ApartmentIQ is multifamily’s all-in-one, daily data platform covering 40M units. It integrates daily property and market signals into modern tools for market surveys, investment research, and revenue management. Owners, operators, and investors use ApartmentIQ to benchmark performance, price confidently, and move faster – trusted by 65% of the NMHC Top 50.

ApartmentIQ offers 4 user roles: Admin, Manager, Editor, and Read Only Users. Please use the image below to understand what each role is able to control within the Research and Explore tools. 

• Research Report Creation: Available to all roles (Admin, Manager, Editor, Read Only).
• Sharing Research Reports: Available to all roles.
• Edit Comps within Research Reports: Available to Admin, Manager, and Editor only.
• Add or Remove Users: Available to Admin only.

While Admin Users can manage basic permissions via the Manage Users tab on the left-hand side of the dashboard, access to Explore Pro, Pro+, and the Research feature is sold on a pay-per-seat basis. To enable these specific tiers for your team members, please contact your Customer Success Manager or reach out to our Support Team at support@apartmentiq.io.

Explore Lite

The perfect entry point for focused research. Explore Lite is designed for users who need high-quality, real-time data for specific markets without the complexity of deep-tier analytics. It provides:

• Essential Property Data: Access to core unit-level metrics and current market conditions.
• Streamlined Mapping: A simplified interface to view property locations and basic market boundaries.
• Efficient Benchmarking: Compare subject properties against the market or submarket competitors to gauge immediate market positioning.

Explore Pro

For the power user who requires a comprehensive, 360-degree view of the landscape. Explore Pro eliminates static research with:

• Daily Market Intelligence: Access unit-level rents, occupancy, and five years of historical data to stay ahead of the curve.
• Unified Research & Reporting: Combine supply pipelines, demographics, and custom rent comps into export-ready insights for faster underwriting.
• Forecasting & Strategy: Leverage zip-code rent forecasts and interactive mapping to identify market risks and site selection opportunities.

Explore Pro+ Transactions

Includes everything in Pro, plus an additional layer of intelligence with 10+ years of sales history, cap rates, and RCA-sourced ownership filters for those focused on acquisitions and capital markets.

All ApartmentIQ customers have access to Lite. For Pro and Pro+, you will see the specific advanced data layers (like forecasts or 10+ years of sales history) active in your account. Your account Admin can also verify permissions via the Manage Users tab.

Daily Updates: Data is updated daily from property websites, whereas legacy systems may be 30 to 60 days out of date.

Multifamily Focus: Unlike competitors who cover office or retail, ApartmentIQ is built specifically for multifamily.

User Interface: Features a modern and intuitive interface compared to dated legacy tools.

Transaction History (Pro+): Sourced from Real Capital Analytics (RCA), the "gold standard" of commercial data.

Demographics: A combination of the US Census, ACS, and Bureau of Labor Statistics, updated biannually.

New Supply: Sourced from public records, building permits, government databases, and news. Updated daily or weekly.

Property Images: Sourced from Rentable.co and available for nearly 90% of properties.

The history is robust and dates back to 2005

In Planning: The project has obtained necessary building permits and entitlements from local authorities, allowing construction to begin legally. At this stage, the property is approved but ground has not yet been broken. It represents early pipeline supply that may or may not proceed promptly.
 

Scheduled Construction: The project is planned and scheduled to start construction soon, with financing, contractors, and timelines in place, but active building work has not yet commenced. This is a pre-construction planning stage where the project is committed but not yet underway.
 

Under Construction: Active vertical construction is ongoing. Ground has been broken, and the building is being erected. Units are not yet complete or available for occupancy, but the project is contributing to near-term future supply.
 

Lease Up: Construction is complete (or substantially complete), and the property is actively marketing and leasing units to reach full occupancy. This phase starts with a certificate of occupancy and focuses on filling units, often with incentives. It typically lasts 6–18 months depending on market conditions and project size, until reaching stabilized occupancy levels.
 

