Panoplai supports weights but does not calculate them for you. If you need help creating a weighting scheme, consult your research or statistics team.
Why Use Data Weights?
Weights help correct for sample imbalances and ensure that your results reflect the target population—not just the sample that responded.
You might use weights if:
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Your sample doesn’t match key quotas (e.g., too many younger respondents)
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You want to compare across markets or groups with different sizes
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You’re combining datasets that should be normalized against a common population
Weights can be applied to a full dataset or to specific respondents based on demographic or behavioral attributes.
How to Apply Weights in Panoplai
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Go to your study in the dashboard.
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Click the Manage Weights button.
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Export the list of Respondent IDs (RIDs)
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Append the corresponding weights to each participant ID
- Save as a CSV
- Upload your CSV file back into Panoplai.
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Once successfully uploaded, you’ll see a new toggle at the top of the dashboard: Use Weights — switch this on to apply your weights to charts, tables, and AI Conversations.
Notes & Best Practices
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Each RID must be unique in your CSV and must match exactly to your dataset.
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Weights should be numerical.
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Applying weights won’t modify your raw data—it only affects how data appears in the dashboard when weights are toggled on.