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Discuss your survey

Tell us what you need to understand from your student feedback. Name and email are required; the other fields are optional.

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We’ll use these details to respond to your enquiry. You can also email info@studentvoice.ai.

Feature

Know how much of the student voice your analysis covers

Analyse every valid student comment and report coverage clearly, including categorised and uncategorised rates.

Student Voice Analytics is built for all-comment coverage. Teams can see the proportion of comments analysed, categorised, and left uncategorised, giving clearer confidence in the evidence base.

Discuss your survey

Discuss the source data, reporting question, outputs and delivery window.

Who this is for

Survey teams, quality leads, governance teams, and senior education leaders.

Why it matters

Sampling and high uncategorised rates can weaken trust. If large parts of the student voice are excluded or hidden, leaders may not know whether the analysis reflects the full dataset.

What teams get

Reduce sampling blind spots

All valid comments can be included, so rare but important patterns are less likely to disappear.

Report coverage transparently

Categorised and uncategorised rates help teams understand the limits and strength of the analysis.

Build confidence in governance conversations

Coverage metrics make it easier to explain what was analysed and what remained outside the category structure.

How it works

  1. Load the full valid comment dataset rather than a manual sample.
  2. Classify comments and sentences against HE-specific categories.
  3. Calculate coverage, categorisation, and uncategorised rates.
  4. Include coverage notes in reports and governance materials.

Outputs

Governance and evidence quality

FAQs

Does all-comment coverage mean every sentence gets a category?

No. It means every valid comment is considered. Some sentences may remain uncategorised if they do not fit the taxonomy or contain no substantive feedback.

Why report uncategorised rates?

They make the method more transparent and help teams understand how much of the comment dataset is represented in category reporting.

Is all-comment coverage better than sampling?

For institutional reporting, all-comment coverage reduces avoidable sampling bias and gives leaders a clearer view of the full evidence base.

See the workflow with your team

Discuss the source data, reporting question and outputs your team needs. Explore the worked example before agreeing the scope and delivery window.

Discuss your survey