Cutting Vacancy Time With Portfolio-Wide Analytics

The client managed a mix of residential properties across three cities through two separate property management platforms — neither of which talked to the other. Vacancy data lived in spreadsheets. Decisions about pricing, marketing spend, and refurbishment priority were made on gut feel and lagging monthly reports, by which point the profitable window had often already closed. Every week a unit sat empty cost real money, and no one could see the pattern across the whole portfolio.

What they needed wasn’t just reporting — it was foresight. The ability to see which properties were trending toward vacancy before the tenant gave notice, which lease renewal windows were approaching, and where refurbishment spend would generate the fastest return to market. That required unifying messy, siloed data into a single model — and building decision-support tools on top of it.