What Export Gives You
Export turns survey submissions into analysis files. Download CSV for scripts, Stata .dta for Stata 14+, SPSS .sav, or R .RData to load directly with load() — no haven or labelled package needed — and keep assigned conditions, quota fields, completion metadata, response-quality fields, and any randomized display order in the same download.
Open the Export tab after you have at least one test response. Use it as a prelaunch audit: the exported file should tell the same story as the questionnaire, Flow diagram, quotas, and codebook.
Export: Data Output
Before Exporting
Step 1: Open Preview. Complete at least one test response before relying on Export.
Step 1: Open Preview
Step 2: Check variables in Block Builder. Confirm question names and recodes are readable before live collection.
Step 2: Check variables in Block Builder
Step 3: Check Flow data. If the survey uses experimental conditions, verify that condition assignments are recorded as expected.
Step 3: Check Flow data
Step 4: Check randomization fields. Include ordering data when shuffled answers, rows, columns, sliders, or blocks affect interpretation.
Step 4: Check randomization fields
Step 5: Open Export. Use the Export tab to download the file and inspect headers.
Step 5: Open Export
Step 6: Back up before major edits. Download a backup before changing a live survey's wording, answer options, quotas, or conditions.
Step 6: Back up before major edits
Data To Review
- Answers: responses from each question type, including open text, scale values, matrix rows, rankings, and specialized tasks.
- Condition picks: assigned arms for experimental condition sets and any assignment-relevant variables.
- Randomized order snapshots: answer, row, column, slider, block, conjoint, or stimulus order when exported.
- Quota-relevant variables: fields needed to understand sample targets, eligibility, and rerouting.
- Completion data: status, end screen path, timestamps, and any completion-code workflow allowed by the protocol.
- Quality fields: response-quality score, flags, flag details, review source, review tags, rule matches, and cleaning action.
- Metadata: respondent context available for the survey, plus fields needed for cleaning and reproducibility.
Export: Data Output
Analysis Notes
Keep a codebook that explains question wording, answer recodes, condition arms, exclusions, and any mid-field changes. If you use randomized display order, decide whether order will be a control variable, diagnostic field, or audit field in your analysis. For multilingual projects, document respondent language and translation choices; see Multilingual Research Surveys.
After live launch, download backups before changing wording, answer options, quotas, Flow, or end screens. If you use quality review, archive the cleaning log with the raw export and codebook. If you pull data with scripts, compare API output with a manual export at least once; see Pull Survey Responses With the API and Troubleshoot API Response Pulls.
Export: Data Output
Open The File In Stata Or R
From the Export tab you can download a Stata .dta file with variable labels and value labels applied, an R .RData file, or a replication package that also includes Codebook.csv and an R script that loads the files. In Stata, open the .dta directly. In R, load("Responses.RData") gives you a responses data frame with real base-R factors and variable labels already applied — no package needed; use haven::read_dta("Responses.dta") instead only if your workflow specifically needs the Stata file. Randomized display-order columns stay in every format so you can control for or reconstruct order effects.
If you only need a codebook for labeling, download Codebook.csv or pull it from the API; see Survey Codebook in R and Pre-Analysis Files and Pull Survey Responses With the API.
Export: Stata, R, and codebook files