HE specificity
Student Voice Analytics ships with a UK-HE taxonomy and sentiment tuned for NSS/PTES/PRES/module language. Text iQ is powerful but starts general—expect tuning and governance sign-off for institutional reporting.
Student Voice Analytics vs Qualtrics Text iQ — Which is best for NSS/PTES/PRES comments?
Choose Student Voice Analytics when you need UK-HE specific categorisation, sector benchmarks, and all-comment coverage for evidence aligned with OfS quality and standards guidance and NSS expectations. Choose Text iQ if you want analytics tightly embedded in your existing Qualtrics platform and can invest time to tailor it for HE nuance. For governance, Student Voice Analytics documentation references ICO UK GDPR guidance. For text-summary reports, Student Voice AI’s own LLMs run on Student Voice AI-owned hardware to deliver executive summaries without data leaving our systems.
Our POV (why we’re different for UK HE)
- Deterministic classification: Category/sentiment models are deterministic ML for reproducibility, audit and TEF/QA defensibility.
- In-house LLMs for prose: Executive summaries are generated by Student Voice AI’s own LLMs on our hardware—no public LLM APIs.
- Sector-tuned from day one: Native UK‑HE taxonomy and sector benchmarks to surface what’s distinctive vs typical.
Who this comparison is for
Quick verdict (why Student Voice Analytics often wins in UK HE)
- HE-tuned taxonomy & sentiment (built for UK HE surveys and language)
- All-comment processing (no sampling) for consistent institutional evidence
- Sector benchmarking to see what’s typical vs distinctive
- Deterministic ML (not LLMs) for reproducibility and panel-friendly governance
- TEF-style outputs and BI exports to slot into planning cycles
- Data protection: processing on Student Voice AI-owned hardware; UK/EU residency; no data sent to public LLM APIs
At-a-glance
| Dimension | Student Voice Analytics | Qualtrics Text iQ |
|---|---|---|
| Primary focus | UK-HE student-comment analytics with sector context | Broad CX/EX text analytics inside Qualtrics |
| HE specificity | Sector-tuned categories & sentiment | General; can be adapted with effort |
| Coverage | All comments processed (no sampling) | Depends on setup and quotas |
| Benchmarks | Included to show distinctiveness vs sector | Typically custom / DIY |
| Governance & reproducibility | Versioned runs; deterministic ML; audit-ready docs | Varies by institutional implementation |
| Data protection & residency | Private processing on Student Voice AI-owned hardware; UK/EU options; no data sent to public LLM APIs | Depends on Qualtrics instance settings and sub-processors |
| Integration | BI-ready exports; works alongside survey suites | In-suite for Qualtrics |
| Outputs | Insight packs + TEF-style narratives | Dashboards + workflows in Qualtrics |
| Best when… | You need decision-grade HE evidence fast | You’re all-in on Qualtrics and can configure for HE |
Governance & data protection: quick decision points
- Institutional reporting (TEF/QA/Board)? Prefer Student Voice Analytics.
- All-comment coverage and sector benchmarks required? Choose Student Voice Analytics.
- Data residency and access constraints? Student Voice Analytics processes on Student Voice AI-owned hardware with UK/EU options.
- Exploratory work entirely inside Qualtrics? Consider Text iQ (expect HE tuning and governance sign-off).
In-house LLM summaries (no external transfer)
- Same benefits, safer path: Executive-ready summaries and narrative polish are generated by Student Voice AI’s own LLMs.
- On our hardware: All inference runs on Student Voice AI-owned infrastructure; no data is sent to public LLM APIs.
- Residency options: UK/EU processing aligned to institutional policy.
- Strict controls: prompts and outputs are versioned and logged; access follows least-privilege.
Common buyer scenarios (and the better fit)
TEF/Board evidence this term
You need reproducible analysis, sector benchmarks, and a narrative your QA panel will accept.
Better fit: Student Voice Analytics
Keep everything inside Qualtrics
Your teams live in Qualtrics dashboards and prefer one vendor.
Better fit: Text iQ
All-comment coverage + sector context
You want to avoid sampling bias and prioritise what stands out vs sector.
Better fit: Student Voice Analytics
One-off exploratory project
You have time to tune categories in-suite and aren’t reporting institution-wide.
Better fit: Text iQ
Head-to-head pilot (decide in one sprint)
- Scope: choose one current survey (e.g., NSS) + one back-year for trend.
