Case Study: How a Florida Property Manager Handles 100+ Calls/Week

The Challenge: Sarah manages 35 vacation rental properties across Miami and Fort Lauderdale. During peak season, she receives 120+ calls per week. Before AI, she was drowning in phone calls, missing bookings, sacrificing family time, and on the verge of burnout.

The Solution: Dimora AI receptionist handles 100% of calls 24/7, autonomously books reservations, routes maintenance requests, and escalates only true emergencies.

The Results: Zero missed calls, 24% revenue increase, 20 hours/week saved, and Sarah finally took a vacation without her phone.

Let's dive into the exact numbers, challenges, implementation process, and lessons learned from Sarah's transformation.

Background: Sarah's Growing Pains

The Business

Sarah's Portfolio (January 2024):

35 vacation rental properties
Mix of condos (Miami Beach) and houses (Fort Lauderdale suburbs)
Average nightly rate: $267
Occupancy rate: 78%
Annual revenue: $2.8M
Team: Sarah + 2 part-time coordinators + cleaning/maintenance vendors

Property breakdown:

12 beachfront condos (1-2 bedrooms)
15 suburban family homes (3-4 bedrooms)
8 luxury waterfront properties (5+ bedrooms)

Guest demographics:

40% families (domestic)
30% couples (romantic getaways)
20% business travelers
10% international tourists

The Pain Points

Sarah's daily reality (Before AI):

Call Volume:

Average: 112 calls/week
Peak season (Dec-Apr): 145 calls/week
After-hours: 47% of calls
Time spent on phone: 28 hours/week

The breakdown:

Booking inquiries: 42 calls/week
Current guest questions: 38 calls/week
Maintenance reports: 19 calls/week
Vendor coordination: 13 calls/week

Missed calls:

Business hours miss rate: 31%
After-hours miss rate: 89%
Total missed per week: 42 calls

Impact of missed calls:

Lost bookings: Estimated 6-8 per week
Revenue loss: $1,600-$2,200/week
Guest frustration: 2-star reviews mentioning "couldn't reach host"

Work-life balance:

Worked 7 days/week
Phone answered at dinner, soccer games, bedtime
Last vacation: 2 years ago (cut short by crisis call)
Sleep disrupted 3-4 nights/week
Relationship strain with family

Sarah's own words (January 2024):

"I was making good money but miserable. The phone controlled my life. I couldn't remember the last time I watched a movie without pausing it for a call. My daughter said, 'Mommy, why do you always love your phone more than me?' That broke my heart. I knew something had to change."

The Tipping Point

The incident that led Sarah to seek automation:

Labor Day Weekend 2023:

Friday evening: Family dinner interrupted 4 times
Saturday: Missed 14 calls while at daughter's birthday party
Sunday: Woken up 3 times overnight with "emergencies" (WiFi password, how to use coffee maker, hot tub temperature)
Monday: Guest left 1-star review: "Host unresponsive during stay"

Sarah's reaction:

"I spent my daughter's birthday on the phone in the parking lot instead of watching her open presents. That was the moment I knew I couldn't keep doing this. There had to be technology to help."

The Research & Decision Process

What Sarah Tried First

Attempt 1: Traditional answering service

Cost: $950/month
Coverage: 24/7
Problem: Generic scripts, no property-specific knowledge, escalated 70% of calls back to Sarah anyway
Duration: 6 weeks (cancelled)

Attempt 2: Virtual assistant (Philippines)

Cost: $800/month
Coverage: 12 hours/day (timezone difference)
Problem: Language barrier confused guests, couldn't access PMS efficiently, still missed after-hours calls
Duration: 8 weeks (let go)

Attempt 3: Hired full-time receptionist

Cost: $42,000/year
Coverage: 9 AM - 5 PM Monday-Friday
Problem: Only covered 21% of hours in week, still missed most calls, receptionist overwhelmed during peak times
Duration: 4 months (quit due to stress)

Sarah's frustration:

"I spent $15,000 on 'solutions' that didn't solve anything. I was ready to give up and just accept that this was my life now."

