Etch Media — Staff Tracking & Performance

Powered by Etch Media AI • Real-time Workforce Intelligence

Today: 25 Mar 2026

Executive Overview

Real-time staff performance metrics powered by AI-driven camera network analysis

Active Staff On Floor
24/28
85.7% present
+2.1%vs last week
Avg Service Response
1.8 min
Customer approach to greeting
-12.4%vs last week
Break Compliance
94.2%
Took scheduled breaks
+2.1%vs last week
Customer Engagement Score
8.4/10
Interaction quality
+0.6vs last week

Staff Activity Breakdown

Staff Activity Breakdown

AI vision system automatically classifies every staff member's activity in real-time. Shows percentage of time spent in each activity category across the entire team. High "Serving" and low "Idle" indicate healthy floor presence.

Insight: 42% serving vs 8% idle is healthy. Restocking (18%) could be optimized by off-peak timing. Consider batching stock tasks during slower hours to maximize customer-facing time.

Weekly Performance Trend

Weekly Performance Trend

Tracks average staff count on floor (blue bars), total customer interactions completed (dark bar), and overall team efficiency score (line). Helps identify peak performance days and efficiency patterns.

Insight: Saturday shows highest activity (34 interactions/staff) and efficiency (92 score). Friday pre-weekend prep shows strong engagement despite lower absolute numbers.

Team Comparison (3 Shifts)

Team Comparison Radar

Radar chart comparing Morning, Afternoon, and Evening shifts across 5 dimensions: Response Time (lower is better), Engagement (higher is better), Coverage (staff count), Compliance (policy adherence), and Efficiency (tasks per hour). Identify team strengths and development areas.

Insight: Evening shift leads in Engagement (88) and Response Time (1.2 min), but shows lower Coverage (21 staff). Morning shift excels in Compliance (96%) but could improve Efficiency. Cross-train morning team on peak-hour techniques.

Attendance Trend This Week

Attendance Trend

Stacked bar showing Present, Absent, and Late staff by day. Helps identify attendance patterns and potential scheduling issues. Auto-logged from AI camera network and badge readers.

Insight: Monday shows 3 lates (higher than avg). Consider earlier briefings on Mondays or revisit shift start times. Attendance otherwise stable—no absence spike detected.

Real-Time Location & Activity

AI camera network tracks staff location and activity classification across zones

Staff in Zone A (Sales Floor)
12
Primary selling area
Staff in Zone B (Checkout)
5
Payment processing
Staff in Zone C (Stock Room)
4
Replenishment & prep
Staff on Break
3
Currently off-duty

Hourly Zone Distribution (8AM–9PM)

Zone Distribution Over Day

Stacked area chart showing how staff spread across three zones throughout the day. Zone A (Sales Floor) should peak during customer hours. Reveals staffing imbalances and opportunity to shift resources.

Insight: Zone A peaks at 2PM (14 staff) then drops to 8 at 5PM, despite 6–7PM being peak customer hours. Recommend shifting lunch breaks to 5–6PM to maximize floor presence during high-traffic periods.

Activity Classification Timeline

Activity by Hour

Hourly breakdown of staff activities: Serving customers, Restocking shelves, Cleaning areas, and Idle time. High "Serving" during peak hours is expected. Idle time should be minimal during business hours.

Insight: 6–7PM shows 38% serving (highest), validating this as peak customer hour. 11AM shows 22% idle (above target), suggesting opportunity to front-load restocking or marketing tasks.

Zone Coverage Heatmap

Coverage by Zone

Horizontal bar chart showing ideal vs actual coverage % for each zone. Green = well-staffed, Orange/Red = under-covered. Under-coverage can lead to missed customer interactions and longer queues.

Insight: Zone B (Checkout) at 71% coverage during peak hours is below target (80–85%). Adding 1–2 staff or cross-training would reduce queue times from current 3.2 min to target <2 min.

Staff Movement Between Zones

Zone Transitions

Shows frequency of staff movement between zones. High movement suggests staff are responding to needs dynamically. Excessive movement may indicate inefficient task allocation or unclear zone ownership.

Insight: 156 transitions between A↔B and 142 between A↔C is healthy. 64 transitions C↔B suggests stock room staff are helping with checkout overflow—consider dedicated checkout cross-training.

