Ticket fields

Overview

With ticket fields, you can capture structured information about customer interactions that goes beyond the standard ticket properties. Create custom fields to capture product details, issue categories, resolution metrics, or other data specific to your support workflow.

​Core competencies

• 5 Field Types: Text, numeric, dropdown, Boolean, and product fields

• AI Automatic Filling: Automatically fill in fields by analyzing the conversation context

• Smart product linking: Link tickets to the products purchased in customer orders

• Advanced Analytics: Use, Trends, and Distribution of Careers Over Time

• Validation of Required Fields: Make sure to record important information before solving the problem

• Channel-specific fields: Display different fields depending on the communication channel

​Getting Started

1.

Go to the settings for ticket fields

Continue toSettings→Ticket fieldsto access the field management.

2.

Create your first field

ClickCreate fieldto open the field configuration window.

You will configure the following:

• Display name: How the field is displayed to the agent

• Field type: Text, number, dropdown, Boolean value, or product

• Description: Optional help text for agents

• Channel Availability: Which channels should display this field?

3.

Configure field options

Configure specific options depending on the field type:

• Text: Single-line or multi-line input

• number: Integer or decimal values

• Dropdown: Add custom options with nested hierarchies

• Boolean: Simple on/off switch

• Product: Automatic integration with e-commerce platforms

The field key is automatically generated from the display name and must be unique.

4.

Enable AI and configure the necessary settings

Enable or disable these options as needed:

• AI-powered: Let the AI fill in the field automatically

• Required: Must be completed before the ticket is processed

The combination of AI-driven and mandatory data entry ensures that important data is captured automatically, with manual entry used only if the AI cannot determine the value.

5.

Save and activate

Save your field configuration. The field will be available immediately in tickets for the enabled channels.

Field types

​Text field

Capture free-form text entries from employees.

Configuration options:

• Single-line: For short text such as names, IDs, or brief notes

• Multi-line: For more detailed descriptions or information

Behavior:

• Automatically save when the field loses focus (onBlur)

• Automatic saving when you press the Enter key

• AI can extract relevant passages from conversations

Use cases:

• Customer reference numbers

• Summaries of legal cases

• Special Notes

• Tracking-IDs

Number field

Enter numerical values with validation.

Configuration options:

• Very: Only whole numbers

• Decimal: Decimal places are allowed (e.g., 10.99)

Behavior:

• Automatically save when the field loses focus (onBlur)

• Automatic saving when you press the Enter key

• Automatically checks numerical entries

Use cases:

• Order quantities

• Refund amounts

• Severity ratings

• Response time requirements

​drop-down menu

A dropdown menu with a single selection option and custom options.

Features:

• Unlimited customization options

• Support for nested hierarchies (e.g., category → subcategory → problem type)

• Searchable options

• Options that can be rearranged using drag-and-drop

Behavior:

• Saved immediately after selection

• The AI selects the most appropriate option based on the context of the conversation

• Real-time updates

Use cases:

• Topic Categories

• Product type

• Possible solutions

• Department assignment

Example of nested options:

Here's how to enter the data:

Advance Sales::Product Information::Prices
Pre-sale::Product Information::Features
Questions about advance sales and shipping
After Purchase::Returns
After Purchase::Refunds
After purchase::Exchanges

This is how it appears:

Advance Sales > Product Information > Prices
Pre-sale > Product Information > Features
Pre-order > Questions about shipping
Customer Service > Returns
Customer Service > Refunds
Customer Service > Exchanges

Usage::as a separator when creating nested options. The system displays them with>for easier reading.

Boolean field

Simple yes/no switch for binary choices.

Behavior:

• Saves immediately when switching

• The AI uses the conversation to determine whether a statement is true or false

• Clear visual indication of status

Use cases:

• Designated as a VIP customer

• Indicator for high priority

• Eligibility requirements for a refund

• Warranty Services

Product Line

Expanded product selection from customer orders and the catalog.

Features:

• Order products first: The customer's most recently ordered products are displayed at the top

• Full access to the catalog: Search the entire product range

• Support for variants: Select specific product variants

• Order context: Indicates which order the product came from

• Multi-Integration: Compatible with Shopify, WooCommerce, Billbee, and other platforms

Behavior:

• Searchable interface with two sections:

  1. From customer orders(priority)

  2. All Products(General Catalog)

• Display variants as nested options

• Displays the order number for the context

• Cached in Redis for fast loading (10-minute TTL)

Ad format:

Product Name – Variant (Order Number 12345)

Example:
iPhone 15 – 256 GB, black (order number 12345)

AI Behavior:

• Analyzes conversations to identify products mentioned in them

• Links to the customer's order history

• Automatically selects the right product and variant

Use cases:

• Product-specific support tickets

• Warranty claims

• Processing Returns and Exchanges

• Tracking Product Defects

The "Product" field requires active store integrations (Shopify, WooCommerce, etc.) to function. The field remains empty if no integrations are configured.