Discovering Dimora AI

How Sarah found us:

December 2023: Sarah attended a property management conference in Orlando. Heard Dimora AI presentation about AI receptionist specifically built for property management with native Guesty integration.

What caught her attention:

"Built FOR property managers" (not generic answering service)
Native Guesty integration (she used Guesty)
24/7 coverage with intelligent escalation
Handles bookings, maintenance, guest questions autonomously
Other property managers sharing success stories

Sarah's initial skepticism:

"I thought, 'Sure, another company promising magic.' But the Guesty integration was intriguing. And hearing other property managers—people like me—talk about their results made me think maybe this was different."

What convinced her to try:

21-day free trial (risk-free)
Could keep existing setup while testing
Setup claimed to be 48 hours (seemed too good to be true)
ROI calculator showed potential $38K/year benefit

Sarah's decision:

"I figured I'd already wasted $15,000 on failed solutions. What's another free trial? If it didn't work, I'd cancel and accept my fate."

Implementation: The 48-Hour Setup

Sarah's implementation timeline:

Day 1: Tuesday, February 6, 2024

Morning (9:00 AM - 10:30 AM): Initial Configuration

Dimora team scheduled onboarding call
Connected Dimora AI to Sarah's Guesty account
Verified data sync (all 35 properties imported correctly)
Configured pricing rules and availability sync
Duration: 90 minutes

Afternoon (2:00 PM - 4:00 PM): Knowledge Base Building

Uploaded property-specific information:
- WiFi passwords and network names
- Door codes and access instructions
- Parking details for each property
- Check-in/checkout procedures
- House rules
- Appliance instructions
- Local area recommendations
Created emergency escalation rules
Configured vendor contact list
Duration: 2 hours

Evening (7:00 PM - 8:00 PM): Testing

Sarah and team ran test scenarios:
- Booking inquiry (verified pricing accuracy)
- Guest question about WiFi
- Maintenance report (plumbing issue)
- After-hours emergency simulation
All tests passed successfully
Duration: 1 hour

Day 2: Wednesday, February 7, 2024

Morning (9:00 AM - 10:00 AM): Soft Launch

Forwarded after-hours calls to Dimora AI (6 PM - 9 AM)
Kept business hours on existing system
Monitoring first real calls
Duration: 1 hour setup, then monitoring throughout day

First Results:

3 after-hours calls that evening (all handled perfectly)
1 booking secured at 9:47 PM (would have been voicemail before)
2 guest questions answered (WiFi password, checkout time)
Sarah's reaction: "Wait, it actually works?"

Evening (8:00 PM): Full Cutover Decision

Confidence high after successful soft launch
Decided to forward ALL calls to Dimora AI immediately
Set up text notification for emergencies only
Duration: 15 minutes

Day 3 - Week 1: Monitoring & Adjustment

Sarah's monitoring routine:

Morning: Review overnight call summary (5-10 minutes)
Afternoon: Check dashboard for trends (5 minutes)
Evening: Read call transcripts (10-15 minutes)
Adjust AI responses based on feedback

Minor adjustments made:

Clarified parking instructions for 2 properties (guests confused)
Added more detail to early check-in policy
Expanded hot tub troubleshooting guide
Refined emergency escalation criteria (too sensitive initially)

Week 1 results:

118 calls handled
0 missed calls (first time ever)
8 bookings secured (including 3 after-hours)
2 emergency escalations (both legitimate)
Time spent: 3.5 hours reviewing vs. 28 hours on phone

Sarah's reaction:

"I kept waiting for something to go wrong. By Friday, I realized: This is actually working. I slept through the night Thursday—first time in 3 years. I woke up confused because my phone hadn't rung once."

