracle enable you to create a very natural interface for conversation. You can also integrate this across numerous messaging apps, websites, digital voice assistants and of course mobile apps. Oracle bots maintain conversational context through the combination of complex machine learning and intent detection.

They extend functionality of the back-end and provide a personalized experience, and they are easily scalable - so you need not worry about adding on expensive hardware to deliver enterprise solutions for your growing business. The Oracle bots have the capability to provide resolutions to external B2C issues as well as internal issues. Another advantage offered by this platform is the inbuilt analytics; this enables businesses to gain valuable insights into not only the customer behavior, but also the performance of the bot itself.

Facebook Wit.ai

Considering that this is a Facebook bot, it will be no surprise to you that it enables the development of apps that can respond to both spoken and written queries, as well as bots that are capable of interacting with actual people through messaging apps. Wit makes use of NLP to understand what users say, and extracts the necessary info to take the requisite action. Though it is most ideal for developing simple B2C bots, it has proved its mettle across various businesses for the creation of virtual assistants, as well as bots that need to be integrated with IBM services.