1. Overview
The Wide format presents each respondent as a single row, with each survey question represented as a separate column. This format is particularly useful when you want to:
- Run statistical analysis or modeling in packages like SPSS, R, or Python.
- Use dashboards or BI tools that expect one record per respondent.
- Quickly view all answers for a respondent in one row.
2. File Structure & Layout
Each row is one respondent. Each column is a question, an expanded option/topic or a metadata field. Headers use normalized stable reporting IDs, following the same naming rules as SPSS variable names.
The reporting ID identifies the source question. The exported column name is its normalized, file-safe identifier, with an indexed suffix when the question expands. The reporting label is the readable name used for analysis, while question text preserves the original wording. For example, how-old-are-you, how_old_are_you, Age and How old are you? are four different fields for the same question.
Names use letters, digits and underscores. Punctuation is normalized to underscores and outer underscores are removed. A name that does not start with a letter, or consists only of V followed by digits, receives a q_ prefix; an empty normalized name becomes column. Names are limited to 50 characters in these exports.
Expanded questions use _1, _2, and subsequent indexed suffixes for options or topic combinations. Numbering follows the survey-definition option and topic order, with deterministic natural ordering for values without a defined order. The suffix is a column index, not the respondent's selection rank. Changing readable labels does not rename the source ID; changing the question definition or option order can change its expansions.
Normalization, truncation and case-insensitive name collisions are resolved using deterministic hash suffixes derived from the source identifier. Indexed endings are retained where possible. Always use the supplied map or codebook to identify the resulting name rather than recreating it from a label.
Example (first 5 columns):
The export begins with respondent metadata such as respondent_id, status, weight, start_time, end_time and duration, followed by question columns. Available sequence and quality fields also belong to the leading metadata block; identify columns by their headers rather than fixed positions. A respondent can have a partial interview, so do not assume an end time means Complete.
When sequence metadata is available, respondent_sequence identifies the respondent's survey-wide ordinal. Filtering rows does not renumber it, so gaps are normal. It can be empty if the underlying marker is missing; older datasets without the metadata keep their previous columns. The Data Map identifies the field when present.
These actual headers map to the corresponding Data Map entries:
| Exported column / SPSS variable | Stable reporting ID | Readable reporting label | Original question text | Option/topic |
|---|---|---|---|---|
how_old_are_you | how-old-are-you | Age | How old are you? | — |
quota_quads | quota-quads | Quads | quota-Quads | — |
which_of_the_following_brands_have_you_heard_of_1 | which-of-the-following-brands-have-you-heard-of | Which of the following brands have you heard of? | Which of the following brands have you heard of? | Diet Mountain Dew |
which_of_the_following_brands_have_you_heard_of_2 | which-of-the-following-brands-have-you-heard-of | Which of the following brands have you heard of? | Which of the following brands have you heard of? | Canada Dry Ginger Ale |
3. Key Columns
respondent_id— respondent identifier.status— respondent status; filter to Complete for completed-interview analysis.weight— statistical weight.start_time,end_time,duration— recorded timing metadata.- Question columns — normalized reporting IDs with indexed suffixes for expanded options or topic combinations.
The standard export places metadata columns before question columns.
Compatibility: these identifiers replace previous V###_descriptive_label headers. Update scripts, saved SPSS syntax, joins and BI imports that match the previous headers or readable labels. Use a fresh data map or codebook to build the old-to-new mapping, verify expanded options, and retain that mapping with the export. Do not assume an old positional variable number is a reporting ID.
4. Data Representation
Single-choice questions
Stored as one column per question with the selected answer recorded.
Multi-choice questions
Each option is represented as a separate column. Values indicate whether the option was selected, and may also include rank order (e.g., -1 = not selected, 1 = selected first, 2 = selected second, etc.).
Numeric questions
A coded export can contain reporting categories, such as 55+ for Age. Choose the uncoded export for underlying numbers such as 62.
Open-end questions
The coded export can include coded categories. Choose the uncoded export when you need the original verbatim text; check the Data Map to identify the exported representation.
