What makes the best AI chatbot? Let’s find out!

Chatbots are known by various names, such as a conversational AI bot, AI assistant, virtual customer assistant, intelligent virtual assistant, digital assistant, conversational agent, virtual agent, conversational interface, and more.

In a nutshell, chatbots are software applications that allow companies to interact with their customers using various input methods such as voice, text, gesture, and touch, 24/7 365. One of the major driving forces for using chatbots is improving customer experience through increased engagement and fast and convenient personalized services.

As virtual assistants, chatbots offer several operational advantages over live chat or contact center agents. For customers, they eliminate the need to dig down through endless menus and options to get what they are looking for in a website. Customers can simply open the chatbot and ask for what they want, just like they talk to a live assistant, and get the right response, every time.

Therefore, chatbots are perfect for resolving customer service issues, troubleshooting common problems, account administration, and providing general advice.

Obviously, reduced costs are clearly a key incentive, but there are several other advantages given below in providing your customers with an intelligent automated self-service option.

  • Always On: A chatbot is available at your customers’ convenience over any number of different channels.
  • Fast: Chatbots are built to recognize, understand, and respond to specific queries and problems in seconds.
  • Accurate: Chatbots have incredible accuracy to reduce first-time call resolution rates.
  • Scalable: A chatbot can handle millions of conversations simultaneously, all to the same high standard.
  • Compliant: Chatbots ensure that legal requirements are never forgotten or the regulations aren’t accidentally breached.

To substantially improve and prove seamless customer experience, chatbots need intelligence. For this, enterprises should build a conversational AI chatbot platform that can deliver human-like conversations over any channel, in any language.

This post will discuss some of the top chatbot features to have while building the ultimate conversational AI chatbot platform.

1. Truly conversational

To initiate an intelligent conversation with the customers, the user interface needs to be as human-like and conversational as possible. The AI-based, conversational chatbot must understand the user’s intent, no matter how complex the sentence, and ask questions in return to remove ambiguity and to discover more about the user. The chatbots’ ability to correctly interpret the users’ queries and requests and their ability to provide helpful and informative responses are vital factors affecting customer service trust. A human-like style of communication just feels better, and therefore is beneficial to create trust. The chatbot also needs memory to reuse critical pieces of information throughout the conversation for context or personalization purposes and bring the conversation back on track when the user asks off-topic questions.

2. Hybrid

Most chatbot development tools today are either linguistic or machine learning models. They have their own drawbacks. Most chatbot development tools today are either linguistic or machine learning models. They have their own disadvantages. As far as the developer is concerned, machine learning systems work as a black-box that cannot function without massive amounts of perfectly curated training data, which most times only a few enterprises have. On the other hand, linguistic-based conversational systems require humans to craft the rules and responses, and cannot respond to what it doesn’t know.

A hybrid approach, meanwhile, combines both linguistic and machine learning models, allowing the enterprises to rapidly build their AI-based chatbot platform irrespective of their starting point – with or without data – and to subsequently use real-life inputs to optimize the application from day one. Besides, this ensures that the system maintains a consistent and correct personality and behavior aligned with business aims.

3. Hyper-personalization

Chatbots don’t need to impersonate humans to boost business outcomes and deliver superior experiences. Instead, they must quickly deliver responses that speak directly to customer needs and continuously learn so they can apply meaningful responses to these unique requirements over time. The focus is to enable more natural and human-like conversations with customers. This is a lofty goal, yet very much possible when combined with the promise of technologies like natural language processing (NLP) and data sources such as geo-location, purchase history, even time of day to personalize the conversation even further. The ability to hyper-personalized responses determines the quality of an AI-based chatbot and the customer experience it offers. The chatbot must build a relationship with the customers based on an awareness of their needs rather than providing generalized responses that it is trained to deliver.

4. Data ownership & analytics

Data is one of the critical considerations while building a chatbot platform. As part of their conversations, customers share vast amounts of data in everyday conversations that includes their individual preferences, views, opinions, inclinations, feelings, and more. This information is like gold for an organization since it can be used to feedback into the conversation to increase engagement, train and maintain the conversational AI chatbot interface; and analyzed to deliver actionable business insights.

A robust analytics module that can capture activities and events and represent them as dashboards and downloadable reports is, therefore, compulsory to know the performance, usability, and accuracy of the platform. Besides, it is so essential that enterprises maintain ownership of their data. Alongside data ownership, organizations should carefully consider the data analytics package being developed as part of the platform, including the flexibility to drill down through the data and understanding the context of conversations and their level of details.

5. Cross-platform

To be successful, chatbots need to be cross-platform compatible. Customers move more fluidly between channels in the digital world, and they cluster around different platforms and devices based on their interests and convenience. Therefore, they anticipate a uniform and consistent experience across different platforms and channels, including engagement devices (e.g., Amazon Echo and Google Home devices), messaging platforms (e.g., Facebook Messenger), the web, mobile, SMS, and email, and enable seamless access to customer services wherever, whenever, and however customers want to engage. So, it is essential that the chatbot delivers a smoother, more consistent customer experiences across all channels.

6. Data security

Data security is a critical part when dealing with regulatory frameworks and customers’ personal information. Chatbots are an entirely new category of software, and their unique, text-based user experience presents some unique challenges in chatbot deployments. Flexibility is essential in an AI chatbot platform to meet today’s customer needs, yet the primary concerns should be around safety and security procedures and data access. Companies should understand what policies and procedures are in place to protect their data, who has access to the data and how it’s encrypted since there may be “unknown unknowns” related to security and privacy.

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