How to use Zendesk AI agent data capture forms: A complete guide

Getting your AI agent to collect the right customer data at the right time is what separates a helpful bot from a frustrating one. When your Zendesk AI agent captures information effectively, it can personalize conversations, route tickets intelligently, and hand off context seamlessly to human agents.

This guide walks you through two approaches to Zendesk AI agent data capture forms. Whether you need a simple no-code solution or advanced customization, you'll learn exactly how to implement data collection that fits your support workflow.

What are Zendesk AI agent data capture forms?

Data capture forms are how your AI agent collects and stores information during customer conversations. Think of them as the bridge between what your customer tells the bot and what your support team sees in the ticket.

Here's why they matter:

• Personalization at scale: The AI can greet customers by name, reference their order history, or acknowledge their account status without asking repetitive questions
• Intelligent routing: Collected data automatically routes tickets to the right team based on issue type, priority, or customer segment
• Seamless handoffs: When conversations escalate to human agents, all captured context transfers with the ticket, so customers never have to repeat themselves

Zendesk offers two distinct approaches to data capture. The Flow Builder method works for teams that want simplicity, while Advanced AI agents (formerly Ultimate) unlock enterprise-grade customization through metadata and APIs.

Method 1: Using Flow Builder for basic Zendesk AI agent data capture

The Flow Builder approach is Zendesk's no-code solution. It's built into all Zendesk Suite plans and handles straightforward data collection without any programming.

Here's how it works: you add an "Ask for details" step to your conversation flow, which prompts customers for specific information. Their responses get stored as variables that automatically populate ticket fields when the conversation transfers to an agent.

Step 1: Create custom ticket fields

Before building your flow, set up the fields where you want to store collected data.

Navigate to Admin Center > Objects and rules > Tickets > Fields. Create fields for the information you want to capture (order numbers, issue categories, account IDs, etc.).

Important limitation: Flow Builder only supports text and drop-down field types. If you need more complex data structures, you'll need the Advanced approach covered later.

Step 2: Add the "Ask for details" step

In your Flow Builder answer flow, add the "Ask for details" step where you want data collection to occur. Select the custom fields you created in Step 1.

Configure the step with clear prompts that tell customers exactly what information you need. For example: "What's your order number? You can find this in your confirmation email."

Step 3: Map data to ticket fields

The variables you collect automatically map to the ticket fields you selected. When the conversation escalates to a human agent, those fields appear pre-populated in the ticket.

This happens through Zendesk's native integration. No additional configuration needed. The data simply flows from the conversation into the ticket record.

Step 4: Test and publish

Always test your flow before going live. Use Zendesk's preview mode to simulate conversations and verify that data appears correctly in ticket fields.

Once everything works as expected, publish your AI agent. The Flow Builder approach is now handling your data capture automatically.

Method 2: Advanced data capture with Zendesk AI agents

For teams that need more sophisticated data handling, Zendesk AI agents Advanced (available as an add-on to Professional and Enterprise plans) unlocks powerful capabilities through Sunshine Conversations and metadata.

This approach lets you:

• Pass data from your website or app into the conversation
• Update information in real-time during the chat
• Use structured forms with validation
• Connect to external systems via API

Understanding the metadata architecture

Advanced AI agents use Sunshine Conversations as the underlying messaging platform. Data flows through metadata using a specific format: zen:ticket_field:FIELD_ID.

Here's what happens behind the scenes:

1. Your website passes data to the Zendesk Web Widget via JavaScript
2. The data stores as conversation metadata
3. Your AI agent retrieves this metadata through Actions
4. Parameters make the data available throughout the conversation
5. Upon escalation, metadata populates the corresponding ticket fields

Step 1: Pass context via JavaScript

Add this script after initializing the Zendesk Web Widget on your website:

zE("messenger:set", "conversationFields", [
  { id: "123456789", value: "customer_value_here" }
])

Replace 123456789 with your actual custom field ID from Admin Center, and customer_value_here with the data you want to pass (user ID, order number, page context, etc.).

The field must be end-user editable for this to work. You can find field IDs in Admin Center under Objects and rules > Tickets > Fields.

Step 2: Create Actions to retrieve metadata

In the AI agents Advanced dashboard, navigate to Content > Actions. Create a new Action with these settings:

• Target: Sunshine Conversations
• Task: Get conversation metadata
• Retrieve: (Metadata) object
• Save as: A parameter name you'll reference in replies (like order_number or customer_tier)

For the Key field, use the metadata format: zen:ticket_field:123456789 (using your actual field ID).

