What is a Chatbot? A Helpful Guide on the Future of Conversation

A brief non-technical overview of Chatbots

The Basics on Chatbots and Voicebots

A chatbot is software that simulates conversation with a goal of performing a task for a user. Chatbots are designed to process voice and text-based commands and perform predefined actions. Most use artificial intelligence to understand and respond to human dialogue but more simple bots rely on regex (regular expressions).

A user gains access to a virtual assistant over a messaging platform. The most familiar ones may already be in your home like Alexa or in your pocket like Siri. You can learn more about chatbots by reading our Chatbot Primer by downloading it here.

Why Now for Conversational Applications

Messaging is King

So far over 1 billion people use Facebook Messenger each month and they now have the ability to summon chatbots into their messaging experiences. From a usage perspective, in terms of daily average users time spent at least: Messaging apps > Social media.

  • Many view this as part of the natural digital evolution from Web to Social to Messaging.
  • In reality it is still really early — today the search term “chatbot” logs roughly 125,000–150,000 monthly searches. Among search topics that is tiny. But this is basically 2x the number of searches from just 6 months ago
  • Chatbots today, exist within mobile applications, on the web, and even through your phone’s SMS through text messages
  • When you consider all of the departments of the economy it can touch it can be a $40 billion market.
messaging overtakes social media in 2015 or the rise of conversational applications opportunity

Artificial Intelligence for the Masses

Platforms and Tools for Developers

Along side the rise of messaging and separate but just as powerful disruptive technology is gaining a second wind through the rise of new data infrastructure and the cloud. Today all companies can take advantage of artificial intelligence to reshape their businesses. No vertical will go untouched.

We can build unique solutions with the help of machine learning and natural language tools from Google, Microsoft, Facebook and IBM to create virtual assistants, chatbots and voicebots. Even more so a number of chatbot technologies and voice app development technologies have emerged to help agencies, businesses and entrepreneurs build their own solutions.

  • For natural language, a sub-sector of AI, you can find a deep dive on their services here, here, and here
  • Many of the unique machine learning algorithms have also been made available to the public. So today the only differentiators are tied to your ability to manipulate these models and the underlying data that you can supply for the models.
  • This is where most companies have a unique advantage over some of the tech giants. Its why these giants are so hungry to get you to use their data platforms for free (they want your data).
  • Developers who mature out of these solutions or don’t want to share their data can build their own intelligent solutions or bots using tools like this one.
AI related companies by founding from 2016 data for chatbots and voice applications

A New Channel for Business and Customer Support

Not Just for Marketing

Most businesses have a strategy for inbound customer telephone calls and more digital savvy companies have introduced solutions like Intercom to address real-time web traffic. But as the chart below demonstrates only a few have established a persistent scaleable messaging solution.

  • Messaging platforms give customers a direct connection to a business and they provide a channel for other stakeholders to get what they need
  • Chatbots for automating customer service, human resources, and sales for internal use or external purposes are natural extensions
  • This is why most companies will have more than one bot to meet purpose driven needs of their business
conversational applications and chatbots and voicebots are growing for customer support

Consumers Strongly Prefer Digital Interactions

To wrap this why now section up lets just look at whether people are truly ready for more digital engagement. From below its quite clear that the population prefers digital as the starting point for customer care interactions. Most consumers want a self-service option. The question from here is whether or not bots can deliver an experience that matches the expectations of users.

younger generations prefer on demand channels where chatbots and voice applications can serve them faster

What Can a Chatbot Do?

the future is conversation for chatbots and voice applications

Bots Help Businesses and People Today

A Few Use Cases:

use cases for chatbots and voice apps like for Amazon Alexa and Google Assistant

Bots in Customer Support are a Natural

Bots can Handle an Array of Customer Care Tasks

  • For today’s consumer, bot-based support is a logical use case
  • Customers have migrated toward self-service, preferring not to deal with human agents as the earlier chart demonstrates
  • In fact, 90% of consumers say they now expect brands and organizations to have a self-service option
  • Customers either want to solve their issue quickly on their own, or receive an immediate response
  • But these bots don’t have to be customer facing to create significant value for businesses
  • If you are curious about Customer Service Chatbots or Human Support Voice Applications you can contact us

Chatbot and Voicebot Building Blocks

The Interface for an Emerging Channel (not a technical discussion review)

At its core chatbots rely on a few components — many developers will also use bot frameworks but these are the core components from our perspective:

  • Dialog Management: Dialog scripting and content manager responsible for tagging and storing digital assets.
  • NLP: Core solution for processing language to understand user intent and context. Today most companies rely on commercial services from Microsoft, IBM and Google. From our work we’ve seen advanced bots developed on open source solutions.
  • Analytics: Data management layer used to instrument the bot. Essentially if you are trying to understand engagement a host of analytics tools have popped up to help you in the discovery process

The Visual Anatomy of a Bot

A Bot can Use a Host of Visual Features or None at All

The conversational interface for a bot can take many different forms. For example, below is just a sampling of the design elements available for a bot operating on a smartphone.

The messaging platform where the bot resides can impact the available visual features for the bot. Since most of the platforms are still developing — many aspect of visual anatomy or the features a user can interact with are changing

design elements for facebook messenger chatbot

But the different types of chatbots go beyond the phone.  Today, many people interact with Amazon Alexa, Google Assistant, and Apple’s Siri with their voice. Developing for these types of chatbots is different because oftentimes the visual cues you would have available to you in the mobile phone experience are not always available.

Under the Hood

In Short Chatbots read and react to user inputs

A user creates a query or prompt for the bot by interacting through a common messaging interface such as Facebook Messenger, the Web or a mobile app. The user’s query is received by the bot and parsed by the NLP (natural language processing) service to understand the user’s intent (myNLU is shown below — Watson or LUIS can also work).

The bot generates a response based on its internal logic or calls a back-end system for data. The user receives a response based on the content of the question via the messaging interface. While human conversations are typically far more robust, we have seen and developed many bots that can handle more nuanced conversations.

Go With the Flow

Designing a Bot Experience

In all candor designing a bot experience takes time and effort but this is just a brief overview on what we mean we suggest a bot flow. At Azumo we’ve developed several tools internally that aid our customers when they want to create a chatbot from Bot Flow which is a visual editor to a simple dialog management editor that any one can use. In fact, when we first started building chatbots and voice applications, we tied the flow of the chatbot to Google Sheets. We did that because it was just as easy as using some of the existing solutions for building a chatbot.

Below is a brief example: You want your bot to run a brief survey for inbound quote requests. Depending on a user’s answers to questions the bot can ask additional clarifying questions to serve the most appropriate “flow of information” to the user. Here is an example of the bot’s interactive flow with the user:

Reusable Components

Every chatbot is unique, and the overview above is just a sampling of what is available for companies seeking to get value from a chatbot. No matter where you begin in your bot journey the better option today is to keep your options open and components reusable. If you are trying to gauge your chatbot developer. Here are some of the keys to look for or questions to ask

  • An easy-to-use dialog management system that enables rapid scripting and updating
  • Ability to use custom NLP libraries to add keyword and soft understanding capabilities
  • Reliable cloud-hosted NLP service so you can own your data, affordably
  • Bot framework that tightly links to key messaging platforms
  • Bot-in-the-loop (“BitL”) functionality allowing non-developers to step in and out of conversations seamlessly

At Azumo, we build intelligent applications and chatbots. We are passionate about using new technologies to solve complex problems for customers around the globe. We are chatbot developers.

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