The Results: 6 Months of Data

Comparison: January-March 2024 (Before) vs. April-June 2024 (After)

Call Handling Metrics

Metric	Before AI	After AI	Change
Total calls/week	112	121	+8%
Answered calls	70 (62%)	121 (100%)	+73%
Missed calls	42 (38%)	0 (0%)	-100%
After-hours calls	53/week	57/week	+8%
After-hours answer rate	11%	100%	+809%
Average response time	3.2 hours	<1 second	-99.9%

Key findings:

Call volume increased 8% (better availability attracts more inquiries)
Zero missed calls for 6 months straight
After-hours answer rate went from 11% to 100%

Booking Performance

Metric	Before AI	After AI	Change
Booking inquiries/month	182	197	+8%
Bookings secured	64	82	+28%
Conversion rate	35.2%	41.6%	+18%
After-hours bookings	5/month	18/month	+260%
Average nightly rate	$267	$271	+1.5%
Monthly revenue	$43,200	$53,600	+24%

Key findings:

Conversion rate improved 18% (instant response = more bookings)
After-hours bookings tripled (capturing previously lost revenue)
24% revenue increase ($124,800/year)

Operational Efficiency

Metric	Before AI	After AI	Change
Hours on phone/week	28 hours	2.5 hours	-91%
Maintenance coordination	4.5 hours/week	45 min/week	-83%
Guest communications	8 hours/week	1 hour/week	-87%
Total work hours/week	58 hours	35 hours	-40%
Hours with family	12 hours/week	32 hours/week	+167%

Key findings:

Sarah reclaimed 23 hours/week
Work week normalized from 58 to 35 hours
Family time nearly tripled

Guest Satisfaction

Metric	Before AI	After AI	Change
Average review score	4.6 stars	4.9 stars	+0.3
Communication rating	4.3 stars	5.0 stars	+0.7
Responsiveness mentions	34% of reviews	78% of reviews	+129%
Negative reviews (unresponsive)	8/quarter	0/quarter	-100%
Repeat booking rate	18%	29%	+61%

Key findings:

Communication score reached perfect 5.0 stars
Zero "unresponsive host" complaints
Repeat booking rate increased 61%

Financial Impact

Annual Revenue Increase:

Additional bookings: 18/month × 12 = 216 bookings
Average commission: $287
Additional revenue: $62,000/year

Cost Savings:

Eliminated failed solutions: $15,000/year
Reduced maintenance escalation (better triage): $4,200/year
Prevented bad reviews (reputation damage): $8,000/year (estimated)
Total savings: $27,200/year

Investment:

Dimora AI cost: $2,415/month ($69 × 35 properties)
Annual cost: $28,980

Net ROI:

Revenue increase: $62,000
Cost savings: $27,200
Total benefit: $89,200
Investment: $28,980
Net gain: $60,220
ROI: 208%

Unexpected Benefits

Sarah identified benefits she didn't anticipate:

Step 1: Better Maintenance Triage

Before: Guests reported "AC not working"—Sarah immediately dispatched technician ($175 emergency fee). Often turned out to be thermostat confusion.

After: AI troubleshoots first, walks guest through thermostat settings. Only escalates when truly broken.

Result: 31% reduction in unnecessary vendor calls. Saved $6,450 in first 6 months.

Step 2: Vendor Relationships Improved

Before: Sarah frantically called vendors at odd hours with incomplete information. Vendors frustrated with constant interruptions.

After: AI collects detailed information (photos, description, guest availability) before contacting vendor. Vendors receive organized tickets during business hours.

Result: Faster response times, better vendor pricing (happier vendors = better deals).

Step 3: Team Morale Boost

Before: Sarah's 2 coordinators dreaded peak season (overwhelmed with calls). High turnover.

After: Coordinators focus on strategic work (property inspections, guest experience improvements, marketing) instead of repetitive calls.

Result: Job satisfaction increased, both coordinators still employed (retention improved).

Step 4: Strategic Time Freed Up

Before: Sarah in reactive mode 24/7, no time for business growth.

After: 20+ hours/week available for strategic work.

