Customer Conversations
Interaction data is captured across the contact center.
DFCU Case Study
How DFCU Transformed Manual QA Into Automated Conversation Intelligence
Learn how Dort Financial Credit Union used Zenylitics' conversation analytics workflow, automated scorecards, calibration, and analyst-supported Team-as-a-Service model to expand QA coverage, reduce manual effort, and create actionable coaching intelligence.
Complimentary PDF · Practical insights for regulated contact centers
Key Results
Calls monitored~15,000Monitored through automated scoring and analyst-supported QA workflows
Annualized labor savings$32,718Under DFCU's current sampled QA policy
Projected annual labor avoided$6.43MModeled cost of manually reviewing DFCU's full monitored-call population under the legacy QA processFull-coverage benchmark
QA coverageFull coverageFrom 4 calls per agent per monthDFCU moved beyond limited manual sampling across roughly 50 to 60 agents to automated scoring across the active call population
Disclaimer: the $6.43M figure is a full-coverage benchmark modeling the cost of manually reviewing every call now monitored. It is not incremental realized cash savings, and it is separate from the $32,718 figure above, which reflects actual savings under DFCU's current sampled QA policy.
The Challenge
DFCU Had a QA Process, But It Was Difficult to Scale
DFCU's quality assurance program depended on manual listening and scoring. Each monitored call required more than 30 minutes of senior team effort, limiting coverage to approximately four calls per agent per month.
That level of sampling made it difficult to identify broader trends across training needs, process issues, call drivers, and compliance risks. The program produced real findings on the calls it reviewed. What it couldn't produce was a reliable picture of what was happening across the calls it never reached.
Before ZenyliticsAfter Zenylitics
Manual call reviewAutomated scorecards
Limited samplesBroader call coverage
Reviewer-dependent scoringCalibrated scoring logic
Reactive coachingData-backed coaching
The Solution
How Zenylitics Helped DFCU Build a Scalable QA Intelligence Workflow
Zenylitics deployed a conversation analytics platform (CallMiner), automated scorecards, analyst validation, calibration feedback, guided insights, and Team-as-a-Service support.
The engagement was not a software handoff. Zenylitics provided the analytics expertise, scorecard tuning, validation, and reporting layer needed to turn interaction data into operational intelligence DFCU's team could act on directly.
From Raw Conversations to Coaching and Governance Intelligence
Customer conversations move through a structured path before they become a coaching or compliance decision.
Conversation Analytics Platform
The platform processes calls at scale and surfaces signals.
Automated Scorecards
Consistent scoring logic is applied across interaction volume.
Analyst Validation and Calibration
Zenylitics calibrates findings to DFCU's real environment.
Guided Insights
Supervisors receive findings ready to use directly.
Coaching and Operational Decisions
Validated insights inform coaching and operational action.
Each stage builds on the one before it. Conversations get captured and processed by the analytics platform. Automated scorecards apply consistent scoring logic across the interaction volume. Zenylitics analysts validate that scoring and calibrate it against DFCU's real environment. The resulting guided insights reach supervisors in a form they can use directly for coaching and operational decisions, without requiring further interpretation.
The Impact
The Impact: Expanding QA Coverage While Reducing Manual Effort
The engagement delivered operational value without adding internal QA headcount or leaving the team with another dashboard to interpret.
Annualized Labor Savings
Under DFCU's existing sampled QA policy. This is current-policy labor savings, not a projected full-coverage benchmark.
Calls Monitored
Through automated scoring and analyst-supported quality workflows.
Improved QA Efficiency
Supervisors spent less time manually reviewing calls and more time using structured findings for coaching.
Better Operational Visibility
Zenylitics helped identify top call drivers, silence metrics, call avoidance signals, recap language issues, and investigative language opportunities.
The client perspective
Dort Financial
Credit Union Conversation intelligence
in practice
Credit Union Conversation intelligence
in practice
Overall, Zen has helped improve efficiency, reduce manual QA time, and create a more consistent monitoring process.
Zen's support has been excellent since day one. Their responsiveness and willingness to help have made the transition and ongoing use very smooth for our team.
Operational Change
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What Changed After Implementing Conversation Analytics
The program gave DFCU a repeatable way to turn a broader set of conversations into consistent action.
QA Automation
Manual listening, documenting, and scoring no longer served as the primary QA process.
More Consistent Scorecards
Calibration improved scoring consistency, category accuracy, and reporting reliability.
More Specific Coaching
DFCU used transcripts and scorecard outputs to coach average handle time, upsell behavior, recap language, investigative language, and call handling consistency.
Risk and Governance Visibility
The program supported UDAAP reporting, compliance review, and documentation of member service issues.
A Scalable QA Model for Regulated Contact Centers
Financial contact centers face increasing call volumes, compliance requirements, limited QA resources, the need for consistent coaching, and the need for better customer experience visibility.
Financial institutions need more than interaction data. They need a process that turns conversations into measurable operational improvements, not just a wider dashboard to interpret on their own.
Inside the Study
Inside the DFCU Case Study
- How DFCU moved beyond manual QA sampling
- How automated scorecards expanded monitoring coverage
- How calibration improved scoring consistency
- How analyst-supported insights improved coaching
- How conversation analytics supported governance and compliance
Why Zenylitics
Why Organizations Choose Zenylitics
Zenylitics combines conversation analytics technology, analyst expertise, scorecard development, calibration, and guided insights. The goal is to provide finished intelligence rather than leaving organizations with raw platform outputs to interpret themselves.
Take the Next Step
See How Financial Contact Centers Can Turn Conversations Into Actionable Intelligence
Download the DFCU case study for a closer look at the workflow, measured results, and scalable QA model.