Step 3: Use parameters in AI agent replies

Once your Action retrieves the metadata, reference it in AI agent messages using double curly braces: {{parameter_name}}.

For example: "Hi there! I see you're asking about order {{order_number}}. Let me check on that for you."

Add conditional logic to handle cases where metadata might be empty. Use an "if" condition to check if the parameter exists before referencing it.

Step 4: Update metadata during conversations

Sometimes you need to capture new information during the chat and pass it back to Zendesk. Create another Action:

• Target: Sunshine Conversations
• Task: Update conversation metadata
• Key: zen:ticket_field:YOUR_FIELD_ID
• Value: {{parameter_name}} (the variable storing the new information)

Place this Action in your escalation flow so the updated data transfers when the conversation moves to a human agent.

Step 5: Transfer data to tickets

When escalation occurs, all metadata automatically populates the corresponding ticket fields in Agent Workspace. Your human agents see the complete context without any manual data entry.

For complex workflows, you can use the Conversations API to make custom API calls that transfer conversations with specific metadata patterns.

Working with forms in conversation flows

Structured forms offer a cleaner alternative to conversational data collection, especially for complex information gathering.

Creating forms in Sunshine Conversations

Forms are created separately in Sunshine Conversations before being integrated into AI agent dialogues. A typical form includes:

• Text inputs for free-form data (names, order numbers, descriptions)
• Select dropdowns for categorical choices (issue type, product category, priority level)
• Validation rules to ensure data quality

Once created, you reference forms in AI agent dialogues using the template syntax: %((template: form_name))%

Sanitizing PII data

When collecting sensitive information, enable sanitization to protect customer privacy. Zendesk automatically sanitizes email addresses and IBAN numbers by default.

For other PII fields, open the "if..." condition details panel in your dialogue builder and check the "Sanitize the user's answer" box. This hides sensitive data in conversation logs while still passing it to ticket fields.

Best practices for form design

• Keep forms focused on a single purpose (account lookup, issue categorization, etc.)
• Use clear labels that customers understand without support context
• Limit required fields to essential information only
• Test forms across different messaging channels (web, mobile, WhatsApp)

Choosing the right approach for your Zendesk AI agent data capture

Both methods have their place. Here's how to decide:

Choose Flow Builder when: You need basic information collection (names, issue types, simple identifiers) and want to get up and running quickly without developer resources.

Choose Advanced AI agents when: You need to pass rich context from your website or app, integrate with external systems like Shopify or your CRM, or build complex multi-step workflows.

If you find yourself somewhere in between, eesel AI integrates with Zendesk to provide advanced data capture capabilities through a simpler interface. You can connect your Zendesk account and start automating without the technical overhead of Sunshine Conversations configuration.

Common use cases for Zendesk AI agent data capture forms

Here are practical ways support teams use data capture:

Order number collection: E-commerce companies capture order IDs upfront so the AI can look up shipping status, process returns, or check eligibility for exchanges. This deflects common "where's my order" tickets automatically.

Account verification: Financial services and healthcare organizations collect identifying information (account numbers, date of birth, security questions) before allowing access to sensitive account details.

Issue categorization: By capturing the topic or product area early, tickets route directly to specialized teams (billing, technical support, returns) without manual triage.

Customer feedback: Post-resolution surveys collect CSAT scores and qualitative feedback that feeds into reporting and agent coaching.

File uploads: Integrations with secure file collection tools like SendSafely let customers upload documents (receipts, ID verification, screenshots) directly within the conversation.

For teams looking to automate these workflows without complex setup, our guide on how to automate your customer support workflow using AI covers implementation strategies that work alongside Zendesk.

Start capturing data effectively with Zendesk AI agents

Effective data capture transforms your AI agent from a simple chatbot into a true support partner. Whether you choose the straightforward Flow Builder approach or the powerful Advanced AI agents method, the key is matching the complexity of your solution to the complexity of your needs.

Start simple. Implement basic data collection with Flow Builder to solve immediate problems. As your needs grow, graduate to Advanced AI agents for deeper integration and customization.

Remember: every piece of data you capture should serve a purpose. Collecting information just because you can creates friction for customers. Collecting the right information at the right time creates better experiences for everyone.

If you're looking for a way to achieve advanced data capture without the technical complexity, eesel AI works seamlessly with Zendesk to provide sophisticated automation through a simpler interface. Check our pricing to see how we can complement your Zendesk setup.