
Tour conversations don’t fit neatly into 9–5.
Tour-related calls were 2.4 times as likely as the overall property-management call mix to arrive outside weekday reference hours.
Read the analysisThe Call Report · September 2026
Original data on the conversations that keep businesses moving. Built for property managers, and anyone thinking seriously about AI agents.
Featured finding · Property management
Tour-related calls were 2.4 times as likely as the overall property-management call mix to arrive outside weekday reference hours.
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Tour-related calls were 2.4 times as likely as the overall property-management call mix to arrive outside weekday reference hours.
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A small group of frequently returning caller numbers accounts for a large share of property-management phone traffic.
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Rapid recontacts are common in this sample. Measuring them can reveal patterns that an average handle-time metric misses.
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Plumbing and leaks appeared in one-quarter of maintenance-topic calls, ahead of the other selected repair categories we measured.
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A strict phrase screen found explicit status requests in roughly one in ten application-topic calls.
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In 17.6% of detected human-request calls that later logged a transfer, the AI produced at least five more response turns first.
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The workweek was uneven in this property-management sample, with Monday generating the most calls.
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In the same set of calls, short greetings lead when calls receive equal weight. Long greetings lead when organizations receive equal weight.
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Almost 30% of eligible call records had no recorded caller speech. That is a denominator question before it is a performance metric.
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The long tail of call duration carries a disproportionate share of total time across the observed AI-agent sample.
Read the analysisA clear view of the evidence. This edition analyzes one fixed observation window. The property-management subset contains 27,103 calls from 19 organizations. These are descriptive findings from Frontdesk customers, with specific definitions and limitations—not estimates for the entire industry.
Read how we selected the sample and calculated the findings ↗