Steps to create a WhatsApp Bot

Updated on October 29th, 2021

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Design the bot Build the bot on Haptik Platform Stage 1: Create a New Bot Stage 2: Create a Skill and Skill Set Stage 3: Create Steps Stage 4: Add User Messages Stage 5: Add Bot Responses Stage 6: Add Entities Stage 7: Create Connections

In this section, we will see how to begin the designing of a WhatsApp bot, how to build the bot on the Conversation Studio tool of Haptik Platform and how to deploy the bot so users can start sending messages to your business.

Design the bot

Well, when it comes to creating a WhatsApp IVA, the first and foremost consideration is design. There are a lot of UX considerations to keep in mind while designing an automated experience for WhatsApp.

Some tips to start with:

WhatsApp is a user-focused platform, users have the power to block or report a business number.
Start small: Start with the burning customer issues which can be resolved in a transactional manner with a quick resolution on WhatsApp. These use cases will help maintain a high-quality rating from the users
Design a conversational experience for the user. It’s WhatsApp, after all.
Enrich the customer experience by using media messages (photos, videos, etc.) to drive higher engagement
Ensure valid human escalation paths - Businesses without a valid human escalation path may become red in terms of quality rating and will see the phone number Status is Flagged. Valid escalation paths include human agent handoff in a thread, phone number, email, web support form, or prompting the user for an in-store visit

To start the Conversation Design process for the WhatsApp bot, please read here.

Build the bot on Haptik Platform

Stage 1: Create a New Bot

We will start by creating a new bot on the platform.

Stage 2: Create a Skill and Skillset

After creating a new bot, create a new Skillset within the bot. Within the Skillset, create a new Skill. Every Skill handles one use case. To know more about Skill, click here.

Stage 3: Create Steps

Steps are the interlinked building blocks of a bot. Each step acts like a gatekeeper that detects user inputs, sends out appropriate responses, and directs users to the next step.

Steps are composed of several important sub-components, which house important pieces of information - User Messages, Bot Responses, Entities, and APIs.

To know more about Steps, click here.

Stage 4: Add User Messages

User Messages are the inputs from the user that the agent needs to interpret the user’s goal. It is important to add and train the bot with a variety of different sample user messages for each step, so that the bot can identify the correct intents and extract entities from the user utterance.

Whenever a user sends a message, we try to understand what the user is trying to say using various Machine Learning algorithms and find the corresponding step. One of the key modules which is used for step identification is the Intent Detection module.

To know more about adding user messages, click here.

Stage 5: Add Bot Responses

Bot Response is where a Step stores the replies that are sent in response to the user's message.

To know more about Bot Responses, click here.

Because of the platform limitations, many HSL elements from the Conversation Studio tool will not work on WhatsApp.

Here's the list of HSLs that are currently supported:

Raw Text/JSON
Image HSL
Quick Replies
Buttons

You can read more about Buttons and Lists here.

Any media type of file (image, video, or document) that you are sharing with the users, should be 10MB or less in size.

Stage 6: Add Entities

An entity represents values that are collected from the user in a conversation. Depending on the context of the conversation, the required response can either be a single value or a group of specific values.

On the WhatsApp bot, the majority of flows are menu-driven.

For example:

Therefore, on WhatsApp, we make use of the Words & Phrases entity. Words & Phrases is a dictionary entity, which is configured as follows -

As we want the user to select an option from the menu, we have created a dictionary entity, where the Words column represents the actual word that will get detected and in the Variants column we can add the different variations which users can type. If the user types 1, the bot captures the value as word, work, in this case.

For attachment type entities, WhatsApp can compress images and send compressed images to Haptik. Haptik stores the received image to S3.

You can fetch user's name and phone number from WhatsApp.
There are system entity that can fetch these values from the user's profile.
Use _completion_phone_number_ to fetch user's phone number and _username_ to fetch the user's profile name.

Add the entities on the first step of the bot and mark them as non-mandatory. Read here to know more about entities.

Stage 7: Create Connections

Connections represent the path a conversation takes from step to step. Depending on the response a user inputs to the bot, they traverse down a different connection to the appropriate next step. Bot builders must modify every connection they create to indicate which user inputs correspond to which steps.

On WhatsApp, we majorly use 2 types of connections -

Connection using entity - We will use the entity detected from Stage 6, to create further connections. To know more about using entity values on connection, click here.
Self Connecting Steps

When the bot breaks or if you are sending notifications to the user and want the user to start the conversation by clicking on the buttons present in the HSM, we make use of Self Connecting steps.

When the suer taps on the HSM button, they will always be directed to the start of the flow.

Self connecting steps also are helpful to restart the flow in case the bot breaks. You can ask the use to start the flow by typing Main Menu and it will again restart the flow from the start steps.

How to create a self-connecting step?

Create a Words & Phrases entity and add dictionary as shown below -

On the start step, go to the Connections tab and create a self-connection as shown below -

Click on the new arrow, and create the connection on the basis of Entity.

The feedback module does not work on the WhatsApp bot due to UI limitations.

Follow our Quality Assessment section to test the bot.

Once the bot is tested, we will deploy the bot on WhatsApp using Platform Deployment under Business Manager of Conversation Studio.

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