ZazzyAgent Custom Fields | How to Store Customer Information
A chatbot can answer questions, but useful automation often depends on remembering information about the customer.
That's where custom fields come in.
Custom fields let you store structured information about a customer so it can be used later in conversations, automations, conditions and other workflows.
Examples include:
Product of interest
City
Company name
Budget
Preferred date
Order preference
Lead source
Customer type
What is a custom field?
A custom field is a piece of customer information that you define and store.
For example:
Field: Product Interest
Value: Running Shoes
Another customer could have:
Field: Product Interest
Value: Formal Shoes
The field stays associated with the customer so your automation can use it later.
Why use custom fields?
Imagine a customer tells your chatbot:
I'm looking for a black shirt, size XL, under ₹2,000.
Instead of forgetting the information after the message, your automation can save useful parts of the conversation.
You could store:
Product Interest: Shirt
Color: Black
Size: XL
Budget: 2000
Later, an agent or automation can use those values.
Custom fields vs labels
These are different tools.
Label
A simple marker.
High Intent
Custom Field
A specific value.
Budget = ₹2,000
A label tells you what kind of customer or situation this is.
A custom field tells you the value associated with that customer.
Examples of useful custom fields
Lead generation
Name
Company
Job Role
Budget
Requirement
Ecommerce
Product Interest
Preferred Category
Size
Color
Order Number
Real estate
Preferred Location
Budget
Property Type
Bedrooms
Education
Course
Qualification
City
Preferred Intake
Appointments
Service
Preferred Date
Preferred Time
Location
How to create a custom field
Open the Custom Fields area in ZazzyAgent.
Create a new field.
Give it a descriptive name.
Good:
Product Interest
Customer City
Budget
Avoid:
Field 1
Data
Test
Clear names make your automations much easier to understand later.
Decide what should be stored
Don't create a custom field for every piece of text a customer sends.
Create fields for information that has a purpose.
Ask:
Will I use this information later?
If the answer is no, you probably don't need to store it.
Save information through User Input
One of the easiest ways to populate custom fields is through User Input.
For example:
What city are you in?
The customer's response can be saved to:
City
Then later your flow can check:
City = Mumbai
and send the appropriate response.
Use custom fields in conditions
Suppose you save:
Budget = 50000
You can then build conditional logic around that information.
For example:
If Budget is greater than 40,000
→ Show premium products.
Otherwise:
→ Show standard products.
Conditions can use custom-field values to create different customer journeys.
Use custom fields for personalization
Suppose you saved:
First Name = Rahul
You may be able to use that information in supported messages to personalize the conversation.
Instead of:
Welcome back!
you can create a personalized message such as:
Welcome back, Rahul!
Personalization should be used naturally. Don't repeat the customer's name in every message.
Save information from an AI Agent
An AI Agent can also be instructed to save information using the appropriate action.
For example:
When the customer clearly provides their preferred city,
save it to the City custom field.
##save_custom_field## : 42
Use the ## autocomplete in the System Prompt editor and select the correct custom field rather than guessing the numeric ID.
Use custom fields in automation
A common workflow is:
Customer provides information
↓
Save to custom field
↓
Check the field
↓
Choose the correct path
For example:
What is your budget?
Customer:
₹25,000
↓
Save Budget
↓
Condition:
Budget >= ₹20,000
↓
Show premium products.
Use custom fields in segmentation
Customer information can also help create more targeted audiences.
For example:
Budget >= ₹20,000
and:
Product Interest = Laptop
This gives you a more specific group than a generic "Laptop Interested" label alone.
Don't overwrite useful information accidentally
Suppose you previously stored:
Preferred City = Mumbai
Later, the customer says:
I'm moving to Pune next month.
You need to decide whether the new information should replace the old value.
The System Prompt should tell the AI when an existing field should be updated.
Custom field troubleshooting
The field is empty
Check:
Was the field actually created?
Was the customer's answer captured?
Did the workflow save the value?
Is the correct custom field selected?
Did the customer provide a usable value?
The wrong value is stored
Check the instructions used by the flow or AI Agent.
Make sure the system clearly explains what information should be saved.
The condition isn't working
Check:
The field name
The field value
The operator
The data format
Whether the customer actually has a value stored
Best practice
Don't think of custom fields as a place to store everything.
Think of them as your structured customer memory.
Store information that helps you:
Personalize conversations
Make decisions
Segment customers
Trigger automation
Help human agents
Connect customer data with external systems
A small set of well-designed fields is much easier to manage than hundreds of poorly defined ones.