How AI Agents Save Customer Information in ZazzyAgent
A useful AI Agent should not have to ask the same question repeatedly.
When a customer provides information that will be useful later, you can save it into a custom field.
Examples:
Name
Email
City
Product interest
Budget
Order number
Preferred date
Company name
The AI Agent can be instructed to save that information during the conversation.
The custom-field action
The action format is:
##save_custom_field## : 42
The number represents the selected custom field.
Inside the System Prompt editor, type:
##
Then select the action and the correct custom field from the autocomplete list.
The interface uses the field's name when you select it; the stored prompt uses its internal ID.
Example: Save a customer's city
Suppose the agent asks:
Which city are you based in?
Customer:
Mumbai
You can instruct the agent:
When the customer clearly provides their city,
save that answer in the City custom field.
##save_custom_field## : 42
Select your actual City field using autocomplete.
Example: Save product interest
When the customer identifies the product category they are interested in,
save it to the Product Interest custom field.
##save_custom_field## : 18
Now the customer record can contain:
Product Interest = Running Shoes
Example: Save budget
When the customer clearly provides their approximate budget,
save the amount to the Budget custom field.
##save_custom_field## : 27
If the customer says:
Around ₹40,000.
Your workflow can store that information according to the custom field's configuration.
Tell the AI exactly what should be saved
This is critical.
Don't write:
Save the customer's information.
That's too vague.
Tell the agent:
Save the customer's preferred city to the City custom field.
or:
Save the customer's approximate budget to the Budget custom field.
The clearer the instruction, the easier it is to control the stored data.
Don't save information before the customer provides it
Bad instruction:
Save the customer's budget.
The customer hasn't provided a budget yet.
Better:
Ask the customer for their approximate budget.
After the customer provides a clear answer,
save the answer to the Budget custom field.
##save_custom_field## : 27
Don't ask twice
Your prompt should tell the AI to reuse information already provided.
Example:
If the customer has already provided their city,
do not ask for their city again.
Use the existing customer information when appropriate.
This makes conversations feel much more natural.
Save order numbers
Order numbers are particularly useful for ecommerce support.
Example:
Customer:
My order number is 12345.
Your agent can be instructed:
When the customer provides their order number,
save it to the Order Number custom field.
##save_custom_field## : 35
You can then use that information in other workflows where supported.
Save lead information
A lead-qualification agent might save:
Name
Company
Requirement
Budget
Timeline
Then your sales team can see the information without reading the entire conversation.
Save appointment information
An appointment agent could save:
Service
Preferred Date
Preferred Time
This allows the information to be reused later in the conversation or passed to another system where supported.
Combine saving information with other actions
A common AI workflow is:
Customer provides information
↓
Save custom field
↓
Add label
↓
Start sequence
For example:
When the customer confirms that they are interested in the Enterprise plan,
save Enterprise as the Product Interest value.
##save_custom_field## : 18
Add the Qualified Lead label.
##add_label## : 12
Start the appropriate sales follow-up sequence.
##assign_sequence## : 8
Each action has a different purpose.
Custom field vs label
Use a custom field when you need the actual value.
Budget = ₹40,000
Use a label when you need a simple classification.
High Intent
Both can be used together.
What if the customer changes their answer?
Suppose the customer first says:
Mumbai
and later says:
Actually, I moved to Pune.
Your System Prompt should explain when the newer information should replace the old value.
Example:
If the customer corrects or updates their city,
save the new city value to the City custom field.
Don't store guesses
The AI should never invent values.
Use rules such as:
Only save a value when the customer clearly provides it.
If the customer's answer is ambiguous,
ask a follow-up question before saving it.
Use saved information later
Once information is stored, supported ZazzyAgent features can use that information for:
Conditions
Personalization
Segmentation
Broadcast targeting
Other automation
External integrations
Test your custom fields
Test:
Clear response
I'm based in Pune.
Expected:
City = Pune
Ambiguous response
Somewhere near Mumbai.
The agent should clarify if an exact city is required.
Correction
Actually, I moved to Delhi.
The field should be updated if your prompt says to accept corrections.
Missing response
I don't want to share that.
Don't save a made-up value.
Common problems
Field remains empty
Check that:
The custom field exists.
The correct field was selected.
The customer actually provided the information.
The prompt tells the agent when to save it.
Wrong value was saved
Make the extraction rule more precise.
Agent keeps asking the same question
Tell the agent to use already-known customer information before asking again.
A useful pattern
The best instruction is usually:
Ask → Confirm → Save
Example:
What city are you based in?
Customer:
Pune.
Just confirming, you're based in Pune?
Then:
##save_custom_field## : 42
You don't always need the confirmation step, but it can be valuable for important information.
The purpose is simple:
Turn useful conversation information into structured customer data.