A curated list of 20 real estate use cases for external data

Real estate is a constantly evolving industry. Founders of real estate companies know better than anybody else that staying ahead is crucial for success. Therefore, external data has become a vital tool for real estate companies to make informed decisions, stay competitive, and ultimately increase revenue. The main goal of the following list is to share some uncommon growth hacking real estate use cases based on external data. Everything is based on our experience and research.

Uncommon real estate use cases

1. Analysis of local transportation patterns to identify the most convenient and accessible locations for new properties.
2. Use of satellite imagery to assess the condition of properties and surrounding areas.
3. Use of weather data to predict demand for properties based on seasonal and climate changes.
4. Analysis of school district boundaries to identify the most desirable areas for families with children.
5. Use of crime data to identify high-risk areas for property investment.
6. Use of social media data to monitor customer sentiment and preferences.
7. Analysis of real estate market trends and patterns to identify areas for investment opportunities.
8. Use of air quality data to identify areas with high levels of pollution, which can impact property values.
9. Analysis of housing prices and trends in neighboring cities and states to inform investment decisions.
10. Use of online reviews and ratings to improve customer service and satisfaction.
11. Use of location data to analyze the popularity of local restaurants, shops, and other amenities.
12. Analysis of housing demand data to identify areas with high rental demand, which can be a good indicator of investment potential.
13. Use of data from local housing authorities to better understand regulations and policies that may impact property values.
14. Analysis of customer feedback data to identify areas for improvement in the buying and selling process.
15. Use of online job listings to identify areas with high levels of employment and economic activity.
16. Analysis of local housing supply and demand data to identify areas with a high demand for rental properties.
17. Use of customer survey data to identify areas where customers are more likely to be interested in purchasing properties.
18. Exploration of data from real estate associations to better understand market trends and patterns.
19. Use of data from government agencies to identify areas with high levels of economic growth and development.