Housing Analytics Listing Trends

**Overview**
ListingTrends provides monthly snapshots of time-series housing data at the ZIP Code-level and above.

CoreLogic ListingTrends utilizes deep and broad coverage of MLS data from 2007 forward to aggregate key housing metrics, including leading indicators of house prices, listing inventories, days on market and absorption rates by listing type – new, active, pending, closed and sold.

Product Attributes:
- Property appraisal
- Loan underwriting and origination
- Risk and fraud management
- Real estate market forecasting

**Use cases**
- **Market Analysis** - Housing Analytics Listing Trends can provide key insights into the housing market's status and trends at a granular level. Real estate professionals, investors, and financial institutions can utilize this data to understand the market's direction and make informed strategic decisions.
- **Customer Acquisition** - For real estate agents and brokers, Listing Trends can identify markets with high activity, indicating potential opportunities for customer acquisition. By targeting areas with a high number of listings or short days on the market, they can focus their efforts where they're most likely to find new clients.
- **Pricing Analysis** - By analyzing trends in listing prices, businesses can gain insights into how property values are changing in different areas. This information can be invaluable when setting prices for new listings or advising clients on appropriate offers for existing listings.
- **Demand Forecasting** - Listing Trends can help predict future demand in the real estate market. High activity levels or short average times on the market could indicate strong demand, while an increase in the supply of active listings might suggest a cooling market.
- **Risk Analysis** - For lenders, understanding listing trends can help assess the risk associated with mortgage loans. For example, an area with a high number of listings and a long average time on the market might be riskier than an area where properties sell quickly.
- **Data Quality and Cleansing** - By comparing Listing Trends data with their own data, businesses can identify and correct discrepancies. This ensures they're making decisions based on the most accurate and up-to-date information.

**Product details**
- Datasets represented include Listing Trends by ZIP Code, Listing Trends by County, Listing Trends by CBSA and Listing Trends by State.
- Sample fields include Mean Active Days on Market, Active Number of Listings, Mean Listing Price, Mean Cumulative Days on Market, Mean De-Listed Days on Market, Months Supply of Active Listings, Market Velocity and Mean Sold List Price.