diff --git a/wise_pizza/cluster.py b/wise_pizza/cluster.py
index 72e35ce..f4e185f 100644
--- a/wise_pizza/cluster.py
+++ b/wise_pizza/cluster.py
@@ -25,6 +25,7 @@ def guided_kmeans(X: np.ndarray, power_transform: bool = True) -> np.ndarray:
 
     best_score = -1
     best_labels = None
+    best_n = -1
     # If we allow 2 clusters, it almost always just splits positive vs negative - boring!
     for n_clusters in range(3, int(len(X) / 2) + 1):
         cluster_labels = KMeans(n_clusters=n_clusters, init="k-means++", n_init=10).fit_predict(X)
diff --git a/wise_pizza/explain.py b/wise_pizza/explain.py
index f49d1af..82ca8f8 100644
--- a/wise_pizza/explain.py
+++ b/wise_pizza/explain.py
@@ -25,6 +25,7 @@ def explain_changes_in_average(
     how: str = "totals",
     force_add_up: bool = False,
     constrain_signs: bool = True,
+    cluster_values: bool = False,
     verbose: int = 0,
 ):
     """
@@ -85,6 +86,7 @@ def explain_changes_in_average(
         how=how,
         force_add_up=force_add_up,
         constrain_signs=constrain_signs,
+        cluster_values=cluster_values,
         verbose=verbose,
     )
 
@@ -118,7 +120,7 @@ def explain_changes_in_totals(
     how: str = "totals",
     force_add_up: bool = False,
     constrain_signs: bool = True,
-        cluster_values: bool=True,
+    cluster_values: bool=False,
     verbose: int = 0,
 ):
     """
@@ -256,7 +258,7 @@ def explain_levels(
     verbose=0,
     force_add_up: bool = False,
     constrain_signs: bool = True,
-    cluster_values: bool=True
+    cluster_values: bool=False
 ):
     """
     Find segments whose average is most different from the global one