Data Collection
Data Collection allows you to automatically extract structured information from conversations that you can report on. Track common product issues, return reasons, customer types — or any other details that matter to your business.
You choose the data fields. The AI classifies every conversation for you.
What you can collect
You can capture almost any detail important to your business. For example:
| Example Use Case | What the AI Extracts |
|---|---|
| Product issues | The specific defect or complaint (e.g., not charging, broken part, poor fit) |
| Packaging issues | Mentions of broken seals, damaged containers, missing parts, or leaks |
| Delivery problems | Delay, lost shipment, damaged on arrival |
| Order cancellation | Why the customer wants to cancel (e.g., changed mind, delivery taking too long, ordered by mistake) |
| Customer product interest | What type of product the customer is looking for (e.g., protein powder, multivitamin) |
| Customer type | The customer group defined by your business (e.g., male, female, younger, older, preferred language) |
The possibilities aren’t limited to a list. Define the details that matter most to your team, and the AI will turn those conversations into structured data you can act on.
1. Define what to collect
Create and manage data fields in:
Settings → AI & Automation → Data Collection
Absolutely — here’s the table format with the improved wording for Prompt, exactly as requested:
Field settings include:
| Name | How the field will appear in analytics. |
|---|---|
| Prompt | Instructions that tell the AI when to classify this data, and (optionally) how to choose between the possible values. |
| Possible values | The specific values the AI can assign — this can be detailed categories or a simple Yes / No. |
| Optional field | When enabled, the AI only assigns a value if it finds relevant information in the conversation. (Recommended ON — many fields won’t apply to most conversations.) |
2. How it works
After a conversation is closed/resolved or handed off, the AI:
- Reviews the full conversation
- Identifies which data fields should apply
- Required fields are always evaluated
- Optional fields are only applied when relevant
- Assigns the most appropriate value for each field
- Saves the results for reporting and filtering in analytics
3. Analytics
Insights are available in:
Metrics → Data Collection
You can:
- See how often each value appears
- Compare trends by channel, product, or time period
- Spot rising issues early (e.g., “packaging leaks” increasing)
- Filter conversations by any collected field for deeper analysis
This turns raw conversations into clear, structured data you can use to improve products, operations, and customer experience.
Examples
