# Data Enrichment

### Overview

Data enrichment allows you to merge external participant data with your study results — adding demographic, behavioural, or contextual information you already hold into the same dataset as your survey responses. This eliminates the need to re-ask questions participants have already answered elsewhere, and enables deeper cross-analysis of your results.

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<figure><img src="https://358667285-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FzMRQUXiGQlBwWdg6WEmG%2Fuploads%2F3cvnCiUGaBP0quvVtXeR%2FScreenshot%202025-10-29%20at%2017.25.46.png?alt=media&#x26;token=0b2494f4-b0e4-4e23-a31d-087d9b8bd9bf" alt=""><figcaption></figcaption></figure>

### How It Works

#### The Matching Process

1. Navigate to the **Table Data** tab in your study results
2. Click **Enrich**
3. Upload a CSV or Excel file containing your existing participant data
4. Yazi matches each row in your uploaded file to the corresponding participant in the study using the **phone number** as the matching key
5. Matched data appears as additional columns on the right side of the table, alongside your study responses

> **Important:** Your enrichment file must contain a phone number column, formatted consistently with the phone numbers in your study data (including country code). Mismatched formats will result in failed matches.

<figure><img src="https://358667285-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FzMRQUXiGQlBwWdg6WEmG%2Fuploads%2FOHAvkPTezieqHjRCGR4Y%2FScreenshot%202025-10-29%20at%2017.26.15.png?alt=media&#x26;token=bef2cd7a-6bd1-46e2-8c2a-0376945528e2" alt=""><figcaption></figcaption></figure>

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### What You Can Enrich With

#### From Recruitment Screeners

If your recruitment agency collected qualifying data before participants entered the study, upload that screener data to enrich your results:

* **Demographics** — age, gender, income, education, location
* **Behavioral data** — product usage, brand ownership, purchase frequency
* **Segment classification** — which quota cell each participant belongs to

This means you don't need to re-ask demographic questions inside the study itself, keeping the study shorter and improving completion rates.

#### From Your CRM or Customer Database

Merge internal customer data with survey responses to cross-analyse attitudes with actual behaviour:

* **Customer tier** — premium vs. standard vs. new customer
* **Purchase history** — recent purchases, average spend, product category
* **Account status** — active, dormant, churned
* **Tenure** — how long they've been a customer

#### From Previous Studies

Upload results from an earlier research wave to track changes in attitudes or behaviour over time:

* Map responses from Wave 1 to Wave 2 participants
* Compare individual-level changes across survey periods
* Identify participants whose views have shifted significantly

<figure><img src="https://358667285-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FzMRQUXiGQlBwWdg6WEmG%2Fuploads%2FVcvJnSyqlgD7hHPtzM1A%2FScreenshot%202025-10-29%20at%2017.26.57.png?alt=media&#x26;token=4d41d610-6041-4054-98ea-16f03aa4d392" alt=""><figcaption></figcaption></figure>

#### From Panel Providers

If using a recruitment panel, the provider may supply additional participant attributes:

* **Panel ID** — for tracking and incentive reconciliation
* **Profile data** — pre-verified demographics from the panel database
* **Study participation history** — other studies this participant has completed

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### CSV Format Requirements

Your enrichment file should be structured as:

| phone\_number | field\_1 | field\_2 | field\_3 |
| ------------- | -------- | -------- | -------- |
| +27821234567  | Female   | 28       | Premium  |
| +44771234567  | Male     | 34       | Standard |

**Requirements:**

* **Phone number column is mandatory** — this is the only matching key
* **Country codes must be included** — format consistently with your study data
* **Any additional columns** will be imported as enrichment fields
* **Column headers** become the field names shown in the table
* **No limit on additional columns** — add as many enrichment fields as needed

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### Viewing Enriched Data

Once enrichment is complete, your table expands to show:

* All original study responses (left side)
* All enrichment fields (right side, clearly separated)

You can then:

* **Filter by enrichment fields** — show only female participants, or only premium customers
* **Sort by enrichment data** — order results by age, customer tier, or any other field
* **Export combined data** — download the full enriched dataset as Excel or CSV
* **Use in Graph Data cross-tabs** — cross-tabulate survey responses by any enrichment field

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### Use Cases

| Scenario                        | What You Enrich With                             | What You Gain                                              |
| ------------------------------- | ------------------------------------------------ | ---------------------------------------------------------- |
| **Customer satisfaction study** | CRM data (customer tier, tenure, purchase value) | Understand how satisfaction varies by customer value       |
| **Product trial feedback**      | Screener demographics                            | Analyse responses by age, gender, income without re-asking |
| **Panel research**              | Panel profile data                               | Leverage pre-verified demographics for deeper analysis     |
| **Longitudinal tracking**       | Previous wave responses                          | Compare individual-level attitude changes over time        |
| **Employee research**           | HR data (department, tenure, location)           | Cross-analyse feedback by team or seniority                |

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### Known Limitations

* **Phone number matching only** — the only matching key is phone number. If participants used a different number to complete the study than the one in your enrichment file, they won't be matched.
* **Format consistency** — phone numbers must be in exactly the same format in both files. A number with a + prefix in one file and without in another will not match.
* **No automatic re-enrichment** — if you update your enrichment file, you'll need to re-upload it to refresh the data in the table.
* **Enrichment is per study** — enrichment data applies only to the study you uploaded it to. It does not carry across to other studies.