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How to Use CustomGPT.ai for Customer-question test sets
Learn CustomGPT.ai customer-question test sets with step by step workflows, realistic examples, and verified plan notes.
CustomGPT.ai works well for customer-question test sets when you run it like production work: locked brief, SOURCE facts, then review before publish. CustomGPT.ai builds custom chat agents that answer from your documents with citations (customgpt.ai). Catalog lists Standard and Premium amounts; verify customgpt.ai/pricing. Re-index when docs change and set out-of-scope refusals. Start at /explore/customgpt-ai.
This guide focuses on customer-question test sets in detail. Related CustomGPT.ai articles: /blog/how-to-use-customgpt-ai-for-site-embed-or-api-reviews, /blog/how-to-use-customgpt-ai-for-stale-content-re-index-notes, /blog/how-to-use-customgpt-ai-for-plan-confirmation-checklists.
When this workflow is the right job
Use customer-question test sets when the deliverable is specifically this CustomGPT.ai job. Switch to document-grounded agents when that workflow already owns the asset.
Step by step workflow
1. Brief Customer-question test sets
Write what must stay true for customer-question test sets in CustomGPT.ai before settings or spend.
Brief: Customer-question test sets Keep: verified SOURCE facts only Avoid: invented pricing or features Success: one reviewable output
2. Open CustomGPT.ai for Customer-question test sets
Use the CustomGPT.ai surface that owns customer-question test sets. Do not mix a neighboring workflow in the same pass.
Surface: Customer-question test sets Start: pilot with one representative input Plans: customgpt.ai/pricing
3. Pilot Customer-question test sets
Run a single customer-question test sets pilot. Score clarity, grounding, and whether the output is reviewable.
Pilot: Customer-question test sets [ ] SOURCE facts match [ ] Output reviewable [ ] Settings logged
4. Refine Customer-question test sets
Change one customer-question test sets dimension only. Save a template from the best run.
Refine: Customer-question test sets Change: one control only Keep: SOURCE and success criteria
Practical customer-question test sets examples
Embed mode
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Embed mode". Objective: Stand up a citation-aware workspace/agent for Embed mode with clear refuse-if-missing behavior. Inputs: - Document set for Embed mode - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Embed mode → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Embed mode with sample Q&A, citations, and known gaps.
Secure weights dir
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Secure weights dir". Objective: Stand up a citation-aware workspace/agent for Secure weights dir with clear refuse-if-missing behavior. Inputs: - Document set for Secure weights dir - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Secure weights dir → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Secure weights dir with sample Q&A, citations, and known gaps.
Chunk size note
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Chunk size note". Objective: Stand up a citation-aware workspace/agent for Chunk size note with clear refuse-if-missing behavior. Inputs: - Document set for Chunk size note - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Chunk size note → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Chunk size note with sample Q&A, citations, and known gaps.
Top-k retrieval
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Top-k retrieval". Objective: Stand up a citation-aware workspace/agent for Top-k retrieval with clear refuse-if-missing behavior. Inputs: - Document set for Top-k retrieval - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Top-k retrieval → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Top-k retrieval with sample Q&A, citations, and known gaps.
Refuse if missing
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Refuse if missing". Objective: Stand up a citation-aware workspace/agent for Refuse if missing with clear refuse-if-missing behavior. Inputs: - Document set for Refuse if missing - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Refuse if missing → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Refuse if missing with sample Q&A, citations, and known gaps.
Source quote
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Source quote". Objective: Stand up a citation-aware workspace/agent for Source quote with clear refuse-if-missing behavior. Inputs: - Document set for Source quote - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Source quote → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Source quote with sample Q&A, citations, and known gaps.
Update ingest
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Update ingest". Objective: Stand up a citation-aware workspace/agent for Update ingest with clear refuse-if-missing behavior. Inputs: - Document set for Update ingest - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Update ingest → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Update ingest with sample Q&A, citations, and known gaps.
Access roles
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Access roles". Objective: Stand up a citation-aware workspace/agent for Access roles with clear refuse-if-missing behavior. Inputs: - Document set for Access roles - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Access roles → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Access roles with sample Q&A, citations, and known gaps.
Docker deploy
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Docker deploy". Objective: Stand up a citation-aware workspace/agent for Docker deploy with clear refuse-if-missing behavior. Inputs: - Document set for Docker deploy - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Docker deploy → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Docker deploy with sample Q&A, citations, and known gaps.
Desktop install
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Desktop install". Objective: Stand up a citation-aware workspace/agent for Desktop install with clear refuse-if-missing behavior. Inputs: - Document set for Desktop install - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Desktop install → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Desktop install with sample Q&A, citations, and known gaps.
Test prompt small
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Test prompt small". Objective: Stand up a citation-aware workspace/agent for Test prompt small with clear refuse-if-missing behavior. Inputs: - Document set for Test prompt small - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Test prompt small → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Test prompt small with sample Q&A, citations, and known gaps.
