Text based AI powered chatbot: Redefining Customer Care

My blog,’Text based AI powered chatbot: Redefining Customer Care’, is a detailed narration of the information given in the following table:-

Aspect	Description	Details
1. Instant Reply	AI chatbots can provide instant answers during the real time customer request because they are able to respond immediately.	Customers no longer need wait in long queues; responses are as instant, meaning greater satisfaction.
2. Always Online	Chatbots are always available: they are accessible 24/7, guaranteeing the above-mentioned continuous customer support.	It means businesses can support customers globally across all different time zones without human assistance.
3. Personalization	Artificial intelligence chatbots use a client's data to offer personal interactions.	Based on past discussions, preferences, or buying behavior, chatbots can tailor the responses and solutions based on them.
4. Cost Efficiency	No need for a mass workforce of human customer support staff.	It is a scalable solution because it will allow businesses to process many inquiries without any increase in operational cost.
5. Multi-language Support Users	Chatbots can communicate in multiple languages, enhancing global customer service.	AI models are trained to understand and respond in various languages, improving inclusivity and user experience.
6. Data-Driven Insights	AI-powered chatbots collect invaluable data on customer behavior and preferences.	It can be analyzed in respect of better services, product development, and more effective marketing strategies.
7. Error Reduction	Reduce human error at customer service.	Chatbots use a set of protocols, therefore ensuring that information given to customers is correct and uniform in all instances.
8. Scalability	AI chatbots don't stall when multiple demands start coming.	Unlike human agents, chatbots can run multiple customer interactions with no lag or delay.

Across various sectors and domains there are text driven AI Innovative chatbots offering scalable and efficient customer care solutions.

Example of Text based AI powered chatbot: Redefining Customer Care:

Example: Banks and financial institutions utilize AI-powered chatbots to enhance customer service, streamline operations, and improve customer satisfaction. These chatbots can handle a wide range of inquiries and tasks, such as account inquiries, transaction history, balance checks, fund transfers, bill payments, and loan applications.

Google developed Dialogflow as a natural language understanding platform.
Dialogflow software in companies like Google, Dominos Pizza, Ticket Master, Mercedes-Benz, T-Mobile, HSBC, eBay, Telefonica. With 24/7 availability these AI assistants provide instant answers to customer queries. his revolutionizes the way businesses interact with their audiences.
It means there is a conversation between the customers and the websites, mobile applications, messaging services.

Table of Contents

IRCTC an example of Dialogflow integration.(Text based AI powered chatbot: Redefining Customer Care)

IRCTC is an example of Dialogflow integrated to its website on mobile app to power chatbot function.
Users type queries or commands into chat interfaces provided by IRCTC websites and mobile apps to interact with the IRCTC chatbot. Example: ‘Check train availability from Delhi to Mumbai on 25th March. Dialogflow understands the intent behind this above customer’s query on a specific route and date. AI algorithms understand the intent of user input. IRCTC creates predefined intents on Dialogflow. This intent matches the user’s query. These intent includes actions like, booking tickets, Checking PNR status, getting train schedules. Dialog flow responds in the form of a text providing requested information or asks for more details.
The user gives feedback after reviewing the chatbot’s response.
There is an integrated system between the Dialogflow and the backend databases. Dialogflow fetches information from the backend databases about trains, availability fares and bookings. APIs fetch data to provide accurate responses to users.

Dominos Pizza, an example of Dialogflow integration.

The conversation between the user and the Dominos Pizza Chatbot begins like this, ‘Can i have a Pizza?’ or ‘May I have a Pizza?’ or ‘Can I order a Veg Pizza?’.
Dialog flow can be integrated with the order management system, so that the User asks to have a order management. An order management system (OMS) can be considered part of the backend infrastructure of Domino’s Pizza’s operations.

How to use Dialogflow, is given ahead.

Go to the link https://dialogflow.cloud.google.com/#/getStarted

The process of Text based AI powered chatbot: Redefining Customer Care, i.e. using Dialog Flow is as follows:-

When you first visit the link, accept the terms.
Get Started
You can create an 'Agent'. We have created the agent Test-Chatbot1.
Once you create an agent, you will see 'Intent' on the left hand side. You can understand the intent of the user.
'Entity' is for grasping the information from the users. For example, When the customer says,'I want a veg Pizza', it means customer wants a veg pizza instead of a normal pizza. This is done by using Entity.
Using 'Knowledge' feature, you can use your own Knowledge flow.
You can use 'Fulfillment' to integrate Dialogflow with other integration systems like the customer management systems.
You can use 'Integrations' to integrate with other channels, such your website, Facebook, Telegram, Slack etc.
Once you start using your Chatbot, you can certainly use your Chatbot for asking questions which your chatbot doesn't know. These questions are answered by the, 'Training' section of the dialogflow.
You should Enable the 'Validation', this is to improve this feature. If you go to the 'settings', then go to ML Settings, enable Agent Validation, then go to 'Train', then this feature will be enabled.
The 'History' section is to view the history first.
In the 'Analytics' of the chatbot you will find the Analysis of the chatbot.
'Prebuilt Agent' is a Templates which Chatbot directly created for your Chatbot. You can go to Import in the Date, You can create a new agent name, Test-Chatbot1-Date, Select the Google Cloud Project or use which one we already have. Then we can 'Go to Agent' with all of the Intents that belong to this template. We can use these Templates in your Agents.
'Small Talk' is the section which includes answers to standard questions, like Who are you?, Are you a Chatbot?, How old are you?. Simple questions asked by users are answered.
All this above which i have given you is part of Dialogflow essentials(ES Agent). So by default you will be using the trial edition. This edition is free until 180 requests per minute. they will cost you less than 1 scent per request.