Chatbots have grown in popularity in recent years, with their use in the e-commerce business skyrocketing. They’ve established a stronghold in nearly every task that demands text-based public trading. They’ve become crucial in customer service. We will look at how to help our ML algorithm have better conversations with the users. For us, human conversation is natural. It is part of our everyday life.
Now, let us understand what chatbot and Dialogflow are. Also, we will discuss in detail what are the fundamentals of Dialogflow and how we can create a simple chatbot using Google’s Dialogflow.
1. What is a Chatbot?
A chatbot is an intelligent program that can interact with people in the same way that a human can and serves them in the domain where it was designed. The chatbot evaluates the client’s purpose and searches for the most appropriate response.
2. What is Google’s DialogFlow?
Google’s DialogFlow is a development tool that can assist us in creating Chatbots. It is based on Natural Language Processing (NLP), which allows our chatbots to be powerful.
2.1 Fundamentals of Dialog Flow
We’ll go over some of the basics of DialogFlow to make sure you know what we’re talking about when we develop our chatbot.
2.1.1 Agent
Agents can be thought of as customer service superstars who deal directly with users to provide a fantastic experience.
Similarly, our chatbot in DialogFlow is an agent at a high level.
2.1.2 Intent
In DialogFlow, intents are the starting point of a dialogue. DialogFlow matches the input to the best intentions when a user starts a conversation with a chatbot.
Each intent has three parameters which are described below:
- Training Phrase:
These are some sentences that your chatbot could be given as inputs.
That specific intent is when a user input matches one of the phrases in the plan. You don’t have to define every possible phrase your users might use because all DialogFlow agents use machine learning. As people engage with your bot, DialogFlow automatically learns and expands this list.
- Parameters:
For instance, a user could say:
“I’d like to make a doctor’s appointment for Monday.”
In this case, “doctor appointment” and “Monday” might be the parameters extracted by DialogFlow from the input. Each parameter has an Entity type similar to a data type in standard programming. You’ll need to specify the parameters you’re looking for in each intent. It is possible to make parameters “mandatory.” DialogFlow will prompt the user for a needed parameter if it is not included in the input.
- Response
When an Intent is matched, DialogFlow returns these responses to the users. They may deliver answers, request additional information from the user, or act as conversation terminators.
2.1.3 Entities
Dialogflow‘s mechanism for recognising and extracting meaningful data from natural language inputs is called ‘entities.’
An intent restricts the bot’s capabilities to the scope of the user’s input. It may retrieve specific pieces of information from your consumers.
2.1.4 Context
Context is similar to Natural Language comprehension in that to answer the current discussion, we must first comprehend the context of the prior one.
As a result, they assist in connecting each discussion block so that the chatbot’s response is relevant.
3. What are the advantages of using a chatbot?
In some form or another, 80 percent of marketers intend to use a chatbot. It’s one of the main reasons companies are putting money into improving the consumer experience.
Google has stated that a shift from a mobile-first to an AI-first world is on the horizon. Companies in various industries have jumped on board and implemented AI-powered chatbots for their operations.
There are the following advantages of the chatbot.
3.1 24/7 Availability
Chatbots are available 24 hours a day, seven days a week, to answer consumers’ questions.
Chatbots enable the continuous connection between the seller and the client without the need for the customer to wait minutes for the next available operator.
3.2 Multilingual
Finding an English-speaking support representative can be difficult and costly. A chatbot can be built to communicate in several different languages.
They can also ask or detect the language in which clients are conversing at the start of a conversation and adjust accordingly.
3.3 Better Customer Engagement
Conversational bots may keep clients engaged 24 hours a day, seven days a week, by initiating proactive conservation and providing individualised recommendations to improve customer experience.
3.4 Automate lead qualification & sales
Chatbots can help you automate your sales funnel by pre-qualifying prospects and routing them to the appropriate team for further nurturing.
The ability to interact with customers instantaneously boosts lead generation and conversion rates.
4. Let us dive into: To Do
Building a Simple Chatbot in Google Dialogflow
4.1 Getting Started
A Google account is required to access Dialogflow. So, make sure you have one and utilise the link to sign in with Google on the DialogFlow page. Accept Google’s terms and conditions and select your country. You’ll be brought to the Dialogflow console in no time.
4.2 Create an Agent
The second step is to create an agent. Begin by selecting ‘Create Agent’ from the left-hand column menu. Make a name for your Bot!
Make sure you choose your time zone and language correctly. Select ‘Create’ from the drop-down menu.
4.3 Create Intent
The chatbot uses intents to figure out what the clients or users want.
We should include examples of terms that clients may question and some responses that the chatbot should use to respond to the clients in the intent. Let us demonstrate how we can accomplish this. Note that we get two default intents when we establish a new agent: Default Fallback Intent and Default Welcome Intent. Click the Create Intent button to start a new Intent.
After that, you must state your intent’s name. Then select Add Training Phrases from the Training Phrases section. This section explains how to give an example of a phrase that illustrates the various queries customers might ask the chatbot.
Let’s now define several Responses that the agent could utilise to respond to clients.
Add some response statements by going down to the Response section and clicking the Add response button.
You’ll notice that several of the expressions in these replies and examples begin with the $ symbol; these expressions are variables that will hold the values that customers will mention in their questions and that DialogFlow will identify as a distinct entity.
After adding some responses for the agent to utilise, click the Save button.
4.4 Creation of Entities
After you’ve defined your intents, you’ll need to declare your entities.
Entities are sophisticated tools for extracting parameter values from a user’s query.
There should be a corresponding entity for whatever actionable data you want to receive from a user’s request.
Entities, in reality, are keywords that aid the Agent in recognising the client’s desires.
Follow my instructions to make it. Select Entities from the drop-down menu after clicking on the Create Entity button.
After that, give the entity a name (you should provide reservation-type as the name of your entity because you had used it as a variable when you gave some responses to the agent). Click on the Save button.
4.5 Defining Parameters
DialogFlow requires the following information for each defined parameter:
If the parameter is set to ‘Required,’ DialogFlow will alert the user for further information if it was not provided in the original query.
- Parameter Name: It is the name of the parameter.
- Entity: The sort of data/information saved in the parameter is referred to as an entity.
- Value: The variable’s name used in ‘Responses’ refers to this parameter’s value.
- Prompts: The response to using if the parameter was not provided in the initial query.
5. Conclusion
DialogFlow has made it incredibly simple to create highly functional and fully customised chatbots quickly. The goal of this lesson was to provide you with an overview of how to construct chatbots and familiarise you with the platform’s fundamental concepts.
Other Conversational AI tools employ nearly the same concepts as those described here. Thus, they should work on any platform.
TechDel is the best mobile app development company based in London. We have a team of talented developers and designers who can specialise in producing exceptional apps and can help you design chatbots that help your business thrive. For more details, please visit TechDel Mobile Services.