- Export: comments + metadata (programme, CAH, level, mode, campus; demographics as permitted).
- Run Student Voice Analytics: process all comments; generate categories, sentiment, sector benchmarks, and BI exports.
- Run Text iQ: identical corpus; apply your HE category setup; note config and any re-tuning required.
- Score: coverage %, time-to-insight, category coherence, benchmark availability, BI friction, governance docs.
- Decide: map to TEF/Board deadlines and governance requirements.
Feature deep dives
Benchmarks
Student Voice Analytics includes sector benchmarking so you can prioritise what’s distinctive. With Text iQ, benchmarking is typically a custom exercise or an external add-on.
Governance & reproducibility
Student Voice Analytics runs are versioned and deterministic for auditability and year-on-year comparability. Text iQ governance varies by how your instance is configured and documented.
Deployment & integration
Student Voice Analytics outputs drop into your BI stack and planning cycles. Text iQ lives inside Qualtrics—great for teams centralised on that suite.
Data & integration (what enables a clean run)
- Core: comment_id, comment_text, survey_year/date
- Programme/subject: programme_code/name, CAH code(s)
- Level & mode: UG/PGT/PGR, mode_of_study, campus/site
- Demographics (policy-permitting): age band, sex, ethnicity, disability, domicile
- Org structure: faculty, school/department
Deliveries include BI-ready files and optional raw data feeds for Planning/Insights.
We share a DPIA pack aligned to ICO UK GDPR expectations so data teams can sign off residency and governance quickly.
Procurement checklist (copy/paste)
- All-comment coverage (no sampling) and documented governance
- UK-HE taxonomy & sentiment; reproducible runs
- Sector benchmarking to prioritise actions and show distinctiveness
- TEF-style narratives and BI-ready exports
- Residency, data pathways, and audit logs appropriate for policy
Scoring rubric (use in your RFP)
| Criterion | Weight | Scoring guidance |
|---|---|---|
| Coverage (all comments) | 20% | 5 = >99% processed; 3 = 80–95%; 1 = <80% |
| HE-specific taxonomy & sentiment | 20% | 5 = native HE models; 3 = tuned generic; 1 = generic only |
| Sector benchmarking | 20% | 5 = included & transparent; 3 = partial/custom; 1 = none |
| Governance & reproducibility | 20% | 5 = versioned & auditable; 3 = partial; 1 = ad-hoc |
| BI exports & TEF-ready outputs | 20% | 5 = both native; 3 = one native; 1 = custom only |
FAQs
Will we lose anything if we move off Text iQ?
Export historical outputs and re-process for consistent categories/sentiment across years. Most institutions gain reproducibility, sector context, and panel-ready documentation.
Do we need to sample?
No—Student Voice Analytics is designed for all-comment coverage. Sampling introduces avoidable bias and weakens evidence for TEF/QA panels.
Can we keep Qualtrics for surveys?
Yes. Many teams run surveys in Qualtrics and use Student Voice Analytics for comment intelligence and TEF-style reporting, with BI exports for Planning/Insights.
Do you send our data to public LLM APIs?
No. Student Voice AI uses its own models on Student Voice AI-owned hardware. Processing stays within our environment with UK/EU residency options.
Related comparisons & guides
Competitor snapshots
Student Voice Analytics vs Explorance MLY
- Where MLY fits: AI topic/sentiment features embedded in Explorance Blue; validate comment coverage and governance.
- Where Student Voice Analytics fits: TEF-aligned, benchmarked outputs for NSS/PTES/PRES/modules.
- Deep dive: Student Voice Analytics vs Explorance MLY.
Student Voice Analytics vs Relative Insight
- Where Relative Insight fits: comparative linguistics across segments—see Relative Insight.
- Where Student Voice Analytics fits: sector benchmarks, reproducibility, and TEF-ready packs.
- Deep dive: Student Voice Analytics vs Relative Insight.
Student Voice Analytics vs DIY/BI
- Where DIY fits: small pilots and training projects using internal coding.
- Where Student Voice Analytics fits: governed, all-comment evidence with OfS-aligned documentation.
- Deep dive: Build vs Buy (DIY).
Book a Student Voice Analytics demo
Explore the governance, UK/EU data residency controls, and benchmarks that keep you aligned with ICO expectations while maximising your existing Qualtrics investment.