Making Use of the Realist Sell Score

The Realist Sell Score is now a searchable attribute available under My Search > Customize Search. The Sell Score is based on the Propensity to List model*, now featuring a numerical value (0-1000) that predicts the relative likelihood a property will be listed for sale in the next six months. The user can now select the Sell Score attribute (under Customize Search) and add it to their My Search template. Once selected, the user can search for properties based on the desired sell score value(s) and ranges and then proceed with downloading property detail reports, exporting, or creating mailing labels.

Sell Score Ratings and Values:

  • Very High: 831-1000
  • High: 625-830
  • Moderate: 502-624
  • Low: 354-501
  • Very Low: 0-353

To use the Sell Score Search Attribute:

  • In My Search, navigate to Customize Search > Sales Information > Sell Score.
  • Select Sell Score and add it into the search template and click Save or Apply
  • Now navigate to the My Search panel and locate the Sell Score attribute.
  • Sell Score attribute can be searched using 1 of 3 search operators:
    • Is= to search for properties with a specific sell score (e.g. Is=750)
    • Is Between=to search for properties with between two values (e.g., Is Between=750 to 800)
    • Is Greater Than= to search for properties greater than a specific value (e.g., Is Greater Than=750)

Note: Search By Sell Score is restricted to a single county at a time.


The Realist Score is a valuable data point that allows agents to search for properties that are more likely to become listings. Built using CoreLogic’s Propensity to List model, properties with a “high” score can signify having higher chances of being listed due to market conditions, sales data, valuation, and other proprietary CoreLogic data. This information can help agents and real estate professionals looking to build or refine their prospecting & farming lists.

*The CoreLogic Propensity to List model uses various data sources, including but not limited to market trends, Housing and Urban Development, IRS, and AVM data.


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