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Rent Comps: How to Identify Comparable Properties at Scale

Rent comps, or comparable rental properties, are a critical tool used by property managers to accurately price units and remain competitive in their market. Identifying recent lease rates for similar units ensures that pricing is in line with demand, helps monitor market trends over time, and provides justification for renewal offers and rent increases. 

However, traditional methods of manually searching for and verifying rent comps can be extremely tedious. It’s time-consuming, and inefficient, and makes it difficult to identify enough verified comps to inform pricing at scale across an entire property or portfolio. There is a need for more automated, intelligent solutions to unlock comprehensive rent comp data.

Comp Identification Has Gotten Smarter

New technology solutions are emerging that leverage large datasets and intelligent algorithms to automate rent-comp identification. These platforms can look through various listing sites, suggesting data from a much larger set of potential comps for a given property.  It then efficiently filters the data to narrow down the list based on key attributes like location, building type, amenities, unit sizes, year built, and more. This ensures only the most valid comparable properties surface to the top.

While a manual search may uncover 3-5 decent comps over a period of 4-6 days, these automated tools can easily extract 15-20+ highly relevant comparable properties in a matter of minutes. This significantly larger sample size allows for more accurate benchmarking of rental rates against the local market. 

Leveraging large volumes of third-party listing data combined with proprietary internal comps enables intelligent matching at scale. Automated comp identification also allows property managers to adjust search parameters and re-comp on demand to stay on top of market shifts. This data-driven approach provides the accurate, robust rent comps needed to confidently price units and optimize revenue.

Key Attributes To Filter By

When using software that intelligently filters rent comps like ApartmentIQ, there are a few key attributes that you should use to identify the most relevant comparable properties:

  • Location: The geographic proximity to the subject property is one of the most important factors. Comps should be within the same neighborhood or area to control for locational differences in demand.
  • Building type: Filtering comps by structure type (e.g. garden style, high-rise, townhomes) ensures architectural similarities.
  • Amenities: Comparables should feature equivalent amenities like parking, fitness centers, pools, etc. when possible.
  • Unit sizes: Unit square footage, number of bedrooms, and number of bathrooms should match the unit types being priced. 
  • Year built: Comparing against comps from a similar era controls for variances in unit layout, finishes, and overall quality.
  • Accessibility: Factors like proximity to transportation and highways, walkability scores, etc. help account for conveniences.

Isolating for these key characteristics when filtering comps enables an "apples to apples" comparison, leading to more precise rental rate benchmarking. The high-impact attributes get effectively weighted within these intelligent algorithms, helping you maximize them even further.

Verifying The Integrity of This Approach

When evaluating a rent-comp software, you must scrutinize the integrity of the data it provides. There are key verification practices the tool must implement for their comps to be considered truly reliable. 

First, they must compare and cross-check the rental rates for each comp property across multiple listing sites and sources. This allows them to identify and flag significant outliers in the rate data that could skew decisions if included. Outliers must be automatically excluded from the final comp set.

Second, amenities and unit details for each comp must be rigorously fact-checked, either through cross-referencing other sites or directly calling the property. This prevents decisions from being made based on inaccurate or misleading attribute data. 

Additionally, any listing details that seem ambiguous or questionable should be followed up on and clarified directly with the property before using that comp. And a manager's own internal comps should carry the most weight in the analysis since their accuracy is definitive.

Finally, the software must monitor rental rates over time, removing comps with temporarily inflated or discounted rates from the current set. Ongoing rate integrity monitoring is crucial.

Implementing this full suite of verification practices is the only way for a rent comp tool to provide managers with truly reliable, high-integrity data as the foundation for strategic pricing decisions. Be wary of solutions that fail to go the extra mile to rigorously verify their comp data at multiple levels. Reliability is everything. You must understand that not all software that uses intelligent means for gathering rent comp data goes the extra mile to verify. For example, read through the article we wrote comparing ApartmentIQ vs. ILS Data Providers. We uncovered the secrets and reasons why most tools out there might not be as reliable as they like to claim.

Applying Rent Comps for Pricing Decisions

Once a robust set of verified rent comps has been established, property managers can apply the data to make strategic pricing decisions across several areas:

  • Setting and adjusting rental rates: Comps provide the rental rate range for each unit type, allowing managers to price competitively within the local market for new leases. As market conditions shift, comps are monitored and used to adjust prices up or down accordingly.
  • Renewal rate increases: When determining renewal offers, comps justify raising rental rates incrementally while remaining below the market average. Managers can benchmark proposed increases against the market data.
  • Optimizing concession packages: Comps help assess the typical concession packages being offered for each unit type, such as 1 month free on a 12-month lease. Concession offerings can be optimized to stay competitive.
  • Identifying market trends: The comps are tracked over time to spot emerging trends in the market's pricing behavior, demand, and growth. Seeing how a certain building type's rates change provides useful insight.
  • Forecasting and budgeting: Historical comps allow managers to forecast rental income growth and budget for expenses more accurately based on observed market trends.
  • Justifying rate decisions: Comps provide the supporting data to back up rental rate choices if questioned by ownership, investors, or prospective residents. 

With the right insights from local comps, managers can implement strategic pricing optimized to each property's unique market position and performance goals. In other words, you can enjoy all the benefits comps data provides as listed above without sweating about gathering the data yourself.

You won’t even have to bother about the reliability or recency of the data. For example, ApartmentIQ boasts of having less than 1% inaccuracy in data reported, and we track over 14 million units.

Rent comps are an indispensable data foundation that property managers rely on to inform strategic pricing decisions. That's why ApartmentIQ has developed technology solutions that harness massive datasets and intelligent algorithms to automate the process and deliver a robust, highly relevant comp set in minutes.

Our powerful filtering algorithm provides accurate, expansive comps at scale. When pricing based on ApartmentIQ's data, you can profitably benchmark against the market to maximize rental rates and incentives. Our data-driven approach brings efficiency, confidence, and strategic advantage to pricing.

While rent comps will remain a core need, ApartmentIQ is evolving to make the process significantly smoother. Our comp identification will only grow more automated, customizable, and integrated going forward