Koji vs Snap Surveys for Course Evaluation (2026): Honest Comparison

Snap Surveys and Koji solve the same institutional problem — understanding what students think about their courses — but from opposite ends of the methodology spectrum. Snap Surveys, through its Snap XMP platform, is a mature, flexible questionnaire tool with deep roots in UK and European higher education, including course evaluation systems and national survey delivery. Koji is an AI-native platform that replaces static questionnaires with AI-moderated conversational interviews and automatic thematic analysis. If your team is choosing between them in 2026, the decision comes down to whether you want a highly configurable survey engine or a system that produces standardized qualitative evidence at scale.

This comparison is written for QA directors, heads of teaching and learning, and institutional-research leads at European universities. We represent Snap Surveys accurately using its own published materials, and we are explicit about where each tool is the better fit.

The short answer

Choose Snap Surveys if you need a proven, self-hostable or UK-ringfenced survey platform, complete control over questionnaire design and print/scan/mixed-mode data collection, and you are comfortable with manual analysis of open-text comments.
Choose Koji if your priority is rich qualitative feedback that is analysed automatically — AI-moderated interviews that probe follow-up answers, bias-aware standardized moderation, thematic analysis across cohorts, and closing-the-loop action tracking that produces accreditation-ready evidence.

What Snap Surveys does well

Snap Surveys is a long-established British survey-software company. Its current platform, Snap XMP, is used across higher education to run course evaluation systems, student satisfaction surveys, and to support national exercises such as the National Student Survey (NSS). According to Snap's own documentation, the platform offers:

A flexible questionnaire builder with a wide range of question styles — single- and multi-response, rating scales, ranking, open-ended, plus interactive styles such as image selection and slider questions.
A course evaluation template to create a standard survey quickly, which institutions can then customise by editing text, adding images, and adding questions.
Personalised student access: students log in to see a list of all courses for which feedback is required, along with the completion status of each, and can respond on any device, 24/7.
Smart Reports that generate real-time reporting on course satisfaction as a mean score, response levels per instructor, and all student comments, with benchmarking between departments, courses, instructors, and the whole institution.
Mixed-mode collection, including a heritage in paper/scanning workflows that many survey-only tools never offered — genuinely useful for institutions that still run in-hall paper evaluations.
Strong data-governance options: Snap XMP clients can choose how and where data is hosted, including a "ringfenced UK" solution, with security aligned to ISO 27001:2013. Snap is also Cyber Essentials Plus accredited and offers a self-hosting option — attractive for institutions with strict compliance requirements.

As of publication, Snap's public pricing is listed in US dollars, billed annually: a free Starter tier (200 responses), an Advanced tier at 30 USD per month (up to 50,000 responses), an Elite tier at 95 USD per user per month, and a quote-based Ultra tier. Note that higher-education deployments are typically quoted institutionally, so treat the public tiers as indicative rather than the price you will actually pay.

These are real strengths. For an institution that wants total control over survey design, values self-hosting or UK-ringfenced data, and has staff capacity to read and code open-text comments, Snap Surveys is a credible, battle-tested choice.

Where the survey model reaches its limits

The constraint is methodological, not a knock on Snap's engineering. A questionnaire — however flexible — collects the answers you thought to ask for. When a student writes "the assessment was confusing," a survey cannot ask which assessment, what was confusing, or what would have helped. The insight that matters is in the follow-up you never got to ask.

Three practical consequences follow for course evaluation specifically:

Shallow open text. Free-text boxes on end-of-term surveys are famously thin: many students leave them blank or write a few words. There is no interviewer present to probe, so the qualitative signal is limited.
Manual analysis at scale. Snap's Smart Reports surface comments and mean scores, and Snap uses technology to check text quality and to flag plagiarism or generative-AI-written responses — but turning hundreds of free-text comments into reliable themes is still largely manual coding work. Across a faculty or a whole institution, that is a real staffing cost.
Rating-scale bias. Standard SET (student evaluation of teaching) instruments carry well-documented risks — halo effects, leniency/severity variance between cohorts, and the sensitivity of numeric ratings to question wording. A static instrument standardizes the questions but not the conversation.

