Our datasets provide real estate professionals with in-depth insights into local properties for the sectors we cover.
For data companies seeking differentiation in the commercial real estate domain, our flexible datasets serve as invaluable building blocks for augmenting existing content. RealAssetData's submarket boundaries, property, and mortgage data are pivotal in improving market analytics, enhancing data quality controls, and bypassing restrictive vendor licensing constraints. Unlocking primary use cases including property insights, mortgage lead generation, golden record assembly, market analytics, and robust search capabilities.
Catering to B2B SaaS companies in the real estate landscape, our submarket boundaries enrich proprietary data to deliver enhanced search experiences and benchmark analyses. RealAssetData aids SaaS companies in monetizing their content by providing the framework for proprietary market analytics. Flexible content licensing and data enrichment tools streamline proprietary systems and offer time-saving suggestions for data entry, ensuring efficient operations.
Lenders can leverage our content during the origination and underwriting process to enrich proprietary data warehouses. We have accurate information for the sectors we cover and can assist in augmenting property information, comp analysis and market share studies.
Utilize our content for lead generation, BOV (Broker Opinion of Value) analysis, and REIT portfolio insights tailored for tracking class A markets. Our easily integrable data can seamlessly be incorporated into proprietary CRM systems, enhancing search capabilities and streamlining workflows.
REIT and non-REIT investors leverage our datasets to track peers, REIT activities across markets, and identify non-performing loans. Quantitative trading analysis benefits from our comprehensive datasets, enabling insights into availability, performance trends, and property dispositions.
Our high quality property data from authoritative sources enables underwriters to evaluate Statement of Values (SOVs) to more accurately set insurance premiums. Insurers harness our submarket boundaries to enrich internal systems for effective benchmarking and analytics of CRE assets.
Our standardized datasets from 100+ sources, available through bulk feeds and APIs, serve as invaluable resources for research and analysis. Our data also fuels AI research and ML model pretraining, fostering innovation and insights across these sectors.