> ## Documentation Index
> Fetch the complete documentation index at: https://docs.listenlabs.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Appending External Data

> Enrich your Listen Labs study with external data sources for deeper segmentation and analysis

You can enrich your Listen Labs study by appending external data — such as CRM attributes, survey responses, or behavioral logs — and then use that data for segmentation, comparison, and analysis inside the platform. This lets you connect what participants say in Listen with what you already know about them from other sources.

### Key Concepts Explained

**Imported Data**: Additional attributes attached to participants by matching them to rows in an external .csv file using a shared identifier. Once imported, this data becomes available for charts, segments, and filtering.

**Match Identifier**: The unique value used to connect participants in Listen to rows in your .csv — such as a Listen ID, a URL parameter ID, or a panel-provided respondent ID. Every participant is matched row-by-row based on this identifier.

**Post-Import Segments**: After importing data, the imported fields become available as segment criteria — just like screener answers or URL parameters. Use them to create groups based on CRM attributes, survey answers, or other external data.

**Advanced Segments with Imported Data**: Imported fields can be combined with other attributes using AND/OR logic to create highly specific participant groups for comparison.

### Pro Tips

* **Plan ahead**: Decide what external data you'll want to segment on before launching your study. Design your URL parameters and respondent IDs so they match your external data sources.
* **Clean your .csv before uploading**: Remove extra spaces, ensure consistent casing, and verify that your matching identifier column is unique across rows.
* **Ensure your identifier is consistent**: If your matching identifier appears differently in Listen vs. your .csv (e.g., "#221" vs. "221"), the match will fail. Test with a small batch first.
* **Re-upload if needed**: You can re-import updated files — this replaces any previously uploaded .csv data, so you can correct errors or add new fields.

### Quick Reference

**What external data can you append?**

* CRM attributes (plan type, tenure, account size)
* Quantitative survey responses from another tool
* Typing tools or behavioral logs
* Any other structured data stored in a .csv

**What matching identifiers can you use?**

* Listen ID (e.g., #221)
* IDs passed via URL parameters
* Panel-provided respondent IDs
* Any other unique value present in both datasets

**After importing, your data appears in:**

* Bar charts at the bottom of the Details tab
* Segment builder (available as criteria)
* Responses table (as new columns)

***

## Complete Written Guide

### Step 1: Prepare Your .csv File

Before uploading, ensure your file is ready:

1. Include a **unique identifier column** that matches a value present in your Listen study (e.g., a respondent ID or URL parameter value)
2. Clean the file — remove extra spaces, ensure consistent casing, and check that the identifier is unique per row
3. Include any additional columns (CRM fields, survey answers, etc.) you want to bring into Listen

### Step 2: Access the Import Data Feature

1. Open your study and navigate to the **Analysis** tab
2. Click **Details**
3. Scroll to the bottom of the Details page
4. Locate **Import Data** and click **Configure Import**

### Step 3: Upload and Configure Your .csv

1. Upload your **.csv file**
2. **Select the identifier column** from your .csv
3. **Select the corresponding identifier** from your Listen study (Listen ID, URL parameter, panel ID, etc.)
4. The system will **preview how many rows successfully match**
5. Review the match count — if it's lower than expected, check your identifier for formatting inconsistencies
6. Click **Import** to complete the process

### Step 4: Use Your Imported Data

Once imported, your external data is available in three places:

**Bar Charts (Details Tab)**
Imported categorical fields automatically populate as bar charts at the bottom of the Details tab for quick visual exploration.

**Segments**
Imported fields can be used to create Segments, just like screener answers or URL parameters. Go to the Segments button on the Details tab to create groups based on your imported attributes.

**Responses Table**
Each imported field appears as a new column in the Responses tab, allowing you to sort, filter, and review participant-level data with your external attributes visible.

### Step 5: Create Segments from Imported Data

1. Go to the **Segments** button on the Details tab
2. Click **Add segment**
3. Select your imported field as the segmentation criterion
4. Define your groups (e.g., "Enterprise" vs. "SMB" based on a CRM plan type field)
5. For Advanced Segments, combine imported fields with other criteria using AND/OR logic
6. Click **Create Segment Group** and refresh to see the segments reflected in your analysis

#### Frequently Asked Questions

**What happens if some rows don't match?**
Only matched rows are imported. Unmatched rows are ignored and won't appear in charts, Segments, or the Responses table.

**Can I re-upload data?**
Yes. You can re-import updated files — this replaces any previously uploaded .csv data.

**Does imported data affect recruitment?**
No. Imported data is used for analysis only. Recruitment is controlled by screeners and quotas.

**Can imported data be used in Advanced Segments?**
Yes. Imported fields can be combined with other attributes using AND/OR logic in the Advanced Segment builder.

***

**Anything missing?** Let us know at [support@listenlabs.ai](mailto:support@listenlabs.ai) and we'll help you out!