Understanding Analytics & Metrics

The Etienne Intelligence Platform tracks comprehensive metrics across your business, sourced from Zenoti and enhanced with AI-generated insights. This guide explains each metric, what it means, and how to use it.

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Core Business Metrics

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Revenue

Definition: Total revenue from completed appointments Data Source: Zenoti invoices and payment records How It’s Calculated:

• Sum of all completed appointment revenue
• Excludes cancelled or no-show appointments
• Filtered by date range and location

Service Revenue by Type:

• Botox: $450 per session (30 min)
• Dermal Filler: $850 per session (45 min)
• Hydrafacial: $250 per session (60 min)
• Laser Hair Removal: $350 per session (45 min)
• Chemical Peel: $200 per session (30 min)
• Body Contouring: $1,200 per session (90 min)

What Good Looks Like:

• Monthly revenue growth: 5-10%
• Consistent daily revenue (avoid huge spikes/valleys)
• High-value services (Body Contouring, Filler) comprise 30%+ of revenue

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Revenue Trend

Definition: Percentage change compared to previous period Formula: ((Current Revenue - Previous Revenue) / Previous Revenue) × 100 Time Periods Compared:

• Last 30 days vs. previous 30 days (days 31-60)
• This allows you to see month-over-month performance

Interpreting the Trend:

• +5% or higher: Strong growth, current strategies working
• 0% to +5%: Stable growth, look for optimization opportunities
• -1% to 0%: Flat, investigate causes
• Below -1%: Declining, requires immediate attention

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Bookings

Definition: Total number of appointments scheduled (completed + confirmed + waitlist) Tracked by Channel:

• AI bookings: Handled automatically without staff intervention
• Staff bookings: Manually entered by team members
• Online bookings: Direct website bookings

Booking Efficiency:

• AI handles 60-75% of bookings in full operation phase
• Staff handles complex cases and escalations
• Online direct bookings typically 10-15%

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Client Acquisition & Retention

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New Clients

Definition: First-time visitors who complete an appointment Data Source: Zenoti client records (join date) What Drives New Client Acquisition:

• Social media campaigns (Instagram, TikTok, Facebook)
• First-time client promotions (15% off)
• Referral programs
• After-hours availability (captures clients who can’t call during work hours)

Healthy New Client Rate: 15-25 new clients per month per location

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Client Lifetime Value (CLV)

Definition: Total revenue generated by a client over their entire relationship Formula: Sum of all completed appointment revenue for that client CLV Segments:

• VIP: $5,000+ (2% of clients, 30% of revenue)
• Regular: $1,000-$4,999 (30% of clients, 50% of revenue)
• Occasional: Under $1,000 (68% of clients, 20% of revenue)

Top CLV Clients in System:

• Danielle Parker: $15,000 (25 visits, SoHo)
• Sofia Ramirez: $9,600 (12 visits, SoHo)
• Olivia Martinez: $6,500 (10 visits, SoHo)

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Rebooking Rate

Definition: Percentage of clients who schedule their next appointment Formula: (Clients who rebooked / Total completed appointments) × 100 Performance Benchmarks:

• Pre-AI: 30-40% rebooking rate
• AI Ramp-up: 40-55%
• AI Full Operation: 55-72%

What Improves Rebooking:

• Checkout rebooking by staff (highest conversion)
• AI follow-up texts 4-6 weeks after visit
• Treatment-specific reminders (“Time for your next Botox?”)
• Package deals incentivizing pre-commitment

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Total Visits

Definition: Cumulative appointments completed by a client Client Loyalty Segments:

• 1-3 visits: New/Trial clients (65% of database)
• 4-10 visits: Regular clients (25%)
• 11+ visits: Loyal advocates (10%)

Visit Frequency by Service:

• Botox: Every 3-4 months
• Hydrafacial: Monthly maintenance
• Laser Hair Removal: 6-8 sessions over 6 months
• Body Contouring: 3-6 sessions over 3 months

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Operational Efficiency Metrics

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No-Show Rate

Definition: Percentage of confirmed appointments where client doesn’t arrive Formula: (No-shows / Total confirmed appointments) × 100 Performance by Phase:

• Before EIP: 25-30% (industry standard)
• AI Ramp-up: 15-20%
• AI Full Operation: 10-14%

How AI Reduces No-Shows:

• Automated SMS reminders (24 hours before)
• Voice call reminders for high-risk appointments
• 2-hour warning texts (“Your Hydrafacial is in 2 hours”)
• Predictive risk scoring based on client history
• Flexible accommodation (“Running 10 min late? No problem!”)

