7 Voice AI Call Metrics Every PM Should Track

Voice AI Call Analytics: What Property Managers Should Track

Here is a question most property managers cannot answer: How many phone calls did you receive last month?

Not a rough guess. The actual number. Broken down by day, by hour, by property, by topic, by outcome. Most cannot answer because they have never had a way to track it. Calls come in, you answer the ones you can, and the rest go to voicemail. There is no log. No dashboard. No data.

This blind spot is a problem because your phone traffic contains information that can improve your entire operation. High call volume on a specific property might mean the listing needs better check-in instructions. A spike in calls every Friday at 4 PM tells you when to expect the rush. An increase in escalations on amenity questions might mean your knowledge base has a gap.

Voice AI gives you this visibility because every call is automatically logged, transcribed, and categorized. No extra effort from you. The calls happen, the data appears.

This post covers the 7 metrics property managers should track, what each one tells you, and what to do with the information.

The 7 Metrics That Matter

1. Total Call Volume

What it is: The raw count of incoming calls over a given period. Daily, weekly, monthly.

Why it matters: Volume is your baseline. You cannot evaluate anything else (resolution rate, escalation rate, cost savings) without knowing how many calls you actually receive. Most property managers dramatically underestimate their call volume because they only remember the calls they answered.

What to look for:

Weekly trends. Is volume growing as you add properties? Is there a seasonal pattern?
Day-of-week patterns. Weekends typically see higher volume than weekdays for vacation rentals. Friday and Saturday are usually the busiest days.
Month-over-month changes. A sudden increase might signal a listing getting more visibility on OTAs, or a property with a recurring issue driving repeat calls.

Action items: Use volume data to plan staffing for the calls that do get escalated. If you know Fridays are your busiest day, make sure your escalation team is available.

2. Peak Hours

What it is: The hours of the day when call volume is highest.

Why it matters: Guest calls are not evenly distributed across the day. They cluster around check-in time and the evening hours. Understanding when calls peak tells you when your phone support is most critical.

Typical patterns for vacation rentals:

Morning lull: 6-10 AM. Low volume. Guests are sleeping in or starting their day.
Midday activity: 10 AM-2 PM. Moderate volume. Pre-arrival questions, booking inquiries.
Check-in rush: 3-6 PM. Highest volume. Guests arriving, needing access codes, directions, last-minute instructions.
Evening spike: 7-10 PM. High volume. Guests settled in and discovering questions: WiFi, TV, hot tub, amenities.
Late night: 10 PM-2 AM. Lower volume but high urgency. Lockouts, emergencies, issues that cannot wait until morning.

Action items: If most of your calls happen between 4-8 PM, and your current team goes home at 5 PM, you have a three-hour gap where most calls go unanswered. Voice AI covers this gap 24/7, but knowing the peak hours helps you understand where the biggest impact is.

3. Resolution Rate

What it is: The percentage of calls resolved by Voice AI without any human involvement.

Why it matters: This is your core efficiency metric. A high resolution rate means the AI is handling the workload. A low resolution rate means too many calls are reaching your team.

What good looks like:

For a well-configured Voice AI system with a solid knowledge base, resolution rates vary by call category:

Check-in instructions and access codes: 95%+. These are data lookups. The AI has the information.
Amenity and property questions: 85-90%. Depends on how complete your knowledge base is.
Booking inquiries: 70-80%. Some callers want to speak with a human before booking. That is normal.
Late checkout and early check-in requests: 80-85%. Resolved when the turnaround math works. Escalated when it does not.
Complaints and emergencies: 0-10%. These should be escalated. A high resolution rate on complaints would be a red flag, not a positive sign.

Overall target: 75-85% resolution rate across all call types. Below 70% means the knowledge base needs work. Above 90% and you should verify complaints are not being suppressed.

Action items: If resolution rate drops, check the transcripts of escalated calls. What questions is the AI failing to answer? Those gaps become knowledge base updates.

4. Top Question Categories

What it is: A breakdown of what guests are calling about, ranked by frequency.

Why it matters: This tells you where your guest communication has gaps. If 35% of calls are about check-in instructions, your pre-arrival messaging might not be clear enough. If 20% of calls are about parking, maybe the listing description needs a parking section.

Common categories for vacation rentals:

Check-in and access (25-35%): Lockbox codes, door codes, gate access, key location
Amenities and property (15-25%): Pool, hot tub, WiFi, TV, BBQ, washer/dryer
Directions and location (10-15%): How to find the property, parking location, nearest stores
Booking inquiries (10-20%): Availability, pricing, property details
Early/late checkout (5-10%): Time flexibility requests
Maintenance (5-10%): Something broken or not working
Complaints (3-5%): Cleanliness, noise, unmet expectations

Action items: The top category is your biggest opportunity. If check-in calls dominate, invest in better pre-arrival communication: send check-in instructions earlier, include photos of the entrance, add a video walkthrough. Every call you prevent through better proactive communication is a call the AI does not need to handle.

5. Average Call Duration

What it is: The average length of a Voice AI call, from answer to hangup.