Pin model version
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Pin model version". Objective: Stand up a citation-aware workspace/agent for Pin model version with clear refuse-if-missing behavior. Inputs: - Document set for Pin model version - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Pin model version → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Pin model version with sample Q&A, citations, and known gaps.
PII redaction
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "PII redaction". Objective: Stand up a citation-aware workspace/agent for PII redaction with clear refuse-if-missing behavior. Inputs: - Document set for PII redaction - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for PII redaction → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for PII redaction with sample Q&A, citations, and known gaps.
Eval questions
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Eval questions". Objective: Stand up a citation-aware workspace/agent for Eval questions with clear refuse-if-missing behavior. Inputs: - Document set for Eval questions - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Eval questions → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Eval questions with sample Q&A, citations, and known gaps.
Handoff human
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Handoff human". Objective: Stand up a citation-aware workspace/agent for Handoff human with clear refuse-if-missing behavior. Inputs: - Document set for Handoff human - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Handoff human → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Handoff human with sample Q&A, citations, and known gaps.
HR policy workspace
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "HR policy workspace". Objective: Stand up a citation-aware workspace/agent for HR policy workspace with clear refuse-if-missing behavior. Inputs: - Document set for HR policy workspace - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for HR policy workspace → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for HR policy workspace with sample Q&A, citations, and known gaps.
Citations on
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Citations on". Objective: Stand up a citation-aware workspace/agent for Citations on with clear refuse-if-missing behavior. Inputs: - Document set for Citations on - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Citations on → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Citations on with sample Q&A, citations, and known gaps.
Support billing agent
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Support billing agent". Objective: Stand up a citation-aware workspace/agent for Support billing agent with clear refuse-if-missing behavior. Inputs: - Document set for Support billing agent - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Support billing agent → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Support billing agent with sample Q&A, citations, and known gaps.
Local model RAM
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Local model RAM". Objective: Stand up a citation-aware workspace/agent for Local model RAM with clear refuse-if-missing behavior. Inputs: - Document set for Local model RAM - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Local model RAM → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Local model RAM with sample Q&A, citations, and known gaps.
Vector DB pick
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Vector DB pick". Objective: Stand up a citation-aware workspace/agent for Vector DB pick with clear refuse-if-missing behavior. Inputs: - Document set for Vector DB pick - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Vector DB pick → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Vector DB pick with sample Q&A, citations, and known gaps.
Private agent
Scenario: A team sets up Customer-question test sets in CustomGPT.ai for "Private agent". Objective: Stand up a citation-aware workspace/agent for Private agent with clear refuse-if-missing behavior. Inputs: - Document set for Private agent - Model/embed choices - Access roles - Eval questions Workflow: Create workspace → Ingest docs → Configure retrieval → Test Customer-question test sets questions for Private agent → Tune → Hand off Requirements: - Stay within verified CustomGPT.ai capabilities; do not invent features. - Confirm live plan notes on customgpt.ai/pricing before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Require citations; refuse when unsupported. Expected output: A working Customer-question test sets setup for Private agent with sample Q&A, citations, and known gaps.
How to improve customer-question test sets
Cut noise from customer-question test sets by removing extra adjectives while preserving SOURCE facts in CustomGPT.ai.
Raise quality by insisting on a single success check before debating style.
Make review easier by labeling fields that must never change.
Speed iteration by cloning the last good run and altering only one control.
Stabilize outputs by pinning settings after the pilot is approved.
Reduce rework by rejecting drafts that invent claims.
Improve handoffs by recording which control produced the best result.
Harden the workflow by testing an incomplete input before trusting defaults.
Prompting and usage guidance
Name the customer-question test sets job, audience, and success check before opening CustomGPT.ai.
Paste only verified facts under SOURCE so CustomGPT.ai cannot invent details.
Specify the deliverable shape up front.
Call out fixed details versus flexible style choices.
Ask CustomGPT.ai to flag unsupported claims before you accept the draft.
Limitations to respect
Check CustomGPT.ai plan gates for customer-question test sets on customgpt.ai/pricing before you promise timelines.
Keep drafts unpublished until a human confirms SOURCE facts.
CustomGPT.ai can be wrong. Treat customer-question test sets as provisional until review.
If documentation is silent on a claim, leave it out rather than guessing.
Practical tips for this workflow
Pilot once before batching customer-question test sets in CustomGPT.ai.
Keep a reusable template with variables for customer-question test sets.
Separate creative instructions from SOURCE facts.
Log settings from the best run.
Common mistakes
- Skipping the pilot run before scaling volume
- Inventing pricing, quotas, or features not on official pages
- Mixing unrelated workflows in one session
- Publishing without a human review gate
Treat customer-question test sets in CustomGPT.ai as a production workflow: brief, pilot, refine, then ship with review. Related reading: /blog/how-to-use-customgpt-ai-for-site-embed-or-api-reviews, /blog/how-to-use-customgpt-ai-for-stale-content-re-index-notes, /blog/how-to-use-customgpt-ai-for-plan-confirmation-checklists.