Sloppy open-end classification


You can access the Sloppy open-end classification tab on your Participants page to review AI-powered classifications of open-ended responses, grouped by result category, and take bulk actions on respondents within each group.

Sloppy open-end classification main table

How it works

The feature uses a large language model to classify each participant’s open-ended responses into one of four categories:

Category of responsesSignalDescription
Carelessopen-end-carelessResponses that are overly brief, vague, or fail to address the question adequately
Copy-pastedopen-end-copy-pastedResponses that appear to be copied and pasted from other sources
Keyjammingopen-end-keyjammingResponses containing nonsensical or gibberish characters
Goodopen-end-goodResponses that are relevant and related to the survey question

Clicking the number of participants opens a modal where you can review each respondent’s response text, quality rating, and inclusion status, and exclude specific participants from your analysis as needed.

Detailed respondent view

You can also click Actions for all respondents to apply inclusion, exclusion, or reset quality assessment actions to all respondents in that category.

When this feature is available

The Sloppy open-end classification tab is available when your experiment meets the following requirements:

  1. Your experiment includes at least one analysable open-ended question.
  2. Your team has not disabled LLM features in team settings.
  3. LLM features are not disabled for the primary owner of the experiment.

Enabling the analysis

If the detection of sloppy open-ended responses is switched off, you can click on the Detect sloppy open-ended responses to enable the analysis.

Please note that enabling this setting will incur a fee of USD 0.10 per complete response with an open-end, charged to your team’s balance. This fee does not apply to responses where the sample is supplied by Conjointly.

Conjointly strongly recommends turning on this quality check when working with your own panel sources, as it not only improves the quality of your sample but also helps you save on sample costs by avoiding payment for fraudulent entries.

Once enabled, the tab will load with the full classification results.