AI Automatic Filling

The AI automatically fills in the selected fields by analyzing the context of the ticket.

How AI Analysis Works

1.

Trigger points

The AI analysis is performed at two key points in time:

1. On Creation: When a customer's first message arrives

2. Regarding the resolution: Please try again, as some required fields are missing

2.

Context Analysis

The AI examines:

• Customer reports and ticket subject

• Customer Order History (for product fields)

• Similar resolved tickets (pattern matching)

• Channel-specific context

3.

Trust rating

The AI only saves values if the confidence level exceeds 70%.

• High confidence (>0.7): Value is saved automatically

• Low confidence (<0,7): Field left blank for manual review

The AI logs the reasons behind every field decision, allowing you to better understand them and improve accuracy over time.

4.

Batch processing

For efficiency reasons, all AI-enabled fields are analyzed in a single AI call.

This reduces API costs and improves response times compared to analyzing the fields individually.

​Origin Analysis

When a ticket is created, the AI analyzes itall AI-powered areas:

Customer: “Hello, I ordered an iPhone 15, but it won’t turn on.”

AI Analysis:
✅ Product category → iPhone 15 (from order no. 12345)
✅ Issue category → After purchase → Product defect
✅ Urgency → High (Device not working)

​Resolution analysis

When a ticket is closed, the AI makes another attemptThe only thing missing are the required AI-enabled fields:

The employee has added 3 more messages with troubleshooting steps...

KI Reanalysis:
✅ Resolution method → Replacement sent (as discussed)
✅ Root cause → Hardware failure (determined through troubleshooting)

The AI learns from previously filled-in fields and will only not overwrite manual entries if the field was originally filled in by the AI.

Smart Review Workflow

If the AI is unable to fill in required fields even after several attempts, the tickets are automatically flagged for manual review.

​The Process

1.

AI experiments (3 replicates)

If a ticket is closed even though required AI-enabled fields are missing:

1. Experiment 1: Immediate retry (1-second delay)

2. Experiment 2: Try again in 2 seconds

3. Experiment 3: Final retry after 4 seconds

2.

Automatic status change

After three unsuccessful attempts:

• Status →On hold

• Subcategory →Needs to be checked

• The ticket is displayed in the "Pending Review" system view

3.

Agent Rating

The employee opens a ticket from the "For Review" view:

• Missing fields are marked in red

• The dialog box explains which fields need to be filled out

• The clerk fills in the fields manually

• The ticket can then be processed

This workflow ensures that no necessary data is lost while maintaining the efficiency of automation. Most fields are filled in automatically; manual verification is performed only when necessary.

Validation of Required Fields

Make sure that important information is recorded before processing the ticket.

​Validation contexts

Validation before the solution (chat input):

• Checks onlyFields that do not require AI

• Assume that the AI fields will be filled in automatically

• Prevents the form from being submitted if required fields are missing in the manual entry

Needs to be verified (verification dialog):

• ChecksAll required fields(AI + non-AI)

• Used when the ticket is availableReview requiredStatus

• Displays all fields that still need to be filled in

​Bulk verification of resolutions

When editing multiple tickets at the same time:

1. The system checks all selected tickets for missing required non-AI fields

2. Prevents closure if fields are missing from a ticket

3. Displays a preview window showing the relevant tickets

4. The employee can click on the ticket to fill in the fields one by one

When validating mass resolutions, only fields that do not require AI are checked to prevent blocking if the AI can automatically fill in fields during the resolution trigger.

​Channel Configuration

Specify which fields are displayed depending on the communication channel.

​Here's how it works

Each field can be configured as follows:

• All channels: This field is displayed for all ticket types

• Specific channels: This field is displayed only for selected channels (email, WhatsApp, phone, etc.)

​Use Cases

Fields that can only be filled out via email:

• Email Domain Verification

• Spam Classification

Fields that can only be filled in using voice input:

• Call duration

• Assessment of call quality

Product-specific channels:

• Product Categories for E-Commerce Channels

• Order number for shop integrations

Channel-specific fields ensure a clean user interface by displaying only the relevant fields for each ticket type.

