We, in G-particle, understand your business and industry well, and we know the main drivers of your industry.

Using our unique consulting methodology, we jointly identify those areas of improvement, which have a higher and immediate impact on the market and business growth. There might be a possibility to address the designated areas by using custom made and intelligent chatbots; in such cases, we will offer a unique solution to improve your business productivity.

What is a Chatbot

Also known as Chatter-Bot or Chat Robot, a ChatBot is a computer software program designed to simulate a human-like conversation with its users through either text, image, or voice. For instance, a text ChatBot would require an Instant Messaging Engine, while a voice ChatBot would need a voice recognition engine.

A report suggests that the usage of Messaging Apps has surpassed the usage of social networks. Another research indicates that people, these days, prefer to chat over talk. This preference has created a need for businesses to start building their presence on the messaging platforms, as well. A ChatBot can work on multiple platforms, such as Emails, WhatsApp, Facebook Messenger, SMS, Telephone, or Websites. Click here to try sending a message to the CNN chatbot on Facebook Messenger.

Although Chatbot technology is still far from passing the Turing test, it is increasingly gaining popularity in B-2-B and B-2-C environments.

Companies use chatbots to handle simple and complex routine look-up tasks with tremendous processing speed. This helps businesses make the most productive utilization of their staff’s time.

Gartner predicts that by 2021, 15% of all customer service interactions globally will be handled entirely by AI, an increase of 400% from 2017. However, before then, by 2020, 40% of the bot virtual assistant applications launched in 2018 would have been abandoned as technology-adoption converges on fewer apps.

Thanks to Facebook Messenger, WhatsApp, Kik, and Slack that have played a significant role in this growth.

Best practices

There are mainly two types of dialogs that are used in a chatbot’s  conversations

Guided through: In this type, users are provided with static options to choose from.

Open dialogs: Open dialogs are much more complicated in terms of simulating human-like conversations. In this type, the bot uses AI techniques to identify the user intent and its corresponding attributes. And then based on the identified intent and entities, the bot will decide how and what to respond to the user

Regardless of dialog types, a well-designed chatbot is expected to catch the user’s attention and engagement. Chatbots hope that their users prefer such experience over alternative methods like apps, websites, phone calls, etc. The competition between the bots and all other alternative options is about how fast and comprehensive the user request has been responded and addressed

According to Microsoft as one of the market leaders, a bot may not be successful in the mentioned competition by being smarter or maximizing NLP usage.

Smartness: There is no correlation between the intelligence of a bot and its user adoption. According to Microsoft in reality, many bots have little advanced machine learning or natural language capabilities. A bot may include those capabilities if they’re necessary to solve the problems that it’s designed to address.

Usage of NLP: The primary purpose of a bot is to address the user request. Hence it is essential that how fast and comprehensive such goal is met. According to Microsoft, a bot may have a vast vocabulary and can even make great jokes. But unless it addresses the need, such capabilities may contribute very little to making it successful. Some bots have no conversational capacity at all. And in many cases, that’s perfectly fine.

Voice recognition: although it is a dream if we could talk and they would execute, however with current technology limitations it may result in user frustration

No defined rule states, what makes a bot successful, yet following factors contribute to better user experience vs. alternative options

  • How fast a bot can solve the user problem
  • How easy a user understand how and when to use the bot
  • Is the bot intelligent enough to advise certain things proactively

Why Chatbot

People across the globe use different kinds of online methods to do business. It includes organizations of every size and every industry. Portals, business websites, hosted applications, and social platforms such as webchat, telegram, Instagram, are some of the methods used by the people for this purpose.

State of chatbot reports 2018 identifies the common problems that users face while using such applications.

Initially, the chatbots are meant to improve businesses by addressing the problems mentioned above. The usage of such bots is proliferating. However, the combination of recent technologies such as chatbot, machine learning, big data, and analytics creates a unique proposition to organizations to improve their productivity from different aspects.

Chatbots can be much closer to users compared to traditional GUIs as they can identify the real intent of users much faster and more accurate compared to conventional GUIs. The integration of machine learning with chatbots makes them intelligent, so a bot starts learning from its past experiences, and it makes it more and more personalized to the user demand and expectations.

Integration of chatbot with various applications, big data, and IOT will empower chatbot to execute more complicated expectations, below are the use cases for chatbot predicted by State of chatbot reports 2018, however, innovative use cases which are matched to the exact need of an organization can be far better of what is listed below.

Some of the general features of our chatbot framework

  • Channel-independent framework

    Our framework covers most of the leading messaging platform available in the market

    • Webchat
    • Facebook Messenger
    • Telegram
    • Skype
    • Line
    • What’s app
    • SMS
    • Email
    • Custom mobile app
  • Multi-language support

    • The communication in Guided conversation can be in any languages supported by the messaging platform
    • In the case of using open conversation approach, the ability of understanding a language is limited to the strength of NLP engine which interprets the message, our framework is already integrated with two of leading NLP engines MS LUIS and IBM Watson, each of these engine having their pros and cons, for example as of now MS Luis doesn’t support Arabic, but IBM Watson does.
  • Cloud-based solution

    Our framework can be installed on MS Azure, AWS or IBM cloud