How the Quality Gate Works
Understand Koji's quality gate — conversations scoring below 3/5 are completely free and don't consume credits, protecting your research budget.
The Quality Gate: Never Pay for Bad Data
Koji's quality gate is a built-in protection that ensures you only spend credits on meaningful conversations. Any interview that scores below 3 on Koji's 1-5 quality scale is completely free — no credits consumed, no charges incurred.
This applies to every plan, including overage conversations.
How Quality Scoring Works
Every conversation on Koji is automatically scored on a 1–5 scale based on the depth and quality of the interaction:
| Score | Quality Level | Credits Charged? |
|---|---|---|
| 1–2 | Below threshold | No — free |
| 3 | Meets threshold | Yes — credits charged |
| 4–5 | High quality | Yes — credits charged |
The scoring evaluates factors like:
- Response depth — Did the participant give substantive, detailed answers?
- Conversation completeness — Did the interview cover the key topics?
- Engagement level — Was the participant actively engaged throughout?
- Information value — Did the conversation generate actionable insights?
Why the Quality Gate Matters
Budget Protection
Without a quality gate, every conversation would cost credits — even ones where:
- A participant abandoned the interview early
- Responses were too brief to be useful
- The participant didn't engage meaningfully with the questions
With Koji's quality gate, these low-value interactions are filtered out automatically. You only pay for conversations that actually contribute to your research.
Real Impact on Your Budget
Consider a typical research study with 50 total conversations:
- ~40 conversations score 3+ (quality threshold met) — credits charged
- ~10 conversations score below 3 — completely free
That's a 20% savings on your credit budget, automatically applied.
Quality Gate Across All Plans
| Plan | Quality Gate | Effect |
|---|---|---|
| Free | Active | Low-quality conversations don't consume your 10 starter credits |
| Insights | Active | Low-quality conversations don't consume your 29 monthly credits |
| Interviews | Active | Low-quality conversations don't consume your 79 monthly credits |
| Enterprise | Active | Low-quality conversations don't consume your allocated credits |
Quality Gate During Overage
The quality gate also applies during overage billing. If you've exceeded your included credits and a conversation scores below 3 on the 1-5 scale, no overage charge is generated. You are never billed for low-quality interactions, period.
Quality Gate in Reports
The quality gate doesn't just protect your budget — it also protects your research quality. Reports only include conversations that score 3 or above. Low-scoring conversations are excluded from report aggregation, theme analysis, and statistical summaries. This ensures your research findings are built on substantive, high-quality data rather than being diluted by low-effort responses.
You can still view individual low-scoring transcripts in the Responses tab for reference, but they won't affect your aggregated insights.
What Affects Conversation Quality
Several factors influence whether a conversation meets the quality threshold:
Participant-Side Factors
- Engagement — participants who take the interview seriously produce higher scores
- Response length — one-word answers typically result in lower scores
- Relevance — responses that address the actual questions score higher
- Completion — finishing the full interview improves the score
Study Design Factors (You Control These)
- Clear, open-ended questions — well-crafted questions encourage detailed responses
- Appropriate interview length — not too short (insufficient depth) or too long (fatigue)
- Good probe points — AI follow-up prompts that encourage elaboration
- Relevant guardrails — keeping conversations on topic improves quality
- Structured questions — mixing in scale, choice, and ranking questions helps maintain engagement and produces richer data
Tips to Maximize Quality Scores
- Write open-ended questions — "Tell me about..." instead of "Do you like...?"
- Set up probe points — guide the AI to dig deeper on key topics
- Keep interviews focused — 5-8 core questions is the sweet spot
- Use guardrails — prevent conversations from going off-topic
- Target the right participants — better targeting = better engagement
- Use voice interviews — voice conversations tend to produce richer, more detailed responses
- Add structured questions — scale and choice questions keep participants engaged between open-ended exploration
Viewing Quality Scores
You can see quality scores for each conversation in your study dashboard:
- Navigate to your study
- Open the Responses tab
- Each conversation shows its quality score (1-5)
- Filter by score to review which conversations met the threshold
- Low-scoring conversations are marked and clearly shown as free
The Quality Gate and Research Integrity
The quality gate improves your research quality in two ways:
- Budget protection — you only spend credits on conversations that met the quality threshold
- Report accuracy — reports aggregate only conversations scoring 3 or above, ensuring your insights are built from substantive data
- Targeting feedback — consistently low scores may indicate you need to adjust your participant criteria
- Study design insights — patterns in low-scoring conversations reveal opportunities to refine your questions
Related Articles
Can You Trust AI Interviewers? How Koji Prevents Hallucinations and Bias in Customer Research
A practical guide to how modern AI research platforms prevent hallucinations, model bias, and leading questions during auto-moderated customer interviews — with the verification techniques Koji uses to keep AI-generated insights faithful to the actual transcript.
AI Interviewer Tuning: How to Get Research-Grade Voice Interviews
A complete playbook for tuning Koji's AI interviewer — company context, probing depth, structured questions, and interview mode — to deliver interviews indistinguishable from a human researcher.
Best AI Interview Software in 2026: 9 Platforms Compared
A side-by-side review of the leading AI interview platforms in 2026 — Koji, Listen Labs, Strella, Outset, Marvin, Conveo, Glaut, Feedbk, and User Intuition. Pricing, modality, recruitment, analysis, and the right tool for each use case.
Interview Completion Flow
What happens when an interview ends — thank-you screen, participant feedback, and behind-the-scenes AI analysis.
Koji vs Listen Labs: AI Interview Platform Comparison (2026)
An honest, side-by-side comparison of Koji and Listen Labs — pricing, features, recruitment, analysis, and which AI interview platform is the right fit for your team.
Koji vs Marvin (HeyMarvin): End-to-End AI Interviews vs. Analysis-Only Repository
Koji vs Marvin compared head-to-head. Marvin centralizes and analyzes interviews you have already conducted; Koji actually runs the interview AND analyzes it. Pricing, features, and the right pick for your team.
Managing Research Participants: The Complete Guide to Koji's Recruit Tab
How to track, filter, import, and export research participants in Koji — including personalized links, quality management, and CRM integration.
Overage Billing Explained
Understand how overage billing works on Koji — flat €1/credit pricing, configurable caps, and how the quality gate protects your budget.
Survey Fraud & Respondent Quality: How to Detect Fake and Low-Effort Responses (2026)
Between 5% and 26% of survey responses are fraudulent, and AI-generated answers now pass standard quality checks. Learn the warning signs, the detection tactics that still work, and how Koji's conversational quality gate filters bad data before it reaches your report.
Understanding Quality Scores
Learn how Koji evaluates interview quality on a 0-5 scale and why it matters for your research and billing.
Understanding Usage & Credits
Learn how Koji's credit system works — what actions cost credits, how limits are tracked, and how to manage your research budget effectively.
User Interview Software: A 2026 Buyer's Guide
How to choose user interview software in 2026 — vendor categories, evaluation criteria, pricing models, and the right pick for product, UX, marketing, and research teams.