Skip to main content
Every data project in VoxDash requires an SPSS file to facilitate further analysis.

​
Key Components of a Good SPSS File

A well-structured SPSS file should include:
  1. Comprehensive Question Labels – Ensure that all survey questions are clearly labeled in the “Label” field within the SPSS application. This helps in understanding the context of the data during analysis.
  2. Meaningful Response Values – Each response option should have a corresponding descriptive value in the “Value” column. Meaningful value labels allow for easier interpretation and reporting of data.
spss file overview

​
Structuring Survey Data in SPSS

Survey datasets typically include a set of questions (variables) and corresponding answers (values). In SPSS, responses are often stored as numeric codes, which allow VoxDash to process and analyze large datasets efficiently. For instance:
QuestionResponse CodeResponse Label
Q1_Satisfaction1Very Satisfied
Q1_Satisfaction2Satisfied
Q1_Satisfaction3Dissatisfied
This structure helps VoxDash recognize patterns, identify trends, and generate meaningful insights.

​
Best Practices for Data Structure

To optimize your SPSS file for use in VoxDash, follow these best practices:
  • Use numeric codes for all closed-ended responses, with clear and consistent value labels.
  • Include open-ended text responses where necessary. VoxDash uses AI to automatically code open-ended text and store both the original text and its corresponding numeric value. (Learn more in AI-Open-Ended Analysis)
  • Avoid duplicating questions Do not repeat the same question across multiple columns for different responses.
❌ Example (Incorrect): Q1_Response1, Q1_Response2, Q1_Response3, Q1_Response4 ✅ Example (Correct): One variable Q1 with multiple coded response options. Duplicating questions can interfere with trend analysis and time comparisons, especially in recurring or longitudinal surveys.

​
Optimizing SPSS Data Entry for VoxDash

When you upload your SPSS file to VoxDash, the second and third wizard steps allow you to create shortcuts, hide variables, or manage mappings. To streamline this process, you can set up these preferences directly in your SPSS file before uploading.

​
Naming Conventions

To facilitate automatic processing in VoxDash, follow these naming guidelines:
  1. Shortcuts:
    • Use the prefix Shortcut_ to mark variables you want to access quickly in VoxDash. These variables are often used for filtering, crosstabs, or quick dashboard analytics.
    • Example: Shortcut_Age, Shortcut_Income.
VoxDash will automatically create shortcut fields for these variables, making it easier to segment or compare survey responses.
  1. Survey Administration Question Variables:
    • Use the prefix Hide_ for variables you want to exclude from analysis. These are typically internal fields or incomplete questions.
    • Example: Hide_TestVariable, Hide_InternalNotes.
Hidden variables remain in your dataset but are not included in VoxDash visualizations. You can still view them later if needed.
  1. Map Variables:
    • Use the prefix Map_ for variables representing geographic or hierarchical mapping information.
    • Example: Map_Testprovince
Mapped variables help VoxDash identify the geographic scope of your data (e.g., country, province, or region). This is especially useful for geo-based analysis or when visualizing results by location. By following these conventions, VoxDash will automatically recognize and apply these changes, reducing the need for manual adjustments during the second wizard step.

​
Summary

To ensure a smooth data analysis process in VoxDash:
  • Include clear question labels and meaningful value labels.
  • Keep your data well-structured, avoiding duplicated variables.
  • Apply naming conventions (Shortcut_, Hide_, Map_) for easier processing.
  • Prepare open-ended responses for AI-based coding if applicable.
Following these best practices will make your VoxDash project setup faster, your analytics more accurate, and your reporting more consistent.