Intelligent Customer Help Desk with Smart Document Understanding

INTRODUCTION

Overview

We will be designing an application that leverages multiple Watson Airservices (Discovery, Assistant, Cloud function, and Node Red). By the end of the project, we’ll learn best practices of combining Watson services, and how they can be used to build interactive information retrieval systems with

Discovery + Assistant.

  • Project Requirements: Python, IBM Cloud, IBM Watson
  • Functional Requirements: IBM Cloud
  • Technical Requirements: AI, ML, WATSON AI, PYTHON
  • Software Requirements: Watson assistant, Watson

Scope of Work

  • Create a customer care dialog skill in Watson Assistant
  • Use Smart Document Understanding to build an enhanced Watson Discovery collection
  • Create an IBM Cloud Functions web action that allows Watson Assistant to post queries to Watson Discovery

Proposed solution

For the above problem, we are able to put a virtual agent in the chatbot so it can understand the queries that are posted by customers. The virtual agent should train from some insight records-based company background so it can answer queries supported by the merchandise or associated with the company. In other words, some styles of manual will be accustomed to training the bot using AI. Here I’m using Watson Discovery as a tool for implementing AI and getting trained by the owner’s manual.

THEORETICAL ANALYSIS

Block/Flow Diagram

Hardware / Software Designing

  1. Create IBM Cloud services
  2. Configure Watson Discovery
  3. Create IBM Cloud Functions action
  4. Configure Watson Assistant
  5. Create flow and configure the node
  6. Deploy and run Node-Red app

EXPERIMENTAL INVESTIGATIONS

Create IBM Cloud services

Create the following services:

  • Watson Discovery
  • Watson Assistant
  • IBM cloud function
  • Node-Red

Advantages

  • Companies can deploy chatbots to rectify simple and general human queries.
  • Reduces manpower
  • Cost efficient
  • No need to divert calls to customer agents and customer agents can look at other

Disadvantages:

  • Sometimes chatbots can mislead customers
  • Giving the same answer for different sentiments.
  • Sometimes cannot connect to customer sentiments and intentions

APPLICATIONS

  • It can deploy in popular social media applications like Facebook, slack, and telegram.
  • A chatbot can deploy any website to clarify basic doubts of viewer

CONCLUSION

By doing the above procedure and all we successfully created an Intelligent help desk smart chatbot using Watson assistant, Watson discovery,

Node-RED and cloud functions.

FUTURE SCOPE

We can include Watson studio text-to-speech and speech-to-text services to access the chatbot hands-free. This is one of the future scopes of this project.

Development of Online Shopping Bot using IBM Watson

Introduction

Overview

Online shopping plays a great role in the modern business environment. The best option available for customers in pandemic situations is to use chatbots for online shopping. To support customers in a better way, online shopping bot has opened a door of opportunity and advantage to the firms and customers for having a feel of buying items in a better way. The bot helps to introduce the online shop by listing the items available; it also shows the price of the items and takes orders from the customer. If the customer wishes to see the items, the bot also provides images of the items. This facility ensures the customer sees the products live and gives requests to buy items.

Block Diagram:

Flow Chart Diagram:

Purpose

The online shop bot can help the customer to see the list of items available, images of the images, and the price of the items, and also accepts orders for the items. The purpose of this bot is to save valuable time and money on travel.

  • Literature Survey

In this section, we will discuss the existing solutions available for online shopping and the proposed solution to overcome the limitations.

  • Existing Problems and Solutions

In the past decade, people use the internet as a daily service to access emails, perform online tasks, do shopping, etc. Naturally, people have widely started using the internet at shopper stops too. This showed their willingness to do online shopping. This brings huge responsibility to the shop owners to keep up the buyer’s faith in the particular website. The most important points that affect the customer attitude towards online shopping are customer convenience, collection of information, social contact, and customer diversity.

There are several websites available currently to handle online shopping like Amazon, Flipkart, Big Bazaar, etc. Kotler, (2003) has described the Customer buying method in several sequential steps namely learning, information processing, information searching, evaluating the alternatives, decision making, and post-purchase behavior. When using such websites usability and trust also play a major role and these issues to be handled carefully. With all these facilities available, still we could find some gaps in existing website-based online shopping solutions where the user has limited freedom to communicate or ask doubts regarding items and get a feel of having a discussion with shoppers. This limitation can be overcome by using chatbots for online shopping.

  • Proposed Solution

In recent years, many organizations have shown tremendous interest in developing chatbots for online shopping. These chatbots help customers to handle their queries and to provide information on any kind of items requested. The willingness of the customers to use shopping bots also increased enormously due to the interest in shopping using the internet in pandemic times.

Theoretical Analysis

  • Block diagram
  • Hardware /software requirements
  • Processor: Intel i5
  • Memory: 16GB
  • System Type: 64 Bit Operating system
  • IBM Watson Assistant
  • Node-RED UI Generator

Experimental Investigations

The online shopping bot is developed using IBM Watson. The intents, entities, and context variables are generated, and the JSON file can be downloaded.

Advantages and Disadvantages

  1. An online shopping bot helps to see the list of items available for purchase.
  2. The shopping bot provides the details of the items requested by giving its image and cost.
  3. The shopping bot accepts the mail id to send the order receipt.
  4. The shopping bot accepts the order by asking the item, quantity, and mode of
  5. The shopping bot is interactive.
  6. The shopping bot is simple.
  7. The shopping bot is Usable.
  8. The shopping bot is a user
  9. The shopping bot is available 24/7
  10. The shopping bot is reliable.

Disadvantages

  1. The shopping bot is currently not accepting addresses in the chatbot.
  1. After receiving the receipt, the other interface like email to be used to share the address with the shopper.

Applications

The online shopping bot can be used for advertisement, recommendation, and taking orders from the customer when the customer is living in a chatbot with the shopper.

Conclusion

The online shopping bot is the most useful feature for online shoppers to have a satisfying purchase. With all the possible features embedded in bot it can help the customer to have a successful and satisfactory shopping with less money and time.

Future Scope

  1. The shopping bot can be extended to get reviews
  2. The shopping bot can be added with features like showing offers.
  3. The shopping bot can give recommendations by showing the associated items