diff --git a/etl/customers/stonewater/Wave 3 Preparation.py b/etl/customers/stonewater/Wave 3 Preparation.py
index 904afd30..ab640496 100644
--- a/etl/customers/stonewater/Wave 3 Preparation.py	
+++ b/etl/customers/stonewater/Wave 3 Preparation.py	
@@ -3273,7 +3273,7 @@ def revised_model():
     ccs_matching_lookup = []
     for _, home in tqdm(ccs_coordination.iterrows(), total=len(ccs_coordination)):
         # Handle the case that has the wrong postcode in the asset data
-        if home["Name"] in manual_filters:
+        if home["Name"] in ccs_manual_filters:
             filtered = retrofit_assessment_data[
                 retrofit_assessment_data["survey_folder"] == manual_filters[home["Name"]]
                 ].copy()
@@ -3297,13 +3297,16 @@ def revised_model():
                     )
                 )
             if to_filter.sum() == 0:
-                to_filter = filtered["Address"].str.split(",").str[0:2].str.join("") == home["Name"]
-
+                to_filter = filtered["Address"].str.replace("  ,", "").str.split(",").str[0:2].str.join("") == home[
+                    "Name"]
+            if to_filter.sum() == 0:
+                to_filter = filtered["Address"].str.replace("  ,", "").str.split(",").str[0:1].str.join("") == home[
+                    "Name"]
             if to_filter.sum() == 0:
                 # Do a fuzzy match on the name
                 # Find the best filter
-                to_filter = filtered["Address"].str.split(",").str[0:2].str.join("").apply(
-                    lambda x: fuzz.partial_ratio(home["Name"], x) > 9
+                to_filter = filtered["Address"].str.replace("  ,", "").str.split(",").str[0:2].str.join("").apply(
+                    lambda x: fuzz.partial_ratio(home["Name"], x) > 93
                 )
 
             if to_filter.sum() == 0: