diff --git a/data/data-pipeline/data_pipeline/etl/sources/geocorr_alternatives/etl.py b/data/data-pipeline/data_pipeline/etl/sources/geocorr_alternatives/etl.py
index 68c451a2..2ee3aa52 100644
--- a/data/data-pipeline/data_pipeline/etl/sources/geocorr_alternatives/etl.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/geocorr_alternatives/etl.py
@@ -49,6 +49,7 @@ class GeoCorrAlternativesETL(ExtractTransformLoad):
     ZIP_CODE_INPUT_FIELD = "ZCTA5CE20"
     AREA_JOINED_FIELD = "area_joined"
     AREA_ZIP_FIELD = "area_zip"
+    TRACT_AREA = "area_tract"
 
     def __init__(self):
         self.COLUMNS_TO_KEEP = [
@@ -118,4 +119,15 @@ class GeoCorrAlternativesETL(ExtractTransformLoad):
             joined_gdf[self.AREA_JOINED_FIELD] / joined_gdf[self.AREA_ZIP_FIELD]
         )
 
+        # Calculating "size of tract" that is relevant, e.g., the sum of all overlapping
+        # area between the tract and the zip
+        joined_gdf[self.TRACT_AREA] = joined_gdf.groupby(
+            field_names.GEOID_TRACT_FIELD
+        )[self.AREA_JOINED_FIELD].transform(sum)
+
+        # Calculating share of tract in the zipcode (ordered at tract, zip level)
+        joined_gdf[field_names.PERCENT_OF_TRACT_IN_ZIP] = (
+            joined_gdf[self.AREA_JOINED_FIELD] / joined_gdf[self.TRACT_AREA]
+        )
+
         self.output_df = joined_gdf
diff --git a/data/data-pipeline/data_pipeline/score/field_names.py b/data/data-pipeline/data_pipeline/score/field_names.py
index c19bf5cb..a3add9ef 100644
--- a/data/data-pipeline/data_pipeline/score/field_names.py
+++ b/data/data-pipeline/data_pipeline/score/field_names.py
@@ -363,7 +363,11 @@ PERCENT_OF_TRIBAL_AREA_IN_TRACT = (
 
 # GeoCorr alternatives variables
 ZIP_CODE = "Zip code tabulation area (ZCTA)"
-PERCENT_OF_ZIP_CODE_IN_TRACT = "Percent of zip code tabulation area (ZCTA) in tract"
+PERCENT_OF_ZIP_CODE_IN_TRACT = (
+    "Percent of zip code tabulation area (ZCTA) in tract"
+)
+PERCENT_OF_TRACT_IN_ZIP = "Percent of tract in zip code tabulation area (ZCTA)"
+
 
 #####
 # Names for individual factors being exceeded