How Koji approaches the same problem

Koji is built on a different collection method: AI-moderated interviews. Instead of a form, each student has a short, adaptive conversation with an AI interviewer that asks a consistent core set of questions and then probes follow-ups based on what the student actually says — the way a skilled human interviewer would, but at the scale of an entire cohort.

That design changes the downstream evidence:

Depth without extra staff. The AI probes vague answers automatically, so "the assessment was confusing" becomes a specific, actionable account of which assessment and why.
Automatic thematic analysis. Koji clusters what students say into themes across a cohort, module, or programme, so you get structured qualitative findings without manual coding.
Bias-aware standardized moderation. Every student is guided by the same moderation logic, which reduces the interviewer-variance problem while preserving the openness of a conversation.
Formative and summative collection. Koji supports mid-module (formative) check-ins as well as end-of-term evaluation, so issues surface while a course can still be improved.
Closing the loop with action tracking. Findings can be turned into documented actions and tracked over time — directly useful for quality-cycle and accreditation evidence.
EU/GDPR-aligned data handling designed for European institutions.

Koji's interview engine is the same one that powers the main Koji platform (koji.so) for customer and user research — the education product applies that conversational-research approach to students, courses, and programmes.

Side-by-side comparison

Dimension	Snap Surveys (Snap XMP)	Koji
Core method	Configurable questionnaires (many question types)	AI-moderated conversational interviews
Follow-up probing	No — fixed questions	Yes — adaptive, per-answer
Qualitative analysis	Comments surfaced; theming largely manual	Automatic thematic analysis across cohorts
Bias handling	Standardized questions	Standardized moderation + probing
Formative feedback	Possible via extra surveys	Built-in mid-course interviews
Closing the loop	Reporting/benchmarking; actions tracked manually	Built-in action tracking for the quality cycle
Mixed mode (paper/scan)	Yes — long heritage	Digital-first
Hosting/compliance	UK-ringfenced, self-host, ISO 27001, Cyber Essentials Plus	EU/GDPR-aligned cloud
Best for	Full survey-design control, self-hosting, paper workflows	Deep, auto-analysed qualitative evidence at scale

Competitor details above are drawn from Snap Surveys' published materials as of publication; verify current specifications and institutional pricing directly with the vendor.

When Snap Surveys is the better choice

Honesty matters to this audience, so to be clear: Koji is not the right tool for every job. Snap Surveys is likely the better fit when:

You require on-premise self-hosting or a specific UK-ringfenced data arrangement that your institution has already mandated.
You still run paper or scanned evaluations and need a single platform that handles print, scan, and web in one workflow.
Your primary need is a general-purpose survey engine used across many departments (facilities, events, alumni, staff) — not only course evaluation — and you want maximal control over every question.
You have dedicated staff capacity to code open-text comments and are satisfied with rating-scale-plus-comments as your evidence base.

If those describe you, Snap is a strong, mature option and you should shortlist it.

When Koji is the better choice

Koji tends to win when the goal is evidence quality and analyst time, specifically when you want:

Rich, probed qualitative feedback rather than sparse free-text boxes.
Automatic theming so a small QA or T&L team can cover a whole faculty without drowning in manual coding.
Standardized, bias-aware collection that stands up to scrutiny from PhD-literate committees.
Accreditation-ready outputs — standardized evidence, longitudinal cohort reporting, and documented closing-the-loop actions that map to ESG and national frameworks.

The bottom line

Snap Surveys and Koji are both credible, but they optimise for different things. Snap gives you a flexible, self-hostable survey platform with decades of higher-education pedigree and excellent data-governance controls. Koji gives you AI-moderated interviews and automatic analysis that turn thin survey text into deep, standardized, accreditation-ready qualitative evidence. If your bottleneck is analyst time and evidence depth, Koji is built for exactly that problem. If your bottleneck is survey-design control, self-hosting, or paper workflows, Snap remains a strong choice.

The most rigorous way to decide is to run both on the same module for one term and compare the evidence each produces — the depth of what students tell you, and how much staff time it took to turn that into findings your committees can act on.