Swishr Pulse

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Quick overview for QA, Ops, and Leadership — what’s happening and what needs attention.

View

Evaluations —

In selected period

Avg Quality — ⓘ

Average in period

Fatal Accuracy — ⓘ

Critical compliance

Pass Rate — ⓘ

Passed evaluations

🔔 What needs attention

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Overdue actions ⓘ

Open actions ⓘ

Uncalibrated evals ⓘ

Recent fatal fails ⓘ

⚠️ Quality signals

Top failing parameter ⓘ

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Most impacted theme ⓘ

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Common pattern ⓘ

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Tip: Use Insights for root-cause breakdown and coaching themes.

Total Evaluations ⓘ Total Evaluations
Count of completed QA evaluations stored in the system.

Avg Quality ⓘ Avg Quality
Average quality score across all evaluations. Best used for trend direction, not individual decisions.

Pass Rate ⓘ Pass Rate
Percentage of evaluations that met the pass threshold (including fatal requirements).

Fatal Accuracy ⓘ Fatal Accuracy
Percentage of evaluations where all fatal (non-negotiable) requirements were met. Primary indicator of service risk.

#	Date	Ticket	Agent	Channel	Quality	Status	Calibration	Follow-up	Actions

DSAT Analysis – Evaluation

Capture root-cause attribution for DSAT cases (diagnostic, not scored).

Stored locally • Supabase-ready schema

Channel *

Ticket / Case ID *

Date

Agent

Department

Evaluator *

Root Cause Attribution

Choose one primary failure type, then a sub-reason.

Primary Failure Type *

Sub-Reason *

Impact Severity *

Confidence Level *

What went wrong? (facts)

Max 300 characters

What should have happened instead?

Max 300 characters

Recommended Action

Action Type

Action Owner

DSAT entries are saved to your database (and cached locally for resilience).

DSAT Entries Stored

0 entries

Recent DSAT entries

Date	Ticket	Channel	Agent	Evaluator	Failure	Impact	Actions
No DSAT entries yet.

Delete is a soft-delete (hidden from the app; still recoverable in the database).

Dashboard & Insights will be built next.

Primary Quality Killer ⓘ Primary Quality Killer
The single behaviour causing the biggest drop in overall quality across evaluations (severity × frequency).

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Most Impacted Theme ⓘ Most Impacted Theme
The coaching theme with the highest failure concentration—useful for targeting training and process fixes.

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Emerging Signal ⓘ Emerging Signal
An early pattern showing unusual change (e.g., rising fatal misses or a spike in a theme). Treat as a prompt to investigate.

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🧠

No insights yet

Insights will appear once you submit evaluations

✅ Action Summary ⓘ Action Summary
Follow-up actions created from QA findings (e.g., coaching, refreshers). Open and overdue actions indicate where improvement work is still pending.

Total: 0 Open: 0 Overdue: 0

By Type

Type	Open	Closed	Overdue

By Owner

Owner	Open	Closed	Overdue

🔻 Top 3 Behaviours Impacting Quality ⓘ Impacting Quality
Ranked using failure rate × parameter weight, with fatal items boosted. This highlights what hurts quality most, not just what fails most.

Ranked by failure rate × weight (fatal boosted)

Rank	Behaviour (Parameter)	Failure Rate	Impact

Evaluator Consistency ⓘ Evaluator Consistency
Shows if an evaluator scores systematically higher/lower than the org average once sample size is sufficient. Used for calibration, not performance.

Band: ±10% vs org avg • Min sample: 5

Evaluator	N	Avg Quality	Avg Fatal	Pass Rate	Δ vs Org	Label

🎯 Coaching Themes ⓘ Coaching Themes
Grouped behaviours that roll up multiple parameters into a single coaching area. Use themes to prioritize training and process fixes.

📈 Weekly Quality Trend ⓘ Weekly Trend
Week-by-week average quality. Use for direction and stability; interpret with sample size.

🧩 Patterns & Signals ⓘ Patterns & Signals
Automated highlights from the dataset (e.g., most common failure category, rising fatal misses, channel shifts). Treat as investigation prompts.

Swishr Pulse – Quality System

Home

🔔 What needs attention

⚠️ Quality signals

📋 Evaluation Information

✅ Quality Parameters (32 Total)

💬 General Comments

🧩 Follow-up Action

📊 Live Score

No evaluations yet

DSAT Analysis – Evaluation

Root Cause Attribution

Recommended Action

No data yet

📈 Quality Trend ⓘ Quality Trend
Weekly movement of average quality. Use to spot improvement/decline over time; small week-to-week noise is normal.

👥 Agent Performance ⓘ Agent Performance
Average quality by agent. Use to identify coaching opportunities; always consider sample size (N).

📞 Channel Distribution ⓘ Channel Distribution
Share of evaluations by channel (Call/Email/Chat). Helps explain shifts in quality due to channel mix.