What Sarah did with extra time:

Negotiated better vendor contracts (saved $12,000/year)
Implemented dynamic pricing (increased revenue 8%)
Expanded portfolio by 5 properties (couldn't have managed before)
Finally took a real vacation (more below)

The Vacation Test

The ultimate validation: Sarah took a 10-day vacation to Italy (June 2024)

Before AI (Why She Couldn't Vacation)

Previous attempt: Bahamas, 2022

Day 1: Received 8 calls about check-in issues
Day 2: Maintenance emergency (AC failure), coordinated from beach
Day 3: Decided to come home early (couldn't relax)
Result: Wasted $3,000, returned more stressed

After AI (Italy Vacation, June 2024)

Setup:

Configured AI to handle everything
Set emergency escalation to text (not call) unless true emergency
Left detailed notes for only 3 scenarios that needed her approval

Daily routine:

Morning: Check 5-minute summary email over espresso
If needed: Approve an outlier booking request (happened twice)
Rest of day: Fully disconnected, phone on airplane mode

Results:

Calls during 10 days: 87 total
AI handled: 85 (98%)
Escalated to Sarah: 2 (both appropriate)
True emergencies: 0
Time Sarah spent working: 15 minutes total (approved 2 bookings outside normal parameters)

Bookings during vacation:

14 bookings secured automatically
$16,800 in revenue
Zero issues with any bookings

Sarah's reaction:

"I cried on day 3. Not from stress—from relief. I was standing in front of the Colosseum, actually present in the moment for the first time in years. My husband said, 'You're actually here with me, not lost in your phone.' We rekindled something I thought we'd lost."

Challenges & Lessons Learned

Not everything was perfect. Here's what Sarah learned:

Challenge 1: Over-Trusting Initially

The mistake: First week, Sarah checked dashboard obsessively every 30 minutes.

The learning: "Let go and trust the system. AI doesn't need micromanaging."

Solution: Set specific check-in times (morning, afternoon, evening) instead of constant monitoring.

Challenge 2: Knowledge Base Gaps

The mistake: Initial setup missed some property-specific details (one property had unique door code reset procedure).

The learning: "First week, review every call transcript. You'll find gaps quickly."

Solution: Spent week 1 filling gaps. By week 3, knowledge base was comprehensive.

Challenge 3: Escalation Sensitivity

The mistake: First escalation rules were too sensitive (AI escalated minor issues).

The learning: "Adjust escalation threshold based on YOUR risk tolerance."

Solution: Refined rules after week 1. Found sweet spot by week 2.

Challenge 4: Team Adjustment

The mistake: Didn't communicate changes to coordinators upfront.

The learning: "Team was confused when calls suddenly stopped. Communication is key."

Solution: Held team meeting explaining AI, new workflows, how their roles evolved. Buy-in improved.

Sarah's Advice for Other Property Managers

Sarah's top 5 recommendations:

1. Start with after-hours first

"Don't go all-in day 1. Test with after-hours calls, build confidence, then expand. That's the safest approach."

2. Review transcripts religiously for first 2 weeks

"You'll find gaps in your knowledge base. Fix them early. After 2 weeks, you can trust and check less often."

3. Give yourself permission to let go

"The hardest part isn't the technology—it's trusting it. You've been doing everything yourself for years. Let AI help."

4. Track the numbers

"I wish I'd documented better before starting. Track your current missed calls, time spent, stress levels. You'll appreciate the change more when you see the data."

5. Use the saved time strategically

"Don't just fill the 20 hours you save with more busy work. Use it to grow your business or spend time with family. That's the whole point."

Where Sarah Is Now (October 2024)

Current state:

Portfolio: Expanded to 40 properties (was 35) Revenue: $3.4M/year (was $2.8M) Work hours: 30-35/week (was 58+) Stress level: "Manageable and sustainable" Sleep quality: 7.8/10 (was 4.2/10) Family satisfaction: "Best it's been in 5 years"

Recent milestones:

Attended daughter's entire school play (no interruptions)
Took 3-day weekend trip with husband (spontaneous, unplanned)
Started mentoring new property managers
Considering expanding to 50 properties (manageable now)

Sarah's reflection:

"AI didn't just save my business—it saved my life. I was heading toward complete burnout, divorce, and health issues. Now I'm thriving. My business is growing, my family is happy, and I actually enjoy what I do again. Best decision I ever made."