Financial Impact:

• Each no-show costs $200-$1,200 in lost revenue
• A 10-point reduction in no-show rate = $20K-40K annual revenue recovery

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Response Time Average

Definition: Average time from client inquiry to first response Measured In: Seconds (AI responses) or hours (pre-AI) Performance by Phase:

• Before EIP: 3.5-5 hours (12,600-18,000 seconds)
• AI Ramp-up: 30-60 seconds
• AI Full Operation: 10-28 seconds

Why Speed Matters:

• Clients contacting multiple providers book with fastest responder
• After-hours inquiries are captured instead of lost
• Faster response = higher conversion rates (40% improvement)

Breakdown by Channel:

• SMS: 8-12 seconds average
• Web chat: 10-20 seconds
• Voice: 2-5 seconds (immediate answer)
• Social media DM: 15-25 seconds

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Utilization Rate

Definition: Percentage of available treatment room hours that are booked Formula: (Booked hours / Total available hours) × 100 Calculation Factors:

• Rooms per location (3-6 rooms)
• Business hours per day (typically 9 AM - 6 PM)
• Provider availability
• Appointment duration

Performance Targets:

• Below 55%: Underutilized, need more marketing
• 55-65%: Healthy range with buffer for flexibility
• 65-78%: Optimal (AI target range)
• Above 85%: Over-capacity, consider expansion

How AI Improves Utilization:

• Fills gaps in schedule automatically
• Suggests optimal appointment times to clients
• Manages waitlists to backfill cancellations
• Identifies and promotes slow time slots

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Calls Answered vs. Missed

Definition: Ratio of phone calls successfully answered to those that went to voicemail Tracked Metrics:

• Total calls received
• Calls answered (by AI or staff)
• Calls missed/abandoned
• Call duration

Performance by Phase:

• Before EIP: 70% answered, 30% missed
• AI Full Operation: 97% answered, 3% missed

After-Hours Capture:

• AI answers 100% of after-hours calls
• Pre-AI: All after-hours calls went to voicemail
• Represents 15-20% of total daily call volume

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AI Performance Metrics

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AI Resolved

Definition: Number of customer interactions fully handled by AI without staff intervention Resolution Types:

• Booking appointments
• Rescheduling
• Answering service questions
• Providing pricing information
• Confirming appointments
• Simple rebooking

Resolution Rate:

• AI Ramp-up: 50% of interactions
• AI Full Operation: 75% of interactions

Quality Indicators:

• Customer satisfaction with AI interactions
• Booking completion rate
• Zero complaints or negative feedback

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Escalated to Staff

Definition: Conversations AI transferred to human staff Formula: (Escalated conversations / Total AI interactions) × 100 Healthy Escalation Rate: 12-25% Common Escalation Reasons:

• Negative sentiment detected
• Medical questions or concerns
• Billing disputes
• Complex requests (outside policies)
• Client specifically requests human

Escalation by Sentiment:

• Negative: 8-12% of escalations (highest priority)
• Neutral: 10-15% (policy questions)
• Positive: 75-80% (complex requests from satisfied clients)

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Revenue Recovered

Definition: Revenue saved or generated through AI intervention Sources of Recovery:

1. No-Show Prevention: AI reminders that prevent cancellations
2. After-Hours Capture: Bookings made outside business hours
3. Abandoned Call Recovery: Following up on dropped calls
4. Waitlist Optimization: Filling cancelled slots immediately
5. Same-Day Booking: Capturing urgent requests

Calculation Example:

• 5 no-shows prevented × $350 average =$1,750
• 3 after-hours bookings × $450 average =$1,350
• 2 waitlist fills × $850 average =$1,700
• Total daily recovery: $4,800

Monthly Recovery Target: $30K-50K per location

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Conversation Analytics

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Conversation Status

Status Types:

• AI Resolved: Handled completely by AI
• In Progress: Active conversation happening now
• Escalated: Transferred to staff
• Abandoned: Client disconnected/didn’t respond

