How a 3,300-Unit Multifamily Operator Fills Vacant Units 50% Faster Using an AppFolio Data Warehouse and Power BI

For multifamily operators managing thousands of units across multiple AppFolio accounts, setting the right advertised rent on a vacant unit is the difference between a quick lease and weeks of lost income. This case study shows how a Chicago-area owner-operator with 3,300 units used an AppFolio data warehouse connected to a Power BI dashboard — built by RentViewer — to compare average rents of similar units, spot pricing opportunities in real time, and fill vacant units 50% faster.

Executive Summary

• Who: A multifamily owner-operator managing 3,300 units across Chicago, using two AppFolio accounts — one in-house, one through a third-party property manager
• Problem: Leasing teams had no reliable way to compare a vacant unit’s advertised rent against what similar occupied units were actually renting for
• Complication: Government-subsidized units with above-market rents were skewing averages, making comparisons unreliable
• Failed approach: AppFolio’s native reports combined with Excel formulas became too complex to maintain and too difficult for the broader team to use
• Solution: RentViewer built a custom Power BI dashboard connected to an AppFolio data warehouse, filtering by matching bed/bath count and comparable property type
• What leaders see now: Every vacant unit listed alongside the average rent of comparable occupied units, current market rent, and current advertised rent — side by side
• Result: Vacant units are now filled 50% faster by enabling informed, flexible rent pricing decisions
• Business impact: Units that previously sat dark and produced zero income are now contributing to net cash flow

​The Business Problem

Every day a unit sits vacant, it produces exactly zero revenue.

For a 3,300-unit portfolio, vacancy isn’t just an operational inconvenience — it’s a direct hit to net operating income. The leasing team’s challenge wasn’t motivation. It was information. They didn’t have a reliable, fast way to answer a simple question:

Is our advertised rent competitive enough to get someone to sign a lease this week?

Without a clear answer, leasing teams default to holding rents steady and hoping. Units sit vacant longer than they should. Revenue is lost that can never be recovered.

The “Before” Reality

The team was trying to do the right thing. They pulled reports out of AppFolio, exported data into Excel, and built formulas to calculate average rents on similar units. On paper, the logic was sound.

In practice, it broke down fast.

The formulas grew complex enough that only one or two people could maintain them. Errors crept in. And there was a structural problem no spreadsheet could cleanly solve: the portfolio included government-subsidized units with rents well above market. Those higher rents were pulling up the averages, making comparable units look more expensive than they actually were — and making it harder to know whether the advertised rent on a vacant unit was competitive or not.

When a leasing agent or asset manager wanted a quick answer, they couldn’t get one. The data existed. The insight didn’t.

Why Existing Tools Weren’t Enough

AppFolio is a capable property management platform. But its built-in reporting isn’t designed for cross-portfolio rent benchmarking. It doesn’t easily compare a vacant unit’s asking rent against what similar occupied units are actually leasing for — especially when the data spans two separate AppFolio accounts managed by different organizations.

Excel filled the gap for a while. But spreadsheets don’t scale with a 3,300-unit portfolio. They require manual updates, they break when someone edits the wrong cell, and they can’t be handed off to a whole team without training and risk.

What this operator needed wasn’t more data. They needed a single, reliable view that any team member could open, trust, and act on.

The Solution

RentViewer connected both AppFolio accounts to a centralized data warehouse and built a custom Power BI dashboard tailored to how this operator’s leasing team actually works.

The dashboard does three things that Excel couldn’t:

1. It filters out the noise. Subsidized units are cleanly separated from market-rate units, so averages reflect true comparables. No more skewed numbers pulling decisions in the wrong direction.
2. It surfaces the right comparison automatically. For every vacant unit, the dashboard calculates the average rent of occupied units that match on bed count, bath count, and property type. No formulas to maintain. No manual lookups.
3. It puts three numbers side by side. Average rent of comparable occupied units. Current market rent. Current advertised rent on the vacant unit. Leasing agents and asset managers can see the gap — or the lack of one — instantly.

If there’s room to lower the advertised rent and still meet financial targets, the team knows it. If the unit is already priced competitively, the team knows that too.

The Results

Vacant units are now filled 50% faster.

That’s not a small improvement. For a 3,300-unit portfolio, cutting average vacancy duration in half means units that once sat dark for weeks are now generating rent checks within days.

The operational change is equally significant. Leasing agents no longer wait for a manager to pull a report or rebuild a spreadsheet. Asset managers no longer make pricing calls based on gut instinct or stale data. The whole team works from the same dashboard, the same numbers, and the same logic — updated automatically from live AppFolio data.

Decisions that used to take days now take minutes.

Key Takeaway

“When leasing teams can see exactly how a vacant unit’s asking rent compares to what similar units are actually renting for, they stop guessing — and start filling units faster.”

Q&A

Q: How do you compare average rent of similar units across a large multifamily portfolio? A: The most reliable approach is to connect your property management data to a centralized data warehouse and use a business intelligence tool like Power BI to filter by matching bed count, bath count, and property type. This gives you a real-time comparison without manual spreadsheet work.

Q: Can AppFolio data be used in Power BI dashboards? A: Yes. Through an AppFolio data warehouse integration — such as the one RentViewer provides — property data can be extracted, structured, and connected to Power BI. This allows operators to build custom dashboards that go well beyond AppFolio’s native reporting.

Q: How do you prevent subsidized units from skewing rent averages? A: By tagging and filtering unit types in the data warehouse layer before calculations are run. RentViewer’s solution separates subsidized units from market-rate units so that rent comparisons reflect true market-rate comparables only.

Q: What if we use two different AppFolio accounts — one internal, one third-party managed? A: RentViewer’s AppFolio data warehouse is designed to consolidate data from multiple AppFolio instances into a single reporting environment. Both accounts feed the same dashboard, giving leadership a unified view across the full portfolio.

Q: Is this solution usable by leasing agents, not just analysts? A: That was a core design requirement. The Power BI dashboard is built for everyday use by leasing staff — no formulas, no exports, no training required. Anyone on the team can open it and act on it immediately.

See Exactly Where Your Vacant Units Are Leaving Money on the Table

Your leasing team is making rent pricing decisions every day — often without clear data to back them up. RentViewer’s AppFolio Data Warehouse gives your entire team a single dashboard that shows average comparable rents, market rates, and advertised rents side by side, so you can fill units faster and stop losing income to avoidable vacancy.