diff --git a/backend/Property.py b/backend/Property.py
index bc5660e8..dd92a902 100644
--- a/backend/Property.py
+++ b/backend/Property.py
@@ -1078,7 +1078,12 @@ class Property:
         elif self.floor["thermal_transmittance"] is not None:
             self.floor_type = "solid"
         else:
-            raise NotImplementedError("Implement this floor type")
+            # in this case, it's not super clear what the floor type is, so we default - this is a temp
+            logger.warning(
+                f"Could not determine floor type, given: '{self.floor['original_description']}', defaulting to "
+                f"suspended for property {self.uprn}"
+            )
+            self.floor_type = "suspended"
 
     @staticmethod
     def _extract_component(
diff --git a/backend/app/plan/router.py b/backend/app/plan/router.py
index 9216eac0..3ec1bf5f 100644
--- a/backend/app/plan/router.py
+++ b/backend/app/plan/router.py
@@ -120,7 +120,9 @@ async def trigger_plan_entrypoint(body: PlanTriggerRequest):
                     f"Chunk {i} sent to SQS. Rows {index_start}–{index_end}. Message ID: {response.get('MessageId')}"
                 )
 
-                await asyncio.sleep(random.uniform(0.1, 0.5))  # Delay to reduce spike pressure
+                await asyncio.sleep(0.1)  # Small delay to avoid SQS throttling
+
+                # await asyncio.sleep(random.uniform(0.1, 0.5))  # Delay to reduce spike pressure
 
         except Exception as e:
             logger.error("Error during Excel file handling: %s", e)
diff --git a/etl/customers/peabody/Nov 2025 Consulting Project/data_prep.py b/etl/customers/peabody/Nov 2025 Consulting Project/data_prep.py
index e05d82e4..76871b39 100644
--- a/etl/customers/peabody/Nov 2025 Consulting Project/data_prep.py	
+++ b/etl/customers/peabody/Nov 2025 Consulting Project/data_prep.py	
@@ -210,9 +210,9 @@ archetypes = sustainability_data[archetype_variables + ["UPRN"]].dropna().groupb
 archetypes["Cumulative Count"] = archetypes["Count"].cumsum()
 archetypes["Cumulative Proportion"] = archetypes["Cumulative Count"] / archetypes["Count"].sum()
 
-archetypes_85 = archetypes[archetypes["Cumulative Proportion"] <= 0.80]
-archetypes_85["Archetypes_85_reference"] = archetypes_85.index + 1
-archetypes_85["Archetypes_85_reference"] = "Archetype_Sample_" + archetypes_85["Archetypes_85_reference"].astype(str)
+archetypes_95 = archetypes[archetypes["Cumulative Proportion"] <= 0.97]
+archetypes_95["Archetypes_95_reference"] = archetypes_95.index + 1
+archetypes_95["Archetypes_95_reference"] = "Archetype_Sample_" + archetypes_95["Archetypes_95_reference"].astype(str)
 
 # For the sample, look for invalid looking UPRNs and remove them.
 sample_from = sustainability_data.copy()
@@ -227,13 +227,13 @@ sample_from = sample_from[~pd.isnull(sample_from["UPRN"])]
 
 # We now take a sample of the properties that represent 85% of the total properties
 sample_from = sample_from.merge(
-    archetypes_85,
+    archetypes_95,
     on=archetype_variables,
     how="inner"
 )
 
-# We take 1 random property, by archetype 85 reference
-modelling_sample = sample_from.groupby("Archetypes_85_reference").apply(
+# We take 1 random property, by archetype reference
+modelling_sample = sample_from.groupby("Archetypes_95_reference").apply(
     lambda x: x.sample(1, random_state=42)
 ).reset_index(drop=True)
 
@@ -248,7 +248,7 @@ def compare_distributions(full_df, sample_df, column):
 
 for col in archetype_variables:
     print(f"--- {col} ---")
-    print(compare_distributions(sustainability_data, modelling_sample, col))
+    print(compare_distributions(sustainability_data, sample_from, col))
 
 # prepare
 modelling_sample["domna_property_id"] = modelling_sample.index + 1
@@ -263,7 +263,7 @@ modelling_sample = modelling_sample.rename(
     }
 )
 
-modelling_sample["domna_built_form"] = modelling_sample["domna_built_form"].map(
+modelling_sample["landlord_built_form"] = modelling_sample["landlord_built_form"].map(
     {
         "MidTerrace": "Mid-Terrace",
         "EndTerrace": "End-Terrace",
@@ -274,7 +274,7 @@ modelling_sample["domna_built_form"] = modelling_sample["domna_built_form"].map(
     }
 )
 
-if pd.isnull(modelling_sample["domna_built_form"]).sum():
+if pd.isnull(modelling_sample["landlord_built_form"]).sum():
     raise ValueError("Some built forms are null after mapping")
 
 
@@ -292,7 +292,7 @@ modelling_sample.to_excel(
     "/Users/khalimconn-kowlessar/Documents/hestia/Customers/Peabody/Nov 2025 Consulting Project/modelling_sample.xlsx",
 )
 # Save the archetype definitions
-archetypes_85.to_excel(
+archetypes_95.to_excel(
     "/Users/khalimconn-kowlessar/Documents/hestia/Customers/Peabody/Nov 2025 Consulting Project/archetypes_85.xlsx",
 )
 # Save the full archetypes
diff --git a/etl/find_my_epc/RetrieveFindMyEpc.py b/etl/find_my_epc/RetrieveFindMyEpc.py
index 2e23c7e6..e0370725 100644
--- a/etl/find_my_epc/RetrieveFindMyEpc.py
+++ b/etl/find_my_epc/RetrieveFindMyEpc.py
@@ -684,6 +684,7 @@ class RetrieveFindMyEpc:
             "Heating controls recommendation": [],
             "Replace boiler with Band A condensing boiler": ["boiler_upgrade"],
             "Band A condensing gas boiler": ["boiler_upgrade"],
+            "Install Band A condensing heating unit": ["boiler_upgrade"],
             "Solar panel recommendation": [],
             "Double glazing recommendation": [],
             "Solid wall insulation recommendation": [],