diff --git a/backend/app/plan/router.py b/backend/app/plan/router.py
index 661858b7..45d87dd3 100644
--- a/backend/app/plan/router.py
+++ b/backend/app/plan/router.py
@@ -59,7 +59,7 @@ def patch_epc(patch, epc_records):
 
 
 def extract_portfolio_aggregation_data(
-    input_properties, total_valuation_increase, recommendations, new_epc_bands
+    input_properties, total_valuation_increase, recommendations, new_epc_bands, property_value_increase_ranges
 ):
     # We aggregate a number of metrics for the portfolio:
     # 1) A breakdown of the number of properties in each EPC band
@@ -69,7 +69,7 @@ def extract_portfolio_aggregation_data(
     # 3) Co2/unit
     #    a) before retrofit
     #    b) after retrofit
-    # 4) Energy bulls/unit
+    # 4) Energy bill/unit
     #    a) before retrofit
     #    b) after retrofit
     # 5) Average valuation improvement/unit
@@ -105,6 +105,8 @@ def extract_portfolio_aggregation_data(
         # Get just the default recommendations
         default_recommendations = [r for r in property_recommendations if r["default"]]
 
+        has_recommendations = len(default_recommendations) > 0
+
         # We can now calculate multiple outputs based on default recommendations
         carbon_savings = sum([r["co2_equivalent_savings"] for r in default_recommendations])
 
@@ -125,6 +127,15 @@ def extract_portfolio_aggregation_data(
         cost = sum([r["total"] for r in default_recommendations])
         sap_point_improvement = sum([r["sap_points"] for r in default_recommendations])
 
+        lower_bound_valuation_uplift = (
+            property_value_increase_ranges[p.id]["lower_bound_increased_value"] -
+            property_value_increase_ranges[p.id]["current_value"]
+        )
+        upper_bound_valuation_uplift = (
+            property_value_increase_ranges[p.id]["upper_bound_increased_value"] -
+            property_value_increase_ranges[p.id]["current_value"]
+        )
+
         agg_data.append({
             "pre_retrofit_epc": p.data["current-energy-rating"],
             "post_retrofit_epc": new_epc_bands[p.id],
@@ -135,14 +146,22 @@ def extract_portfolio_aggregation_data(
             "pre_retrofit_energy_consumption": pre_retrofit_energy_consumption,
             "post_retrofit_energy_consumption": post_retrofit_energy_consumption,
             "cost": cost,
-            "sap_point_improvement": sap_point_improvement
+            "sap_point_improvement": sap_point_improvement,
+            "lower_bound_valuation_uplift": lower_bound_valuation_uplift,
+            "upper_bound_valuation_uplift": upper_bound_valuation_uplift,
+            "has_recommendations": has_recommendations
         })
 
     agg_data = pd.DataFrame(agg_data)
 
-    n_units_to_retrofit = len(agg_data)
+    n_units_to_retrofit = agg_data["has_recommendations"].sum()
 
-    valuation_improvment_per_unit = total_valuation_increase / n_units_to_retrofit
+    valuation_improvement_lower_bound_per_unit = (
+        agg_data["lower_bound_valuation_uplift"].mean()
+    )
+    valuation_improvement_upper_bound_per_unit = (
+        agg_data["upper_bound_valuation_uplift"].mean()
+    )
 
     total_carbon_saved = agg_data["pre_retrofit_co2"].sum() - agg_data["post_retrofit_co2"].sum()
     total_sap_points = agg_data["sap_point_improvement"].sum()
@@ -150,6 +169,17 @@ def extract_portfolio_aggregation_data(
     def format_money(amount):
         return f"£{amount:,.0f}"
 
+    valuation_improvment_per_unit = format_money(
+        total_valuation_increase / n_units) + (f" ({format_money(valuation_improvement_lower_bound_per_unit)} - "
+                                               f"{format_money(valuation_improvement_upper_bound_per_unit)})")
+
+    valuation_return_on_investment = (
+        str(round(total_valuation_increase / agg_data["cost"].sum(), 2)) +
+        f" ("
+        f"{agg_data['lower_bound_valuation_uplift'].sum() / agg_data['cost'].sum():,.2f} - "
+        f"{agg_data['upper_bound_valuation_uplift'].sum() / agg_data['cost'].sum():,.2f})"
+    )
+
     aggregation_data = {
         "epc_breakdown_pre_retrofit": json.dumps(
             reformat_epc_data(agg_data["pre_retrofit_epc"].value_counts().to_dict())
@@ -167,11 +197,11 @@ def extract_portfolio_aggregation_data(
             round(agg_data["pre_retrofit_energy_consumption"].mean())) + "kWh",
         "energy_consumption_per_unit_post_retrofit": str(
             round(agg_data["post_retrofit_energy_consumption"].mean())) + "kWh",
-        "valuation_improvement_per_unit": format_money(valuation_improvment_per_unit),
+        "valuation_improvement_per_unit": valuation_improvment_per_unit,
         "cost_per_unit": format_money(agg_data["cost"].mean()),
         "cost_per_co2_saved": format_money(agg_data["cost"].sum() / total_carbon_saved),
         "cost_per_sap_point": format_money(agg_data["cost"].sum() / total_sap_points),
-        "valuation_return_on_investment": str(round(total_valuation_increase / agg_data["cost"].sum(), 2))
+        "valuation_return_on_investment": valuation_return_on_investment,
         # TODO: Could we add 10yr carbon credits value?
     }
 
@@ -446,6 +476,7 @@ async def trigger_plan(body: PlanTriggerRequest):
         property_valuation_increases = []
         session.commit()
         new_epc_bands = {}
+        property_value_increase_ranges = {}
         for i in range(0, len(input_properties), BATCH_SIZE):
             try:
                 # Take a slice of the input_properties list to make a batch
@@ -460,6 +491,7 @@ async def trigger_plan(body: PlanTriggerRequest):
                     new_epc_bands[p.id] = new_epc
 
                     valuations = PropertyValuation.estimate(property_instance=p, target_epc=new_epc)
+                    property_value_increase_ranges[p.id] = valuations
 
                     # Your existing operations
                     property_details_epc = p.get_property_details_epc(
@@ -527,7 +559,8 @@ async def trigger_plan(body: PlanTriggerRequest):
             input_properties=input_properties,
             total_valuation_increase=total_valuation_increase,
             recommendations=recommendations,
-            new_epc_bands=new_epc_bands
+            new_epc_bands=new_epc_bands,
+            property_value_increase_ranges=property_value_increase_ranges
         )
 
         aggregate_portfolio_recommendations(