# Qualtrics Data Export: Values, Labels, and Missing Answers

Check Qualtrics export fields, values versus labels, missing-answer settings, and line breaks with a worked example and handover template.

- Canonical URL: https://www.harmate.com/en/blog/qualtrics-export-data-analysis
- Author: Harmate Team
- Published: 2026-10-25
- Updated: 2026-10-25T22:48:25.684250+00:00
- Language: en

## Content

# Qualtrics Data Export: Values, Labels, and Missing Answers

Before analyzing a Qualtrics export, check three choices: which fields are included, whether choices use coded values or labels, and how missing answers are represented. Two files from the same survey can contain different-looking cells because export options differ, even when respondents have not changed their answers.

The useful handover is therefore a file plus an export record. It tells the next reader what a number, blank cell, or text passage represents. The worked example below shows how to prepare that record without turning an export setting into an analytical assumption.

## Include the fields the analysis actually needs

Qualtrics distinguishes downloading all fields from downloading fields currently displayed. A limited view may be sufficient for a specific analysis, but an absent column does not prove no answers were collected for that question. Check the [official Qualtrics data export options](https://www.qualtrics.com/support/survey-platform/data-and-analysis-module/data/download-data/export-options/) before handing over the file.

First decide what must remain available: the questions being analyzed, an identifier that supports returning to a response, relevant collection context, and metadata needed to explain scope. You do not need to share every available personal detail. However, removing the only response identifier and then sorting rows weakens the link back to the source.

Record either “all fields” or the selected fields. Inspect the downloaded output rather than relying on its filename. Keep the original export separate from the copy prepared for analysis, and preserve a way to identify which extraction produced that copy.

## A coded value is not necessarily a score

Exporting values uses the choices’ recode values; exporting labels uses the choice text. Qualtrics notes that codes can differ from an expected sequence after choices have been added or removed. Numeric order alone does not explain what the values mean.

**The following example is entirely fictional.** A team examines the arrival experience at a workshop. The question “Where did you receive the practical information?” offers the choices below. These codes have been checked against this particular questionnaire.

| Verified code | Choice label |
|---|---|
| 1 | In the invitation message |
| 3 | On the event page |
| 7 | At the on-site welcome desk |

A cell containing `7` means “At the on-site welcome desk.” It is not a rating out of seven or a better answer than `3`. Averaging that column would not answer a meaningful question about the selected information channel.

Labels can make a file easier for a human reader reviewing the accompanying comments. If a downstream process requires codes, keep the values and provide the verified mapping. In either case, retain the full question wording and instructions: an abbreviated column heading does not adequately describe the variable.

If you have received numeric data without a mapping, obtain or locate the source questionnaire. Do not invent labels or reorder the codes simply to make them look more regular. Where a question truly uses a rating scale, its wording and anchors still determine what the scale means.

## Separate unanswered questions from unseen questions

Qualtrics provides an option to recode questions that were seen but left unanswered. The documentation gives `-99` as that option’s default value and allows a different value to be chosen. **It is not a universal code for every blank**, nor a rule that applies to every Qualtrics export.

Check whether the option was enabled, which value was chosen, and which fields it affects. A question that was not presented because of the survey path must not be interpreted as a negative answer. A blank cell supplied without an export record remains ambiguous until configuration and context have been examined.

In the fictional workshop survey, a question about the welcome desk might be shown only to people who selected that channel. A missing value for everyone else does not indicate dissatisfaction. For someone who was shown the question, an absent answer still does not mean satisfied, dissatisfied, or zero.

Multiple-choice questions also have specific options, including splitting choices into separate fields and recoding unselected options in certain configurations. Record those settings separately. Do not carry the interpretation of a zero from one column to another without checking the question type and selected export options.

## Keep open comments readable in their original context

The option to remove line breaks can turn a comment into a single block. That may look like harmless spreadsheet cleanup, but it can remove a separation the respondent used to distinguish situations. For qualitative reading, preserve the original text and avoid flattening it when unnecessary.

A fictional comment might say, “Before the workshop: I did not have the address,” followed on a new line by, “On site: the team directed me quickly.” A summary labeled “arrival problem” would erase the distinction between advance information and help received on site. Keep both passages, their context, and access to the complete response.

The [open-response analysis method](/en/blog/analyzing-200-open-responses-without-bias-a-method-for-actionable-decisions) explains how to develop findings without losing those contrasts. Here, the comments reveal circumstances that selecting an information channel alone cannot capture. They do not, by themselves, establish how common either experience was among people who did not respond.

## An export record to send with the file

This is a working template, not a required Qualtrics format. Complete it from the file and settings actually used.

| Item | Record to keep |
|---|---|
| Source and snapshot | Survey, known version, extraction date and time, collection period, and filters. |
| Included fields | All fields or a detailed selection; retained response identifier. |
| Choice representation | Values or labels; verified mapping when values are used. |
| Missing answers | Whether recoding was enabled, the chosen code, and conditional-question context. |
| Multiple choices | Whether fields were split and which unselected-option settings were used. |
| Open text | Line breaks preserved or removed; access to the original. |
| Review performed | A few rows checked against the questionnaire and any remaining limitations. |

Include a row with a recorded answer, a missing value, and, where relevant, a conditional or multiple-choice question in that review. This targeted check cannot prove the entire file is correct; it can expose a mistaken interpretation before it spreads through the analysis.

If you must combine files, continue with the [guide to preparing survey responses before analysis](/en/blog/prepare-survey-responses-before-analysis-a-practical-method-and-example). Matching export options alone do not establish that questions or populations are comparable. Preserve the separate snapshots until the relationship between them has been checked.

You can then [manually import a compatible file into Harmate](/en/product/response-import) as CSV, JSON, or XLSX and review the column mapping. The export record and the interpretation of codes remain your responsibility. This is not a Qualtrics connector, and it does not automatically reconstruct export settings, the source questionnaire, or the meaning of missing values.