Analytics-Dashboard

Track performance on the sports field and identify trends.

Access to Analytics

Go toDashboard→Ticket fieldsto view the analysis data.

​Field selection

Select the field you want to analyze from the drop-down list.

• Show only active fields

• Grouping by field type

• Update all cards when the selection changes

​Filter for the date range

Filter analyses by time period:

• Last 7 days

• Last 30 days

• Last 90 days

• Custom date range

​Switch data range

Switch between:

• All tickets: Includes tickets without the field set

• For applied science only: Only tickets where the field contains a value

Select "Used Only" to view the distribution across tickets where the field is actually used, excluding tickets where the field was not relevant.

Map showing the highest residual values

A horizontal bar chart showing the most common field values.

Features:

• Displays the top 10 entries by number of tickets

• Values shown within the bars

• Counting the tickets at the end of the bar

• Click on any bar to go to the filtered inbox

Sample findings:

• Most Common Problem Categories

• Popular Product Selection

• Common Solutions

"Trends Over Time" Map

Multi-line chart showing performance over time.

Features:

• Smoothed line graph for each field value

• Color-coded lines for easy identification

• Tooltips that appear when the mouse pointer moves, displaying exact figures

• Footer text highlighting the most frequently used value

Use cases:

• Identifying seasonal trends

• Track the evolution of problem types

• Monitor product issues

• Changes in measurement categories over time

Table of all values

A complete, paginated table of all field values.

Features:

• Sortable columns (Value, Number of tickets, Percentage)

• Search function

• Pagination for large datasets

• Click on any row to filter the inbox by that value

Advantages:

• Complete overview of all values

• Easy export and analysis

• Quick navigation to related tickets

Filter tickets by field

Filter your inbox based on the values in custom fields.

​Here's how to filter

1.

Open the filter menu

Click on theFilterButton in the toolbar of your inbox.

2.

Select "Ticket Field"

SelectTicket Sectionfrom the list of filter options.

3.

Select field and value

The following is displayed on the user interface:

• Grouped by field: All fields, grouped by their values

• Search bar: Quick search across all options

• Multiple selection: Select multiple field values

4.

Apply filter

Selected filters are displayed as active filters. The inbox is refreshed and now displays the corresponding tickets.

Filters are preserved in the URL to make sharing and bookmarking easier.

Feldmanagement

​Active fields vs. archived fields

"Active Fields" tab:

• Currently available fields

• As indicated on the tickets

• Can be edited or archived

"Archived Fields" tab:

• Previously used fields

• Not visible on tickets

• Can be restored if necessary

• Historical data has been preserved

Archive fields instead of deleting them to preserve historical data and ensure the accuracy of your reports.

​Rearrange fields

Use drag-and-drop to reorder fields on tickets. The order affects:

• Display order in the ticket field map

• Tab order for keyboard navigation

• Order of columns in the export/report

​Edit fields

Click on any field to open the configuration window and change the following settings:

• Ad name and description

• Field-specific options (e.g., values in the drop-down list)

• AI-powered status

• Required status

• Channel Availability

Changing the field type for existing fields may result in data loss. Instead, consider creating a new field.

Best practices

Field design

Choose clear and concise field names

Use descriptive names that employees can understand right away:

✅ Good: “Product category,” “Type of problem,” “Solution method”
❌ Avoid: “Field1”, “Category”, “Type”

If possible, use a dropdown menu above the text

Dropdown menus offer:

• Consistent data for reporting

• Simpler filtering and analysis

• The AI has clear options to choose from

• Prevents typos and errors

Provide text fields for data in any format.

Enable AI for repeating fields

Suitable candidates for AI:

• Topic categories (can be derived from the conversation)

• Product selection (can be compared with orders)

• Priority level (for assessing urgency)

• Type of solution (can be inferred from the result)

Keep this manual for:

• Internal tracking codes

• Agent-specific notes

• Subjective assessments

Start with fewer required fields

Start with 2–3 essential required fields, and then expand them based on:

• Feedback from agents on usefulness

• Accuracy rates of AI

• Actual data usage in reports

Too many required fields can slow down the processing of transactions.

AI Optimization

Provide unique field descriptions

Help the AI understand the purpose of the fields by providing meaningful descriptions:

✅ Good: “Select the product the customer is asking for from their order history.”
❌ Unclear: “Product area” – The AI uses descriptions as context when analyzing tickets.

