The 2019 Capgemini research institute’s report published after a research on the use of chat assistants showed a drastic 76% increase in customer satisfaction from organizations where chat assistants where built and incorporated into their services. But how does Dialogflow, a product from Google’s ecosystem, aid developers in building chat assistants and contribute to this quota?

Ever since ELIZA (the first Natural Language Processing computer program brought to life by Joseph Weizenbaum in 1964) was created in order to process user inputs and engage in further discussions based on the previous sentences, there has been an increased use of Natural Language Processing to extract key data from human interactions. One key application of Natural language processing has been in the creation of conversational chat assistants and voice assistants which are used in mobile and web applications to act as customer care agents attending to the virtual needs of customers.

In 2019, the Capgemini Research Institute released a report after conducting a survey on the impact which chat assistants had on users after being incorporated by organizations within their services. The key findings from this survey showed that many customers were highly satisfied with the level of engagement they got from these chat assistants and that the number of users who were embracing the use of these assistants was fast growing!

To quickly build a chat assistant, developers and organizations leverage SaaS products running on the cloud such as Dialogflow from Google, Watson Assistant from IBM, Azure Bot Service from Microsoft, and also Lex from Amazon to design the chat flow and then integrate the natural language processing enabled chat-bots offered from these services into their own service.

This article would be beneficial to developers interested in building conversational chat assistants using Dialogflow as it focuses on the Dialogflow itself as a Service and how chat assistants can be built using the Dialogflow console.

Note: Although the custom webhooks built within this article are well explained, a fair understanding of the JavaScript language is required as the webhooks were written using JavaScript.

Dialogflow

Dialogflow is a platform that simplifies the process of creating and designing a natural language processing conversational chat assistant which can accept voice or text data when being used either from the Dialogflow console or from an integrated web application.

To understand how Dialogflow simplifies the creation of a conversational chat assistant, we will use it to build a customer care agent for a food delivery service and see how the built chat assistant can be used to handle food orders and other requests of the service users.

Before we begin building, we need to understand some of the key terminologies used on Dialogflow. One of Dialogflow’s aim is to abstract away the complexities of building a Natural Language Processing application and provide a console where users can visually create, design, and train an AI-powered chatbot.

#chatbot #dialogflow #developer #machine-learning #artificial-intelligence