Chatbots in 2018 and beyond

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With recent technological advancements in artificial intelligence (AI), neuro-linguistic programming, machine learning, internet of things (IoT) and web speech APIs, it is now possible to streamline interactions between computer and human languages more effectively. And with drastic improvements in speech recognition, especially in terms of native languages, chatbots’ performance in various applications can now be enhanced.

What does all this mean? According to a recent report by Grand View Research Inc., the chatbot market is expected to reach $1.25 billion by 2025, growing at a compound annual growth rate of 24.3 percent. Elsewhere, Gartner predicts that by 2021 more than half of enterprises will be spending more per year on the creation of bots and chatbots than on mobile app development.

What are chatbots, and what makes them so alluring?

Chatbots are services that allow humans to interact with machines using natural conversations. They’re programmable and are powered by rules and artificial intelligence to deliver services and content. Chatbots use speech recognition software that allows users to issue voice commands. And through the use of web speech APIs, users can integrate voice data into web apps.

Chatbots are no longer just a novelty in the customer engagement and experience space. Many global conglomerates are deploying chatbots in their core communication functions. In addition to external use cases, organizations are starting to understand how chatbots can also transform the way we access information at work. Chatbots are now essentially changing the way organizations operate, communicate, educate, access and share information across internal and external channels.

Organizations use chatbots in the workplace to streamline business processes, provide Human Resources and IT helpdesk support, analyze data and leverage blockchain ledger capabilities for payments.

Chatbots can act as virtual assistants, allowing users to focus on more value-oriented tasks. They can also help provide around-the-clock, on-demand customer support and automate many business-to-business activities, such as placing orders, paying for supplies, and requesting information about external products and services.

What about ease of use?

Internally, chatbots are now an integral part of strategy when building a digital workplace. They can be accessed remotely and can leverage messenger apps such as Facebook Messenger, Skype, WhatsApp and Twitter. Chatbots use these familiar communication platforms, backed by neuro-linguistic programming and advanced deep learning algorithm capabilities, to converse in natural language, ask questions, understand intent and seek clarifications.

This makes interactions with chatbots a relatively pleasant and productive experience for users. A good chatbot can engage in conversation, understand what a user is looking for and quickly respond with a satisfactory answer or solution.

There are two primary types of chatbots — those that are rules-based and those that are AI-based. Rule-based chatbots understand the inputs supplied based on predefined static scripts, but do not understand the intent or context of the conversation.

AI bots, on the other hand, can learn on their own, based on data made available to them. They use advanced deep learning functionalities such as automatic speech recognition (ASR) to convert speech to text and use natural language understanding (NLU) to recognize the intent of that text. This enables you to build applications with highly engaging user experiences and lifelike conversational interactions.

What are a few key points to remember when creating a chatbot?

When planning, designing and creating a chatbot, you need to consider:

  • Who is the target customer?
  • What problems will it address, and what are the existing solutions and new solutions to this problem?
  • How will they be positioned and differentiated?
  • How will we define the chatbot’s value proposition?
  • What is the bot’s persona, scope of knowledge and domain expertise?

While it is good for bots to have a personality that reflects the brand, it pays to remember that it is the ability of these chatbots to satisfy the users’ needs that will ultimately decide if it is successful. For that, the data on which the bots are trained and the deep learning algorithm that guides their neural networks are of critical importance.

Creating a chatbot has become much easier and more accessible now, thanks to the wide availability of several well-known software development kit platforms from companies such as Facebook, Microsoft, IBM, Amazon and from other sources.

Over 80% of businesses are expected to develop chatbots by 2021, bringing in an estimated $8 billion in annual savings. The field is wide open for learning and implementation. People are exploring the use of chatbots to foster innovation in all industries. UNICEF, for example, uses a bot called U-Report to collect data via preprepared polls and uses the feedback for policy formation. The organization started a collaborative project with the Liberian Ministry of Education after discovering disturbing practices in country’s education system. In real estate, the field is wide open for chatbots coupled with blockchains.

Gartner, meanwhile, has highlighted the growth of conversational platforms as a Top 10 strategic technological trend of 2018. The future web will be more conversational. So, perhaps this may be a good time for you to create your very own Alexa, Cortana or Siri.

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  1. […] jobs in the United States by 2020 and 30 percent of those jobs in the UK by 2030. Sophisticated chatbots that can credibly impersonate contact-center staff now deliver customer service in many industries […]

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  2. […] and least effective method for delivering customer satisfaction. Indeed, the cost per call for a chatbot is usually under one dollar whereas a CSR typically costs between $10 – $25 per […]

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