sales-callminer
CallMiner platform help — enterprise conversation analytics (Eureka) with omnichannel interaction capture, automated QA scoring, agent coaching, real-time alerts, compliance monitoring, and CX automation. Use when QA scoring is inconsistent or takes too long across agents, when needing to analyze 100% of customer interactions instead of sampling, when setting up automated compliance monitoring for regulated industries (healthcare, finance, collections), when CallMiner Coach scorecards aren't surfacing the right coaching moments, when CallMiner RealTime alerts aren't triggering during live calls, when ingesting audio or text into CallMiner via the Ingestion API, when CallMiner Analyze categories aren't matching expected interactions, or when evaluating CallMiner vs Observe.AI or NICE CXone analytics. Do NOT use for CCaaS platform selection (use /sales-ccaas-selection) or for sales-specific coaching strategy (use /sales-coaching).
NPX Install
npx skill4agent add sales-skills/sales sales-callminerTags
Translated version includes tags in frontmatterSKILL.md Content
View Translation Comparison →CallMiner Platform Help
Step 1 — Gather context
references/learnings.md-
What area of CallMiner do you need help with?
- A) Capture — recording, screen capture, redaction setup
- B) Analyze — categories, scoring, sentiment, topic extraction
- C) Coach — agent scorecards, coaching plans, performance tracking
- D) RealTime — live alerts, next-best-action, real-time guidance
- E) Compliance — PCI/HIPAA monitoring, PII redaction, risk flagging
- F) API — Ingestion API (audio/text in), Data API (insights out)
- G) Integrations — CRM, CCaaS, WFM, transcription engine
- H) OmniAgent / Outreach / LiveTranslate — automation modules
- I) Admin — licensing, user management, permissions
- J) Something else
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What's your role?
- A) QA Manager / QA Analyst
- B) Contact center manager / supervisor
- C) Compliance / risk officer
- D) CX / VoC analyst
- E) IT / admin / developer
- F) Other
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What are you trying to accomplish? (describe your specific goal or issue)
Step 2 — Route or answer directly
| Problem domain | Route to |
|---|---|
| CCaaS platform comparison/selection | |
| Agent coaching strategy (not CallMiner-specific) | |
| Customer feedback / NPS / CSAT strategy | |
| Connecting CallMiner to other tools (architecture) | |
Step 3 — CallMiner platform reference
references/platform-guide.mdStep 4 — Actionable guidance
- Step-by-step instructions for their goal in CallMiner
- Configuration recommendations — specific settings, category rules, scoring criteria
- Common pitfalls — what goes wrong and how to avoid it
- Verification — how to confirm the change worked
- For API questions — point to
references/callminer-api-reference.md
references/learnings.mdGotchas
Best-effort from research — review these, especially items about plan-gated features and integration gotchas that may be outdated.
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Expect a 3-6 month ramp-up. CallMiner is powerful but complex — building accurate categories, scoring models, and coaching workflows takes months. Don't expect instant ROI. Budget for dedicated analyst time during setup.
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Auto-logout after 30 minutes is by design. The session timeout is short and affects all open tabs simultaneously. Save work frequently. This is a known pain point with no user-configurable override.
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Category tuning is iterative, not one-shot. Initial category rules will have false positives/negatives. Plan for weekly refinement cycles during the first quarter. Test categories against known-good interactions before deploying to scoring.
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Transcription engine choice affects everything downstream. CallMiner supports multiple ASR engines (Deepgram, Google, Azure, Nuance) via OVTS. Accuracy varies by accent, industry jargon, and audio quality. Test multiple engines with your actual call recordings before committing.
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Pricing is opaque — negotiate hard. No public pricing. Average ~$102K/year but ranges widely. Seat-based vs. hours-analyzed licensing models have very different economics depending on your volume and agent count.
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Self-improving: If you discover something not covered here, append it towith today's date.
references/learnings.md
Related skills
- — Sales coaching, QA, and agent training strategy (platform-agnostic)
/sales-coaching - — Compare CCaaS platforms (Genesys, NICE, Talkdesk, Five9, etc.)
/sales-ccaas-selection - — Observe.AI — contact center AI for QA and agent assist (CallMiner alternative)
/sales-observe-ai - — Cresta — enterprise contact center AI (CallMiner alternative)
/sales-cresta - — Balto — real-time agent assist (CallMiner RealTime alternative)
/sales-balto - — Convin — conversation intelligence with auto QA
/sales-convin - — Enthu.AI — contact center conversation intelligence
/sales-enthu - — Customer feedback, NPS, CSAT, VoC strategy
/sales-customer-feedback - — Connect CallMiner to CRM, CCaaS, or other tools
/sales-integration - — Not sure which skill to use? The router matches any sales objective to the right skill. Install:
/sales-donpx skills add sales-skills/sales --skill sales-do -a claude-code -y
Examples
Example 1: Automated QA scoring setup
- Reads platform guide for Analyze and Coach modules
- Explains category-based scoring — define quality criteria as categories, assign weights, auto-score 100% of interactions
- Walks through creating a QA scorecard with weighted categories (compliance, empathy, resolution, script adherence)
- Recommends starting with a calibration period comparing auto-scores to manual scores Result: User has a plan to move from 2% manual sampling to 100% automated QA scoring
Example 2: Compliance monitoring
- Reads platform guide for compliance and Redact modules
- Explains how to create categories detecting PCI-sensitive language patterns
- Walks through Redact configuration for automatic PII masking in transcripts and audio
- Recommends RealTime alerts for live intervention when PCI violations detected Result: User has PCI compliance monitoring with auto-redaction and real-time agent alerts