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You'll never need to copy and paste from property websites and listing sites again. Just enter a property and get accurate, up-to-date rent comps in seconds.
HelloData delivers rent comps that match appraiser comp selections 9 out of 10 times, and our daily updates capture rents within 3-4% of actual leased rents on rent rolls.
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Median income, home values, crime rates, school ratings. We know how long it takes to collect and analyze this data, so we use AI to determine market similarity for you.
Median income, home values, crime rates, school ratings. We know how long it takes to collect and analyze this data, so we use AI to determine market similarity for you.We select the most comparable buildings, from the most comparable markets, every time.
Our computer-vision algorithms assess real estate quality from millions of listing photos to find you comps with similar levels of finishes.We identify which rent comps that compete for the same residents based on quality of finishes and overlap of amenities.
We collect updated rent, availability and property data from millions of units every day, delivering real-time competitor intel right in your inbox.Our automated rent surveys reduce market analysis time by over 98%, performing 5+ hours of market analysis work in a matter of minutes.
By analyzing listing descriptions and pictures, our algorithms detect more than 200 building and unit level amenities. We find rent comps with similar amenities and similar quality.
Save time on quarterly amenity surveys with our accurate data and common area quality assessment.
We offer detailed Excel exports and flexible APIs to pull in rent comps, expense benchmarks and detailed unit-level rent and availability data right where you work.Whether you want to pull our data into your underwriting models or integrate our APIs with Salesforce and PowerBI, we can help.
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Selecting comps can be subjective, and real estate investors, managers and brokers always have differences of opinion. We take the guess work out of rental comp selection.
Our comp selections are data-driven and transparent, with a detailed similarity breakdown explaining each selection.
