A pricing analyst knows how far rent can rise on a two-bedroom with a three-year resident before that resident starts researching the market. (Or she has her agent do it for her. But that is a subject for a different day). They set the renewal just under that price point.
Alfred Marshall formalized price elasticity in 1890: how much demand shifts when price moves. Every renewal offer considers the math. At which price, in this market, does renewing beat the cost and hassle of moving?
Here’s the math: On a $1,500 unit, a 5% bump adds $75 a month. One vacant month costs $1,500, which equals twenty months of that increase, before you pay for the unit make-ready or the marketing. Push past the line, and the turn erases the gain.
Elasticity behaves like a slope. Each step up loses a few more renewals, and the slope changes by unit type, floor plan, view, and tenure. A portfolio-wide percentage treats all of those the same, and you discover the slope by losing residents.
Build your own read instead:
- Pull two years of renewal offers and outcomes, broken out by unit type and tenure.
- Test increases in small bands and track acceptance at each one.
- Watch the public market: advertised rents (aka: street rents) and concessions in your submarket. Don’t forget about your shadow markets like BTR and SFR.
Critical Item of Note: Keep that work internal, as pricing from competitors’ confidential lease data is now a serious antitrust risk.
Then be straight with residents: “Here’s your renewal rate, here’s what’s included, and here’s what comparable units nearby are advertising.” Set the rent where staying is genuinely the better value, and you won’t need to lean on how much they dread moving.
Discussion Prompt: For your most common unit type, at what increase does your own renewal data show acceptance starting to drop, and how confident are you in that number?