Stabilized: The property has achieved consistent high occupancy (typically 90–95% or higher, often sustained for a period like 3 months) and steady operational performance. Net operating income is reliable, qualifying for permanent financing, and the asset is considered mature with normalized rent growth and low vacancy.

Properties may have multiple Assessor's Parcel Numbers (APNs) primarily because they were historically separate lots, purchased at different times, or sit across different tax sections. Although managed as one unit by the owner, the county keeps separate tax records for each piece, often arising from boundary adjustments, mergers, or subdivisions.

Our forecasts are powered by a neural network time series model that analyzes historical rent and occupancy trends alongside a wide range of external factors like employment, inflation, and new supply. It learns patterns over time and across markets to generate forward-looking projections. The model is designed to capture both local dynamics (property or submarket) and broader economic trends.

ApartmentIQ monitors daily unit-level pricing across over 40 million units, backed by five years of historical data.

A daily cadence matters. Instead of sampling the market every few months, we track how the industry behaves in real time. That gives our model a clean starting point.

The model combines three core inputs:

• Historical performance (long term-rent growth histroy and occupancy trends)

• Macroeconomic conditions (employment trends, CPI, unemployment, income, inflation, retail spending patterns, population shifts, etc.)

• Supply-side dynamics (development pipelines with delivery timelines, building permit activity, etc.)

Together, these help explain both demand and supply pressures, which are the primary drivers of rent and occupancy outcomes.
 

On a one-month horizon, forecasts average within 0.47 percentage points of actual year-over-year rent growth.

Over a twelve-month horizon, they are typically within 1.46 percentage points.

ApartmentIQ’s forecasting engine is built on deep learning, allowing our model to recognize complex patterns that traditional methods often miss.

Before generating any market projections, our model is trained on nearly a decade of historical rent data. During this phase, it learns recurring patterns like seasonality, long-term cycles, and how different market forces interact over time.

Just as important, we validate the model against data it hasn’t seen before. This testing phase helps confirm that forecasts aren’t simply memorizing historical data but can adjust to new conditions.

Only after that validation step does the model retrain on the full data set and begin generating future forecasts.

The model produces forecasts at multiple levels, including metro, submarket, ZIP code, and property. It combines local historical data with broader economic signals, allowing it to reflect both micro-level performance and macro-level trends. This helps ensure forecasts are relevant for specific assets while staying grounded in the bigger picture.

The model updates on a monthly basis using large language models that factor in labor forces, construction supply, inflation, and demographics, rather than waiting for the end of a quarter. So if those shifts come, we don't need to wait for the next quarter to actually adjust everything.

It comes down to the level at which each forecast is generated. Rent growth and occupancy are forecast at the individual property level, so those projections remain visible regardless of how the view is filtered. Absorption and deliveries, on the other hand, are forecast at the submarket- and metro-level. We don't currently generate forecasts for these metrics below that level of geography, so when a filter narrows the view beyond a submarket, the app drops those forecast lines.

The forecast reflects the underlying economic and supply signals in the data, not a fixed assumption. For example, strong employment growth or limited new supply can lead to more optimistic projections, while rising supply or weakening economic indicators can push forecasts lower. Because the model is forward-looking, it may sometimes diverge from recent trends if leading indicators suggest a change in direction.

The upside and downside views are scenario ranges based on the model’s probabilistic outputs, which reflect the range of outcomes the model considers plausible. Specifically:

• Baseline = median (50th percentile), representing the most likely outcome
• Upside = approximately the 75th percentile, representing a scenario where conditions trend more favorably than expected
• Downside = approximately the 25th percentile, representing a scenario where conditions are somewhat softer than expected

In practical terms, the upside scenario can be thought of as a reasonable expansionary case—for example, stronger employment growth, steady demand, or more limited supply pressure than anticipated. The downside scenario reflects a moderate softening environment, such as slower demand growth, slightly elevated vacancy, or higher-than-expected supply. These scenarios are intended to capture a realistic range of outcomes that are useful for planning, underwriting, and risk assessment under typical market uncertainty.

