diff --git a/backend/SearchEpc.py b/backend/SearchEpc.py
index f93fc5f0..d7e1ae58 100644
--- a/backend/SearchEpc.py
+++ b/backend/SearchEpc.py
@@ -516,7 +516,12 @@ class SearchEpc:
             estimation_data = epc_data[[key, "weight", "lodgement-datetime"]].copy()
             estimation_data = estimation_data[~pd.isnull(estimation_data[key])]
             estimation_data = estimation_data[~estimation_data[key].isin(Definitions.DATA_ANOMALY_MATCHES)]
-            estimation_data[key] = estimation_data[key].astype(vartype)
+            if vartype == "Int64":
+                # We have some edge cases where we get the error "invalid literal for int() with base 10: '1.0'"
+                # so this handles this
+                estimation_data[key] = estimation_data[key].astype(float).astype(vartype)
+            else:
+                estimation_data[key] = estimation_data[key].astype(vartype)
 
             if estimation_data.shape[0] == 0:
                 estimated_epc[key] = None
diff --git a/etl/testing_data/estimate_epc.py b/etl/testing_data/estimate_epc.py
index c72df6af..2203402a 100644
--- a/etl/testing_data/estimate_epc.py
+++ b/etl/testing_data/estimate_epc.py
@@ -7,6 +7,7 @@ from tqdm import tqdm
 from dotenv import load_dotenv
 from utils.logger import setup_logger
 from backend.SearchEpc import SearchEpc, vartypes
+from etl.epc.settings import BUILT_FORM_REMAP
 
 ENV_FILE = Path(__file__).parent / "backend" / ".env"
 
@@ -20,6 +21,12 @@ EPC_AUTH_TOKEN = os.getenv("EPC_AUTH_TOKEN")
 
 load_dotenv(ENV_FILE)
 
+CATETORICALS_TO_IGNORE = [
+    "postcode", "constituency", "local-authority", "built-form", "property-type", "address1", "constituency-label",
+    "building-reference-number", "address2", "posttown", "transaction-type", "lmk-key", "address3",
+    "local-authority-label", "county",
+]
+
 
 def check_numeric_performance(estimated_value, actual_value):
     # If we don't have anything to compare against, return None
@@ -49,6 +56,10 @@ def app():
     if len(numerical_vartypes) + len(str_var_types) != len(vartypes):
         raise ValueError("Not all vartypes have been accounted for")
 
+    # Drop some keys that aren't important
+    for k in CATETORICALS_TO_IGNORE:
+        str_var_types.pop(k, None)
+
     directories = [entry for entry in DATA_DIRECTORY.iterdir() if entry.is_dir()]
 
     directory_sample = choices(directories, k=N_DIRECTORIES)
@@ -80,11 +91,16 @@ def app():
             searcher = SearchEpc(address1, postcode, auth_token=EPC_AUTH_TOKEN, os_api_key="")
             searcher.uprn = epc["uprn"]
 
+            # Perform the same remapping for built-form as in the Property class for this test, in case we get (e.g.)
+            # Enclosed End-Terrace
+            built_form = BUILT_FORM_REMAP.get(epc["built-form"], epc["built-form"])
+
             estimated_epc = searcher.estimate_epc(
-                property_type=epc["property-type"], built_form=epc["built-form"], lmks_to_drop=lmks_to_drop
+                property_type=epc["property-type"], built_form=built_form, lmks_to_drop=lmks_to_drop
             )
 
             # We now compare the difference between the estimated and original
+            # TODO: We can convert windows and lighting to numeric versions and estimate how close we are
             numeric_performance = {
                 key: check_numeric_performance(estimated_epc[key], epc[key]) for key, value in
                 numerical_vartypes.items()