Real Estate · Scenario 12

Property Management

Push rents too hard and units sit empty; play it safe and leave money on the table every month. We find the rent that maximises revenue, not just the rent that fills the unit.

Method · Price-elasticity of occupancy

The situation

Property managers face a constant trade-off they rarely quantify: a higher rent earns more per occupied month but risks longer vacancies; a lower rent fills fast but underprices the whole portfolio. Most set rents by matching the building next door and hoping, with no model of how occupancy responds to price.

Vacancy is the silent killer — every empty month is roughly 8% of a unit’s annual income gone — yet there’s no view of the rent level where extra vacancy starts costing more than the higher rent earns.

7.4%
portfolio vacancy
Match-market
how rents are set
23 days
avg unit downtime
No curve
of rent vs occupancy

Where we dig for the truth

We estimate how occupancy responds to rent across the portfolio, then price each unit where total revenue — not just rent — peaks.

Lease & rent-roll historyVacancy & downtimeListing-to-lease timesLocal comparable rentsRenewal vs turnoverConcessions given
Occupancy vs rent levelEach point a unit-period; revenue peaks just below the drop-off0%25%50%75%100%$0$600$1200$1800$2400Monthly rent (CA$)Occupancy (%)

Occupancy holds firm up to about $2,000, then falls sharply. Revenue per unit peaks just below that knee — not at the highest rent the manager could ask.

Our approach — Rent-vs-Vacancy Optimization

We model the rent-occupancy curve for each unit type and set rent at the revenue-maximising point, accounting for the real cost of every vacant day. Renewals get small, model-based increases that keep good tenants rather than risking turnover.

Listings, photos and timing then target the units where vacancy costs the most — turning marketing spend toward measurable revenue protection.

From match-the-market to a revenue curve1Build the historyCombine rent roll,vacancy and downtimeacross the portfolio.2Fit the curveEstimate how occupancyresponds to rent byunit type.3Price to the peakSet rents where totalrevenue, not just rent,is highest.4Cut downtimeAim listings and turnsat the costliestvacancies first.
Annual revenue per unit — before vs afterRent collected net of vacancy$0k$11k$22k$34k$45k$19k$21kStudio$23k$26k1-bed$29k$32k2-bed$34k$38kTownhouseBeforeAfter

Slightly different rents plus shorter vacancies lift net revenue per unit across every type — without a single renovation.

What changes

Same buildings, priced to the curve. Representative for a mid-size residential portfolio.

Representative 90-day movementVacancy rate7.4%3.9%▼ -3.5 ptsAvg. unit downtime23 d11 d▼ -52%Net revenue / unit$26k$30k▲ +15%Portfolio NOI$1.20M$1.43M▲ +19%
Portfolio occupancy (after)96%units occupiedtarget 95%
Why this is not "social media management"
We didn't just list the units on more websites. We found the rent that actually maximises revenue and cut the vacant days that quietly drain a portfolio. Pricing and downtime are math problems — and that's where the real money in management hides.

Frequently asked questions

How do you set the most profitable rent?
We model how occupancy responds to rent for each unit type and price at the point where total revenue — rent minus the cost of vacant days — peaks. Often that is just below the level where occupancy falls off a cliff, not the highest rent you could ask.
Why does vacancy matter so much?
Every empty month is roughly 8% of a unit's annual income gone for good. Pushing rent too high to chase more per month can cost more in extra vacancy than it earns, which a rent-vs-occupancy model makes visible.
How is this different from matching market rents?
Matching the building next door ignores your own units' demand curve. We use your rent-roll and vacancy history to find your revenue-maximising rents. Book a marketing audit.

Want this run on your numbers?

Send your rent roll and vacancy history and we’ll find your revenue-maximising rents.

Book a marketing audit
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