Realeflow Likely to Sell Real Estate Database

Reach millions of individuals who are likely to be looking to sell their homes
within the next 90 days, before they list them.

Realeflow (https://realeflow.com/) can identify and predict one of the biggest life event triggers – selling of a home – through artificial intelligence and machine learning applied to vast data resources and experience.

Realeflow’s real estate database includes every US household, and a sellability score of 0 - 1,000 applied at a household level. It provides insightful information on a property owner and property details that permit an analyst and marketer, in combination with the sellability scores, to effectively segment homeowners BEFORE they begin the listing process.

Realeflow Data is managed by Think Data Group in the Snowflake platform.

Fields Include:
-The city of the property address
-Zip code assigned by USPS
-Two letter state abbreviation
-The Retail Sellability Score for that property. Value can be 1-1000.
-The timestamp of the Retail Sellability Score value.
-The Wholesale Sellability Score for that property. Value can be 1-1000.
-The timestamp of the Wholesale Sellability Score value.
-The Investor Sellability Score for that property. Value can be 1-1000.
-The timestamp of the Investor Sellability Score value.
-Realeflow indicator that the owner does not reside in the residence.
-Realeflow indicator that the owner does not reside in the residence and lives out of state.
-Realeflow indicator that the property is owned without mortgage.
-Realeflow indicator that the owner owes more on property than what it is worth.
-Realeflow indicator that the owner has owned the property for more than 10 years and does not reside in the residence.
-Realeflow indicator that the owner has occupied the property for more than 30 years.
-Realeflow indicator that the property has been potentially inherited - parent to child or spouse to spouse.
-Realeflow indicator that the property owner is in some level of financial distress.
-The estimated loan-to-value of property.
-The age of the property.
-The sum of all 4 open lien amounts

Expected Workflow:
-Customer shares target criteria with Think Data Group via a snowflake share for audience selection.
-Think Data Group uses a Snowflake share to provide the customer with customized data sets as requested.

搜集汇总

背景与挑战

背景概述

该数据集通过人工智能和机器学习技术，为美国所有家庭提供0-1000分的售房倾向评分，旨在识别未来90天内可能出售房产的房主。它包含详细的房产地址、业主居住状态、财务指标等多种属性，并通过Snowflake平台由Think Data Group管理，支持客户按需定制数据。