Why it matters: Duration is a proxy for efficiency. Shorter calls generally mean the AI resolved the issue quickly. Longer calls might mean the guest had multiple questions, or the AI took a roundabout path to the answer.

Benchmarks:

Quick info lookup (lockbox code, WiFi password): 30-60 seconds
Standard question (amenity info, directions): 60-90 seconds
Multi-question call (check-in instructions + parking + WiFi): 2-3 minutes
Booking inquiry (availability check, pricing, property details): 3-5 minutes
Escalated call (complaint, emergency, complex issue): Varies

Average across all call types: 90-120 seconds is typical for a well-configured system. If your average is above 3 minutes, check whether the AI is being too verbose or struggling to find information.

Action items: Track duration trends over time. A rising average might mean the AI is encountering more complex questions as the easy ones get prevented through better messaging. A falling average usually means the knowledge base is improving.

6. Escalation Rate

What it is: The percentage of calls that Voice AI transfers to a human.

Why it matters: Escalation rate is the inverse of resolution rate, but it deserves its own analysis because escalations are where your human time is spent. Understanding why calls escalate tells you how to reduce that time.

Healthy escalation breakdown:

Complaints: Should always escalate. Guests need empathy and authority.
Maintenance emergencies: Should always escalate. These require action.
Complex booking requests: Group bookings, special accommodations, custom pricing. Reasonable to escalate.
Owner calls: Always escalate. Financial and relationship discussions.
Knowledge gaps: The AI did not have the answer. This is the only escalation type you can reduce.

Action items: Review escalated call transcripts weekly. Separate the escalations that should have been escalated (complaints, emergencies) from the ones that should not have been (the AI just did not know the answer). The second group is your improvement list.

7. Calls by Property

What it is: Call volume broken down by individual listing.

Why it matters: Some properties generate far more calls than others. Knowing which ones helps you identify operational issues specific to those listings.

What high call volume on a specific property usually means:

Confusing check-in process. If a property generates 3x the check-in calls of similar listings, the access instructions might be unclear.
Recurring maintenance issue. Multiple calls about the same thing (AC not working, hot water taking too long) means something needs to be fixed at the property, not just answered on the phone.
Inadequate listing description. If guests frequently call to ask about amenities, the listing might not describe them well enough.
Layout or location confusion. Properties in complexes, gated communities, or hard-to-find locations generate more "where am I going?" calls.

Action items: Rank properties by call volume per booking. The top 10% are your problem properties. Visit those listings, review the check-in instructions, update the listing descriptions, and fix any recurring maintenance issues. Reducing calls at the source is always better than handling them after they come in.

Turning Data into Action

Tracking metrics is pointless if you do not act on them. Here is a practical framework:

Weekly Review (15 minutes)

Check total call volume and compare to the previous week
Review resolution rate. If it dropped, skim the escalated call transcripts to find gaps.
Glance at peak hours to confirm your escalation team is available during high-traffic times.

Monthly Review (30 minutes)

Analyze top question categories. Has anything shifted? New questions appearing?
Review calls by property. Any listing generating an unusual number of calls?
Check average call duration trends. Getting better or worse?
Calculate cost savings: total calls handled x estimated cost per call at call center rates ($6/call at $1.50/min x 4 min average).

Quarterly Review (1 hour)

Look at 3-month trends across all metrics. Is the system improving?
Identify the top 5 knowledge base gaps and fill them.
Review the top 5 highest-call properties and determine root causes.
Calculate total value: calls handled, time saved, revenue generated from upsell offers made during calls.

The Dashboard View

All of these metrics live in one place. Dimora AI's Dashboard module surfaces call analytics alongside messaging metrics, revenue data, and AI learning progress. You do not need to pull reports from multiple systems or build spreadsheets.

The dashboard shows:

Real-time call volume with hourly and daily views
Resolution and escalation rates with trend lines
Category breakdown with drill-down to individual calls
Property-level call metrics with comparison views
Cost savings calculator updated automatically from call data

For property managers who have never had visibility into their phone channel, this data is often the most eye-opening part of deploying Voice AI. You see, for the first time, what your guests are actually calling about and how much time it was consuming.

Before You Had Data

Without Voice AI analytics, here is what you knew about your phone channel: It was busy. You missed calls. Guests sometimes complained about not being able to reach you.

With Voice AI analytics, you know: You receive 247 calls per month. Peak volume hits at 4:30 PM. 31% of calls are about check-in instructions. Your Legacy Villas property generates 2.4x more calls than the portfolio average. Your resolution rate is 82% and climbing. You are saving an estimated $1,482 per month in call handling costs based on 247 calls at $6 each.

The first number is a feeling. The second is a fact you can act on.

For the complete guide to Voice AI in vacation rentals, including how the AI resolves calls, what it escalates, and production data from 600+ calls, read Voice AI for Vacation Rentals: Everything Property Managers Need to Know. For the ROI picture across all six modules, see AI Operations ROI: What to Expect in the First 90 Days.

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