Largest source of publicly aggregated, real-time rental comps covers 28m units and includes floor plan granularity, amenities and concessions

NEW YORK, June 12, 2024 /PRNewswire/ -- Markerr, a leader in data and AI for real estate, announces the launch of RealRent Comps, a new product delivering unique insight into rental markets for investors, owners, operators and property managers. Integrated within Markerr Data Studio, RealRent Comps provides unprecedented coverage, timeliness and granularity to comps analysis, setting new standards for investment and operational decision-making in the industry. Markerr clients are actively leveraging RealRent Comps to power a range of decisions across the asset life cycle including pricing, asset management, rent optimization and acquisitions and underwriting.

RealRent Comps, accessible via Markerr Data Studio, not only provides advanced search and analytical capabilities but also utilizes Markerr's broad data network to enhance our proprietary comps algorithm. This algorithm leverages machine learning to analyze key property and unit attributes, enabling clients to quickly identify and rank competitive properties. By integrating comprehensive, daily updated data at the floor plan level, users can make informed pricing decisions and evaluate investment potential with greater accuracy and insight.

"Implementing Markerr's data has allowed us to build out proprietary analytics and insight to make data driven decisions at granular levels," said Charlie Garner, Principal, Fulton Peak Capital LLC. "We are excited to expand our relationship with Markerr with the addition of RealRent Comps, which will further enhance our real-time and innovative decision making."

The introduction of RealRent Comps arrives at a time when much of the industry is moving away from rental data sources aggregated via private data sharing and call centers. RealRent Comps provides clients with critical insight into rent trends, comps, pricing and concessions while mitigating risk from private data shared via "give and get" data aggregation models.

In creating the RealRent dataset, Markerr has developed a sophisticated and comprehensive approach to public data aggregation. By integrating data from diverse sources including marketplaces, aggregators, originators, community websites, and authoritative government datasets, Markerr ensures RealRent data is complete, accurate and timely. This rich mix of data, ranging from asking rental rates by floorplan to detailed property features, unit mix, concessions and availability, underpins RealRent's ability to offer real estate professionals, investors, and analysts a multifaceted view of the rental landscape.

Andrew Jenkins, Chief Product Officer at Markerr, highlighted the company's commitment to integrating advanced data science with practical real estate business applications. "Markerr RealRent Comps is steering pivotal decisions among top real estate industry leaders. The integration of AI with our publicly-sourced rental data empowers our client with critical rental insights that dramatically improve strategic decision-making while mitigating risk." Jenkins noted.

Markerr RealRent Comps is immediately available to clients.

About Markerr:
Markerr is at the forefront of the real estate industry, offering innovative data products that empower investors to thrive in multifamily real estate investments. Leveraging real-time data, advanced machine learning, and generative AI, Markerr enables clients to gain a competitive edge and make more confident, efficient decisions. Trusted by leading institutional real estate owners and operators worldwide, Markerr is supported by top investors including RET Ventures, Pretium, and Bridge Investment Group. Visit for further details.

SOURCE Markerr