We intentionally include periods like COVID-19 and past downturns in the training data. The model learns how rent and occupancy responded under those conditions and links those outcomes to macroeconomic drivers. This allows it to better understand how similar shocks may impact the market in the future, rather than treating those periods as noise.

Vacancy = how many units ARE empty (now). Vacancy is measure of unoccupied units divided by total units. It is the opposite of occupancy... if 90% of the units are occupied, the vacancy is 10%.

Exposure = how many units WILL BE empty (in the future). Exposure is an estimate of future vacancy, based on: current vacancy and the leases that will start soon or end soon. That estimated future vacancy is divided by the total number of units.

Since we rely on public information, we cannot know the exact vacancy or exposure. So, we look at the number of units that are advertised (every day) and combine that with other information to calculate vacancy and exposure. (The "other information" includes: total number of units, move-in dates, past trends, forecasts, and more.)

Excel/CSV: You can export property lists, portions of the Market Summary, and the market comparison table.

PDF: You can print a PDF of the Market Summary or Property Specific reports. 

Yes, you can filter for properties by ownership or management group and export those lists.

Leased Rent: The average of the most recent rent for each unit in the group, using advertised rents for active units and leased rents for units off the market.

Market Rent: The average rent of the most recently leased units for that group, limited to the last six months.

LTL% (Loss to Lease): Represents the difference between a property's market rent and its actual in-place rent.

Renewal: Percentage of units that are renewed, based on advertised units. 

Renewal Percentage Calculation: (total_units - units_leased_in_the_last_year) / total_units

Yes, lease-ups are included in the exposure number

The transaction history is robust and dates back to 2005.

“Units Seen" represents only the inventory that has been publicly advertised on property websites. This count is typically lower than the "Total Units" or "Estimated" unit counts because it excludes "offline" inventory—such as units under construction, model apartments, or employee housing. 

Particularly in new lease-ups, we can only report on the units management has released to the public so far; as more inventory is marketed, the "Units Seen" count will naturally climb.

Market Surveys for Research empower teams to evaluate opportunities and sharpen underwriting with real-time, market-backed insights. Whether you are vetting an existing asset or a blank plot of land, you can instantly spin up comprehensive research reports tailored to your specific project goals.

Refine data to match your strategy for faster, confident decision-making across the entire property lifecycle.

Tailored Reporting Capabilities

• Acquisition Projects: Instantly generate detailed surveys for existing assets. Evaluate current performance against the broader market to validate your investment thesis and find "hidden gem" upside.
• Development Opportunities: Spin up instant research reports for potential developments. Model various pricing scenarios and unit mixes to ensure your "pencil-to-paper" projections align with future market demand.

What You Can Expect

• Automated Surveys: Effortlessly test unit mix configurations and target rents for any physical asset or hypothetical project.
• Flexible Comp Selection: Hand-pick and refine properties to build a custom peer group, ensuring you benchmark against only the most relevant comparables.
• Daily Performance Signals: Monitor unit-level pricing, floor-plan availability, and concessions to catch emerging market trends 60 days before the competition

In order to share a Research Report with a colleague, head over to the Research function and click the “+ user” icon to the right of your report name. From here, select the user you would like to share the report with. Once selected, you will see their name listed as “people with access”

There is currently no limit. If you have access to the research feature, you can generate as many research reports as you would like. 

Generation: Comps are initially recommended based on pricing, distance, year built, and total units.

Editing: Admin, Manager, and Editor roles can add or remove comps by searching or exploring nearby properties.

Yes - you can export any report you create in either a PDF or Excel format. Simply click “Export” in the top right hand corner of your report to download or schedule for delivery. 

If you are an Admin User, you will see all Research Reports generated in your account. 

If you are any other user role in the system (Manager, Editor, Read Only), you will only see the Research Reports that you create, and any that are shared with you. 

You can now share any of your research reports with anyone else who has the research feature. 

Should you have any continued questions regarding Research Reports, please contact your Customer Success Manager (CSM) or reach out to our Support Team via email at support@apartmentiq.io