Monitor the accuracy of the AI

Review the analytics data to find out the following:

• In which areas is AI making a successful impact?

• Which fields often end up in the "Needs to be checked" category?

• Patterns in AI-driven selection

Adjust the options or descriptions in the dropdown menu to improve accuracy.

Use product categories in store integrations

Product categories work best when:

• Shop integration is enabled (Shopify, WooCommerce, etc.)

• The customer has an order history

• The products have unique names and variants

The AI can then accurately match the terms mentioned in conversations to the actual products.

Performance

Limit the total number of fields per organization

Recommended limits:

• Active fields: maximum 10–15

• Required fields: 3–5 at most

• AI-powered areas: 5–8 at most

Too many fields can:

• Slowing down the loading of tickets

• Overwhelm agents

• Reduce the accuracy of the AI

Archive unused fields

Check the field usage in the analysis regularly:

• Fields in the archive with a usage rate of less than 5%

• Group similar fields

• Remove duplicate or unnecessary fields

This keeps the user interface clear and efficient.

Advanced Features

​Conditional preloading

Product catalogs are preloaded intelligently:

• Is loaded only if the corresponding product field is present on the ticket

• Runs in the background while the agent reads messages

• Cached results are available immediately as soon as the employee interacts with them

This ensures that product fields load quickly without wasting resources on tickets that don't need them.

​Real-time synchronization

All field changes are synchronized in real time via Supabase Realtime:

• The agent fills in the field → The change is immediately updated for all viewers

• AI fills in the field → Displays immediately without requiring a refresh

• Changes to the field configuration → Immediate application to open tickets

Troubleshooting

The field does not appear on the tickets

Possible causes:

1. The field has been archived → Check the "Archived" tab and restore the data if necessary

2. Field is disabled → Switch to "Active" status in the field settings

3. Channel discrepancy → Check whether the enabled channels in the field include the ticket's channel

The AI isn't filling in the fields

Check this out:

1. The "AI-enabled" option is enabled for this field

2. The ticket contains enough contextual information for the AI to analyze it

3. The field type is supported by the AI (all types except pure numerical calculations)

4. Check the logs for the AI's confidence scores (these may be below the threshold of 0.7)

5. For product categories: Make sure that the store integration is active and that the customer has orders

No products are displayed in this product category

Check:

1. The store integration has been set up (Shopify, WooCommerce, etc.)

2. The customer has an order history in the system

3. The login credentials for the integration are valid

4. The products are being synchronized (check the integration settings)

The product catalog is cached for 10 minutes. If you have just added products, please wait until the cache has been updated.

The validation incorrectly blocks the resolution

Context-specific behavior:

• Standard resolution: Only fields that do not require AI are checked (AI fields are filled in automatically)

• Tickets that need to be checked: Check all required fields (AI verification failed; manual entry required)

If the validation appears to be incorrect:

1. Check if the ticket is availableReview requiredStatus

2. Check the "Required" and "AI enabled" settings for the field

3. Make sure the field for the ticket channel is checked

Slow loading of product fields

Performance factors:

• First batch: Retrieves data from the Shop API (may take 2–5 seconds)

• Subsequent shipments: Uses Redis cache (immediately)

• Comprehensive catalogs: Only the 500 most recent products

To be improved:

• Make sure the Shop Integration API is responsive

• Consider reducing the scope of the product catalog at the integration level

• Check the status of the Redis connection

Frequently Asked Questions

Can I change the field type after creating it?

Not recommended. Changing field types can lead to data loss or inconsistencies.

Instead:

1. Create a new field of the desired type

2. Migrate data as needed

3. Archive the old field

This ensures that historical data is preserved and prevents existing reports from becoming inoperable.

What happens to field data when a field is archived?

The data is retained:

• The historical values are retained in the database

• The analyses still work for past periods

• The field is simply hidden for new tickets

You can restore an archived field to reactivate it.

Can customers view or fill out custom fields?

No.Custom fields are only available internally:

• Visible only to real estate agents

• Not displayed in the user interfaces

• Not included in customer notifications

Use fields to collect internal information without revealing operational details to the customer.

How does the AI handle orders that include multiple products?

For product categories, AI:

1. Analyzes conversations to identify the products mentioned

2. Search the customer's orders for matching products

3. Select the specified variant, if available

4. If there are multiple matches, the most recently ordered item is selected

Agents can change the AI's selection at any time if it is incorrect.

Do you have any feedback or feature requests? Please contact Support or send us your feedback via the feedback widget.