How to use advanced reporting tool?

Focus your analysis on specific response segments by applying multilevel filters, choosing visible columns and exporting filtered data.

A general report can show the overall pattern in your responses, but it may not answer questions about one department, audience segment or service area. After collecting data with Porsline’s online questionnaire builder, Advanced Filters help you focus on the responses that matter to a specific decision.

This short video shows how to narrow your collected data without changing the original survey or reviewing every submission manually.

What You Can Do with Advanced Filters

  • Build multilevel conditions for a specific response segment.
  • Narrow the report according to selected answers or criteria.
  • Choose which result columns should remain visible.
  • Edit or delete filters when reporting needs change.
  • Export the filtered data as an Excel or CSV file.

Advanced Filters are most useful when you begin with a clear analytical question. A highly detailed filter is not automatically more useful; each condition should help isolate the group you need to understand.

Where Advanced Filters Improve Survey Analysis

Review Patient Feedback by Service Area

A healthcare manager may need to investigate feedback from one department, physician or service rather than reviewing every response together. In patient satisfaction surveys, a focused filter can isolate the relevant submissions and give the responsible team a clearer dataset for reviewing recurring concerns.

Compare Responses Across Market Segments

A research team may collect answers from several customer types, regions or product-user groups in one study. With market research surveys, Advanced Filters can separate those segments so analysts can examine each group without creating a different questionnaire or export for every audience.

After watching, open a survey that already contains test responses and define one question your full report cannot answer clearly. Build a filter around that question, keep only the columns required for interpretation and check the resulting dataset before exporting it.

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