Performance & Engagement

Individual and team-level engagement and interaction metrics

Top Performer
Sarah L.
Score: 96/100
Avg Customer Interactions/hr
8.2
Per staff member
+1.3vs last week
Avg Service Duration
3.4 min
Per customer interaction
-0.2 minvs last week
Queue Wait Reduction
-22%
vs last month
+5%vs last week

Individual Performance Scores

Performance Scores

Composite score (0–100) for each staff member based on response time, engagement duration, customer interaction quality (detected via posture analysis), compliance, and break adherence. Higher = stronger all-around performance.

Insight: Sarah L. (96) leads through quick response times (1.1 min) and high engagement. Mark T. (82) shows promise but inconsistent break compliance. Pair Mark with Sarah for mentoring to reach team average (87).

Customer Interaction Rate by Hour

Hourly Interaction Rate

Line chart showing average customer interactions per staff member by hour. Peaks correlate with foot traffic. Dips may indicate reduced staffing or product knowledge gaps.

Insight: 6–7PM shows 12.4 interactions/staff (peak productivity). 2–3PM dips to 4.8—consider scheduled product knowledge training or activity engagement during slow periods.

Service Speed Distribution

Service Duration Buckets

Bar chart showing how many customer interactions fall into each duration bucket. <1 min = quick questions, 1–3 min = standard service, 3–5 min = consultative, 5+ min = complex issues. Guides training focus.

Insight: 58% of interactions complete in under 3 minutes (efficient). 16% exceed 5 minutes—flag these as complex cases for post-interaction coaching and product knowledge reinforcement.

Engagement Quality by Staff (Radar)

Staff Engagement Radar

Radar comparison of top 3 performers (Sarah, Emily, James) across Response Time, Engagement Duration, Interaction Quality, Customer Satisfaction, and Compliance. Shows which staff excel in which dimensions.

Insight: Sarah excels across all dimensions (balanced performer). Emily leads in Engagement Duration (customer retention) but lags in Response Time. James strong in Response but lower Satisfaction—may benefit from soft skills training.

Attendance & Compliance

Automated attendance tracking and break/policy compliance metrics

On-Time Rate
96.4%
This month
+1.8%vs last month
Avg Clock-In Time
8:52 AM
Target: 9:00 AM
-4 minvs last week
Break Policy Compliance
94.2%
Took scheduled breaks
+2.1%vs last week
Overtime Hours (Week)
18.5 hrs
5 staff members

Weekly Attendance (Stacked)

Weekly Attendance

Stacked bar showing On-Time (green), Late (orange), and Absent (red) staff by day. Auto-logged from camera network and badge readers, eliminating manual tracking errors.

Insight: Monday shows 3 lates (above typical 1–2). Tuesday–Friday stable. Thursday 1 absence (illness called in). Track Monday lates for pattern—may need shift time adjustment or manager reminder.

Break Duration Distribution

Break Length Patterns

Bar chart showing breakdown of break durations. Most staff take 15–30 min breaks as scheduled. Staff exceeding limits may need reminders. Too-short breaks (under 10 min) reduce rest quality.

Insight: 72% of breaks are 15–30 min (policy-compliant). 18% exceed 30 min (only 2–3 staff repeat offenders). Brief reminder on clock discipline could tighten compliance to 96%+.

Clock-In Time Distribution

Clock-In Times

Distribution of staff clock-in times in 15-minute intervals. Shows how many staff arrive early vs late relative to shift start (9:00 AM). On-time is 9:00–9:15 AM; early (<9:00) is proactive; late is after 9:15.

Insight: 18 staff clock in early (before 9:00)—sign of engagement. 24 on-time, 3 late. No staff are more than 10 min late. Overall punctuality is strong. Monitor the 3 late staff for patterns.

Overtime by Staff Member

Overtime Hours

Horizontal bar showing overtime hours logged for each staff member. Excessive OT (6+ hours/week) may indicate understaffing or burnout risk. Consider workload rebalancing.

Insight: Sarah L. logged 5.2 hrs OT (above avg), likely due to high performance and task ownership. Monitor for burnout. Consider bonus or time-off compensation. John M. logged 4.8 hrs—within reasonable range.