Uncoded exports
The Wide format is also available as an uncoded export. Where a standard export returns a question's recoded category, the uncoded export returns the underlying response value as it was captured. This is useful when you want to inspect or re-derive the original answers rather than work from the recoding applied for reporting. Select the uncoded option in the download dialog; the file structure is otherwise identical.
Numeric-coded wide Excel
Select Numeric-coded Data in Excel (Wide) for SPSS-compatible numeric codes in an Excel workbook. It shares the wide layout and stable exported field names with the other wide formats. Data Map maps export_value to the original response_value and readable response_label.
Categorical codes identify answers; they are not measurements. Numeric and rating values retain their appropriate numeric representation, and multi-choice fields preserve selection-order and non-selection conventions. Use the map for missing and special values rather than assuming every number has the same meaning. The standard wide export uses readable reporting values; the uncoded export returns captured values.
Respondent quality metadata
Available quality_suspect_score, quality_duplicate_detected and quality_termination_reason fields appear before question columns. Each uses the latest recorded value for that respondent. Scores retain their measured 0–5 values in the numeric-coded export; unavailable evidence remains missing. Duplicate findings and termination reasons use the value representation described in Data Map.
The quality_ names identify metadata. A survey question that would collide with one of these identifiers is given a distinct exported identity; use the map to distinguish the question from the quality field. See Respondent quality fields for interpretation and the distinction between evidence and actual exclusion.
Respondents included
Wide raw exports include non-complete respondents as well as completes, so partial interviews appear in the file. Filter on respondent status where your analysis should be restricted to completes.
5. Missing & Special Values
- -1 often denotes an option that was not selected in multi-choice or rank questions.
- Empty cells may indicate a skipped or non-applicable question.
- "Prefer not to say" appears as a standard response category.
Data Map worksheet
The workbook includes a Data Map worksheet alongside Data. Use it to trace every exported column back to its source question before renaming fields or building an analysis script.
Join a Data header to export_column. Read reporting_id, reporting_label, question and question_type for its source, and generated_column_source for an expanded option or topic. export_value, response_value and response_label explain the value mapping. Several map rows can describe one column's values; the map is not one row per respondent. Open-ended verbatim values are not repeated in it.
For the full download and data-map workflow, see Downloading data and reports.
6. Weighting
- Apply the weight column when analyzing results to ensure the dataset reflects the target population.
7. Best Practices
- Keep the Data Map with the Data worksheet.
- Join across formats through the map's stable reporting ID and option/topic context, not column position or the readable label.
- Inspect
statusbefore choosing the analysis population. - Use the map's value definitions when handling non-selections, missing data and selection order.
- Choose coded or uncoded exports deliberately; changing the value representation does not make the readable label the column identifier.
8. Stacked Exports
The Wide format supports stacked exports, where the data is organized by the tags assigned to each question in the survey editor. In a stacked export, each respondent row is repeated for every tag group, and only the columns belonging to that tag are included alongside the respondent identifier and metadata columns (weight, timing).
This is useful when your survey covers multiple topics or when you want to analyze tagged sections independently. For example, if your survey tags questions as "Demographics," "Brand Awareness," and "Purchase Intent," the stacked export will produce a row for each respondent under each of those tag groups, with only the relevant question columns present in each row.
To generate a stacked export, select the Stacked option in the download dialog. The resulting file will contain a Tag column indicating which tag group each row belongs to.
9. Row Limits
Excel files have a maximum number of rows, and a very large survey — particularly a stacked export, where each respondent is repeated per tag group — can exceed it. If an export would produce more rows than Excel supports, the download fails with a clear error explaining the limit rather than producing a truncated or corrupt file. If you hit this, export in CSV or SPSS format instead, or reduce the scope of the export.
10. When to Use Wide Format
- For statistical modeling and regressions.
- When using survey data in BI dashboards or visualization tools.
- When analysts want one record per respondent with all answers side by side.
- When using the stacked option, for analyzing tagged question groups independently or feeding structured sections into BI tools.