HouseCanary has built - and will continue to build - the most comprehensive real estate data set in the marketplace. Every data element included is based on clear reasoning for why this factor matters. HouseCanary tracks the most specific details about a given property, the broadest macroeconomic factors, and everything in between. Their data infrastructure aggregates thousands of data elements from a broad set of data sources. Over 50% of the data used is based on proprietary data calculations as well as data feedback loops from having products in the market.

It started with a business executive and a data scientist, who came together with one mission:

“Imagine...what we would do, if we could understand where real estate prices are going.”

Available tools included data aggregators charging exorbitant prices for incomplete bits of raw data, analysts ineffectively using rear-view looking information to make forward-looking projections, and most information was only available at a county level that lacked the street-level local relevance.

HouseCanary saw a need a to bring better information, analytical rigor, sophistication, and tools to the $20 Trillion US residential real estate market made up of 140M homes, 25,000 ZIP Codes and 80,000 blocks. It would take a different kind of company to build it. That's why HouseCanary was founded.

In this webinar, get a BEHIND THE SCENES look at how HouseCanary uses machine learning and data science to run thousands of simulations

Learn how they run eight individual AVMs, each of which executes different property valuation models. Every day, HouseCanary uses unique ensemble methodology to run thousands of simulations for each property they track. They customize the weight they assign to various data sources to account for regional differences in market trends, economic factors, and demographics.

Join Debra Alban in this tour of ICOR's newest data source, House Canary.

Register at:
Webinar ID: 155-507-867