Posture & Behavior Analysis

AI vision system detects posture, attention levels, and engagement indicators

Attentive Posture Rate
87.3%
Upright, engaged posture
+3.2%vs last week
Active Engagement Time
72%
Customer-facing or task-focused
+4.1%vs last week
Distraction Alerts Today
6
Phone or off-task behavior
Coaching Opportunities
3
Staff flagged for feedback

Attentive vs Distracted Trend

Attentiveness Over Day

Line chart showing two dimensions: % staff with attentive posture and % staff showing distraction signals (phone use, slouching, disconnected body language) by hour. Peaks at start/after break; dips toward end of shift are normal.

Insight: Attentiveness peaks at 9AM (94%) and 6PM (89%), dips to 78% at 4PM (afternoon slump). Consider brief energizer activity or snack at 4PM to lift engagement before evening rush.

Engagement Level by Zone

Zone Engagement

Bar chart showing average engagement score (0–100) for staff in each zone. Sales Floor engagement expected to be highest (customer interaction). Stock Room lower but should still be 70+. Identifies zones needing morale boost.

Insight: Zone A (Sales Floor) shows 86 engagement—healthy customer-facing energy. Zone C (Stock Room) at 74—isolated back-area role. Rotate Stock Room staff to Sales Floor monthly for variety and engagement.

Behavior Classification (Today)

Behavior Types

Doughnut chart categorizing staff behavior patterns: Proactive (initiating customer help, restocking ahead of demand), Reactive (responding to requests only), Passive (minimal activity), Disengaged (off-task, distracted). Proactive % should be 50%+.

Insight: 48% Proactive (target 50%) and 32% Reactive is healthy. 12% Passive and 8% Disengaged warrant individual coaching. Target for next month: 60% Proactive through incentive program or recognition.

Weekly Posture Score Trend

Posture Score

Line chart showing team average posture/engagement score (0–100) over 4-week period. Smooth trend = stable engagement. Dips may correlate with staffing changes, fatigue, or external factors. Peaks show successful engagement initiatives.

Insight: Score improved from 82 (Week 1) to 88 (This week)—likely due to new recognition program launched 2 weeks ago. Maintain momentum with continued positive reinforcement.

HR Integration & Talent Management

Performance-to-HR linkage: bonuses, training recommendations, and automated scheduling

Auto-Logged Attendance
98.2%
vs manual records (99.1%)
+0.8%vs last month
Service Quality Index
8.1/10
Multi-metric average
+0.3vs last month
Training Recommendations
5 staff
AI-identified needs
Bonus-Eligible Staff
18/28
64.3% exceed threshold

Performance vs Bonus Threshold

Bonus Eligibility

Horizontal bar showing each staff member's current performance score (colored bar) vs bonus threshold line (85/100). Staff above the line are bonus-eligible. Helps HR automate bonus decisions and shows gap for non-eligible staff.

Insight: 18 of 28 staff eligible for bonus (64%). Sarah L., Emily C., and James R. top the list (96, 92, 89). Bottom tier: Mark T. (82), John M. (81)—just 3–4 points from eligibility. Targeted coaching could move them across threshold.

Training Needs by Category

Training Gaps

Bar chart showing # of staff flagged for training in each area. AI identifies gaps based on performance metrics: Service Skills (response time, customer interaction), Product Knowledge (upsell, troubleshooting), Time Management (efficiency), Communication (listening, clarity).

Insight: 5 staff need Service Skills training (likely response time). 3 need Product Knowledge (low upsell rate). 2 need Time Management. Schedule 2-hour modules next month. Sarah can mentor Service Skills group.

Monthly Attendance Summary (4-Week)

Monthly Attendance

Stacked bar showing total Present, Late, and Absent days across 4-week month view. Trends help HR identify chronic latecomers or frequent absences for counseling or scheduling adjustments.

Insight: Week 1 had 3 absences (illness spike). Weeks 2–4 stable. Month-to-date: 109 present days (98.2%), 2 lates, 1.8 absences avg/week. On-time rate 96.4% exceeds target of 95%.

Quality Score Trend (4-Week)

Quality Improvement

Line chart showing team average Service Quality Index across 4 weeks. Composite of: Response Time, Engagement Duration, Customer Satisfaction, Compliance, and Behavior. Uptrend = improving team health. Used for HR performance reviews.

Insight: Quality improved from 7.6 (Week 1) to 8.1 (This week). +6.6% improvement over month. Sustained growth suggests new incentive program and recognition efforts are working. Continue momentum into next quarter.