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Conversation Priority

Priority Levels:

• Urgent: Negative sentiment, medical issues
• Pending: Awaiting staff follow-up
• AI Handling: Being processed by AI

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Sentiment Analysis

Sentiment Categories:

• Positive: 75-80% of conversations (happy, booking successfully)
• Neutral: 15-20% (transactional, informational)
• Negative: 3-5% (complaints, dissatisfaction)

Sentiment Tracking:

• All conversations analyzed for emotional tone
• Negative sentiment triggers automatic escalation
• Trending sentiment by location identifies issues early

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Channel Performance

Interaction Breakdown:

• Voice: 35-40%
• SMS: 30-35%
• Web Chat: 20-25%
• Social Media: 8-12%

Conversion by Channel:

• Voice: 68% (highest trust)
• Web Chat: 65%
• SMS: 62%
• Social: 58% (browsers, less committed)

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Alert Intelligence

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Alert Types

Critical Alerts (require immediate action):

• No-show rate spikes above 25%
• High-CLV clients at risk of churn
• Medical or safety issues
• Double-booked rooms
• System errors

Warning Alerts (address within 24 hours):

• Multiple unbooked slots tomorrow
• Provider nearing capacity
• Inventory running low
• Response times creeping up

Opportunity Alerts (revenue growth potential):

• Service demand surging
• Cross-sell opportunities
• Successful campaign results
• After-hours conversion rates high

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Impact Calculation

Estimated Revenue Impact:

• Based on historical conversion rates
• Considers average service prices
• Factors in client CLV for retention alerts
• Accounts for timing (immediate vs. future)

Priority Formula: Impact Amount × Urgency × Confidence Score

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Location-Specific Performance

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Location Capacity

SoHo Flagship:

• 6 treatment rooms
• 3 providers
• Highest revenue location
• Average daily revenue: $4,000-4,500

Williamsburg:

• 4 rooms, 2 providers
• Average daily revenue: $2,300-2,800

Hoboken:

• 4 rooms, 3 providers
• Average daily revenue: $2,500-3,000

White Plains & Stamford:

• 3 rooms each, 2 providers
• Average daily revenue: $1,600-2,000 each

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Comparative Metrics

When viewing “All Centers”, compare:

• Revenue per location (identify top performers)
• Utilization rate (efficiency comparison)
• No-show rate by location (operations quality)
• New client acquisition (marketing effectiveness)

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Using Analytics for Business Decisions

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Scenario: High No-Show Rate at One Location

Data to Review:

1. No-show rate trend (is it getting worse?)
2. No-show risk by booking channel (online? phone?)
3. Staff confirmation call completion rate
4. AI reminder delivery success

Possible Actions:

• Require deposits for high-value services
• Implement stricter cancellation policy
• Add personal confirmation calls for at-risk bookings
• Review scheduling policies (booking window, same-day limits)

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Scenario: Low Utilization at One Location

Data to Review:

1. Utilization by day of week (which days are slow?)
2. Utilization by time of day (morning vs. afternoon?)
3. Competitor presence in area
4. Marketing spend/results for that location

Possible Actions:

• Create time-specific promotions (“Lunch Break Special”)
• Adjust provider schedules to match demand
• Increase local marketing (social media, local ads)
• Offer packages to fill recurring slow slots

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Scenario: Revenue Growth Opportunity

Data to Review:

1. Which services have highest margins?
2. Which services have longest waitlists?
3. Which services have best rebooking rates?
4. Client demand patterns (what are people asking for?)

Possible Actions:

• Add capacity for high-demand services
• Train additional providers
• Create premium service tiers
• Introduce new high-margin treatments

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Reporting & Exports

The platform provides automated reporting:

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Daily Summary (available each morning)

• Yesterday’s revenue by location
• Bookings completed vs. no-shows
• AI performance metrics
• Outstanding escalations

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Weekly Performance Report

• 7-day revenue trend
• Week-over-week comparisons
• Top performers and challenges
• Action items for upcoming week

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Monthly Business Review

• 30-day metrics vs. previous 30 days
• Location rankings
• Client retention analysis
• ROI of AI system

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Next Steps

• Use the AI Analyst to ask custom questions about your data
• Review the Owner View Guide to understand the dashboard layout
• Check the Staff View Guide to see how your team uses metrics