Legacy tools won’t future-proof your operations
As budget season kicks off across the multifamily industry, leaders are once again weighing what to carry into the new year—and what to leave behind.
One line item that’s lost its edge both financially and in operational impact? Secret shopping.
Secret shops capture a single staged interaction—a lone data point in a sea of thousands of real conversations. Teams often know when they’re being shopped, so they follow a script, check the boxes, and deliver a “perfect” moment that rarely mirrors the everyday renter or resident experience. The result is skewed data. This data goes into feedback built on exceptions, not patterns, and it’s impossible to train effectively from a sample size that small.
Worse, until now, secret shops never included resident calls—the ongoing interactions that make up a huge portion of a property’s operational reality. That entire side of the business has been a black box for operators, leaving blind spots in training, staffing, and service strategy.
In today’s operational landscape—where complexity has grown and AI now enables full-call visibility—operators are asking a more important question: What’s actually happening on the other 99% of calls?
From staged moments to operational insight
Leading operators are already moving away from reactive, point-in-time evaluations. Instead, they’re shifting toward tools that provide continuous, portfolio-wide visibility into how teams are performing—and what renters are actually experiencing.
What’s emerging is a new category of operational intelligence: always-on call analysis that surfaces trends, pinpoints coaching opportunities, and uncovers the operational issues buried in everyday interactions. Think: why residents are calling, when calls are most often missed, which agents are driving conversion (and which aren’t), and where friction is creeping in. Without visibility into everyday conversations, leaders are flying blind—unable to see missed revenue, uncover training gaps, or prevent avoidable resident churn.
Plus, did we mention teams are happier too? Turns out, it’s easier and less awkward for everyone involved to get feedback from AI evaluating every call you make than from humans you worried are biased.
Why this matters for 2026 planning
In a market defined by tight margins, high expectations, and shifting consumer behavior, leaders can’t afford to operate in the dark. The tools you budget for should deliver more than compliance—they should deliver clarity.
Good news: Getting that kind of clarity is NOT cost-prohibitive. Where a traditional secret shopping program might run tens of thousands per month for a mid-sized portfolio, modern alternatives can provide exponentially more coverage and insight at a fraction of the cost.
Meet Insights, where operational visibility that drives action
Call scoring is only the starting point. The value lies in what the data reveals. The “Insights” if you will…
When AI analyzes every inbound call—prospect and resident—companies don’t just understand individual performance; they unlock patterns that were previously invisible.
- Which properties are missing the most calls (and when)?
- What keeps residents from renewing?
- Where are avoidable issues—like broken gates or payment confusion—causing friction?
These are the kinds of information that if fixed in the renter and resident experience will drive retention, reduce workload for the team, and shape smarter operational decisions. Secret shops can’t surface them. Surveys miss them. But Insights, with 100% call coverage, 120+ language support, and customizable scorecards by asset type, Insights transforms routine phone calls into a strategic advantage.
The takeaway
This isn’t about ripping out legacy tools just to replace them. It’s about recognizing a broader shift: from isolated snapshots to continuous visibility, from opinion to evidence, from staged perfection to real-world performance.
As you budget for 2026, the question isn’t whether to measure leasing performance and resident experience—it’s how. And the smartest operators are choosing systems that scale with the complexity of the job.