🎯 Top Failed Parameters ⓘ Top Failed Parameters
Most frequently failed QA parameters. High frequency does not always mean highest impact—pair with Insights impact ranking.

No insights yet

✅ Action Summary ⓘ Action Summary
Follow-up actions created from QA findings (e.g., coaching, refreshers). Open and overdue actions indicate where improvement work is still pending.

🔻 Top 3 Behaviours Impacting Quality ⓘ Impacting Quality
Ranked using failure rate × parameter weight, with fatal items boosted. This highlights what hurts quality most, not just what fails most.

Evaluator Consistency ⓘ Evaluator Consistency
Shows if an evaluator scores systematically higher/lower than the org average once sample size is sufficient. Used for calibration, not performance.

🎯 Coaching Themes ⓘ Coaching Themes
Grouped behaviours that roll up multiple parameters into a single coaching area. Use themes to prioritize training and process fixes.

📈 Weekly Quality Trend ⓘ Weekly Trend
Week-by-week average quality. Use for direction and stability; interpret with sample size.

🧩 Patterns & Signals ⓘ Patterns & Signals
Automated highlights from the dataset (e.g., most common failure category, rising fatal misses, channel shifts). Treat as investigation prompts.

👥 Manage Agents

✍️ Manage Evaluators

💾 Data Management

Home

🔔 What needs attention

⚠️ Quality signals

📋 Evaluation Information

✅ Quality Parameters (32 Total)

💬 General Comments

🧩 Follow-up Action

📊 Live Score

No evaluations yet

DSAT Analysis – Evaluation

Root Cause Attribution

Recommended Action

No data yet

📈 Quality Trend ⓘ Quality TrendWeekly movement of average quality. Use to spot improvement/decline over time; small week-to-week noise is normal.

👥 Agent Performance ⓘ Agent PerformanceAverage quality by agent. Use to identify coaching opportunities; always consider sample size (N).

📞 Channel Distribution ⓘ Channel DistributionShare of evaluations by channel (Call/Email/Chat). Helps explain shifts in quality due to channel mix.

🎯 Top Failed Parameters ⓘ Top Failed ParametersMost frequently failed QA parameters. High frequency does not always mean highest impact—pair with Insights impact ranking.

No insights yet

✅ Action Summary ⓘ Action SummaryFollow-up actions created from QA findings (e.g., coaching, refreshers). Open and overdue actions indicate where improvement work is still pending.

🔻 Top 3 Behaviours Impacting Quality ⓘ Impacting QualityRanked using failure rate × parameter weight, with fatal items boosted. This highlights what hurts quality most, not just what fails most.

Evaluator Consistency ⓘ Evaluator ConsistencyShows if an evaluator scores systematically higher/lower than the org average once sample size is sufficient. Used for calibration, not performance.

🎯 Coaching Themes ⓘ Coaching ThemesGrouped behaviours that roll up multiple parameters into a single coaching area. Use themes to prioritize training and process fixes.

📈 Weekly Quality Trend ⓘ Weekly TrendWeek-by-week average quality. Use for direction and stability; interpret with sample size.

🧩 Patterns & Signals ⓘ Patterns & SignalsAutomated highlights from the dataset (e.g., most common failure category, rising fatal misses, channel shifts). Treat as investigation prompts.

👥 Manage Agents

✍️ Manage Evaluators

💾 Data Management

Evaluation Details

📈 Quality Trend ⓘ Quality Trend
Weekly movement of average quality. Use to spot improvement/decline over time; small week-to-week noise is normal.

👥 Agent Performance ⓘ Agent Performance
Average quality by agent. Use to identify coaching opportunities; always consider sample size (N).

📞 Channel Distribution ⓘ Channel Distribution
Share of evaluations by channel (Call/Email/Chat). Helps explain shifts in quality due to channel mix.

🎯 Top Failed Parameters ⓘ Top Failed Parameters
Most frequently failed QA parameters. High frequency does not always mean highest impact—pair with Insights impact ranking.

✅ Action Summary ⓘ Action Summary
Follow-up actions created from QA findings (e.g., coaching, refreshers). Open and overdue actions indicate where improvement work is still pending.

🔻 Top 3 Behaviours Impacting Quality ⓘ Impacting Quality
Ranked using failure rate × parameter weight, with fatal items boosted. This highlights what hurts quality most, not just what fails most.

Evaluator Consistency ⓘ Evaluator Consistency
Shows if an evaluator scores systematically higher/lower than the org average once sample size is sufficient. Used for calibration, not performance.

🎯 Coaching Themes ⓘ Coaching Themes
Grouped behaviours that roll up multiple parameters into a single coaching area. Use themes to prioritize training and process fixes.

📈 Weekly Quality Trend ⓘ Weekly Trend
Week-by-week average quality. Use for direction and stability; interpret with sample size.

🧩 Patterns & Signals ⓘ Patterns & Signals
Automated highlights from the dataset (e.g., most common failure category, rising fatal misses, channel shifts). Treat as investigation prompts.