This article shows you how to have your bot gather information, sending that info to custom fields, then use a workflow to do math and AI to deliver quote.

Many people like to try to have AI collect information, do some simple math, and give a quote to a customer. This is something many AGENT AI CHAT BOT users have implemented and you can too! However, AI is not reliable at performing math operations (even simple ones). This article shows you how to set up workflows and fields that allow the bot to gather information, update custom fields, then rely on workflows to do the math for you.

This blog post demonstrates a workaround for AGENT AI CHAT BOT's limitations in performing mathematical calculations. It outlines a method involving:

1. Creating Custom Fields: Establishing fields to store the necessary data for calculations (e.g., "Sq Footage" and "Price").

2. Building a Math Workflow: Designing a workflow triggered by changes in the input field ("Sq Footage") to perform the calculations and update the "Price" field.

3. Configuring Bot Objectives: Structuring the chatbot to gather relevant information (e.g., home area), update the corresponding custom fields, and incorporate a delay to allow the workflow to execute before delivering the calculated quote.

1. Create Custom Fields

We will need at least 2 custom fields for this. One will hold the final price that we want to deliver as our quote to the customer, and the other(s) will be the values we need in order to do our workflow math. For this scenario, let's pretend we are a flooring contractor who quotes work at $3/sq ft of home size.

The $3/sq ft is constant, but the home area is a variable that we need to collect from the customer. We will create a custom field called Sq Footage (ft^2). The title of the field can be anything, but it should be descriptive enough to let the bot know what you expect to update it with.

The price custom field will be a monetary field. This is the field that our workflow will update with calculated final pricing information.

2. Create Math Workflow

We want our math workflow to trigger any time the field Sq Footage (ft^2) changes, do some simple math, and update our Price field.

3. Bot Objectives

We are done with the hard part at this point 👏 Next, let's set up our bot to conversationally gather the contact's name, home area, how soon they want the work completed and give the final price.

Gathering Info and Updating Field

Each objective can be linked to a field that we want it to update. For example, the area of home objective has been connected to our Sq Footage (ft^2) field so it knows to update that field when the objective has been completed.

Filler Objective

Notice the objective availability after our area of home objective? Collecting one more objective after getting the area of the home allows our workflow the time needed to execute and update our field Price.

You don't have to have this objective set up to update any field if you don't want. It's just there to give your workflow time to do its thing.

Give Price

Lastly, we have our give price objective. We reference the GoHighLevel variable for the Price custom field to instruct the AI to give this price to the contact in a way that fits with the conversation flow.

By leveraging this approach, businesses can effectively utilize AGENT AI CHAT BOT for lead qualification and information gathering while relying on robust workflows to handle complex mathematical operations for accurate and efficient quote generation.