diff --git a/features/esm.py b/features/esm.py
index e1cbf8b..e40d4f6 100644
--- a/features/esm.py
+++ b/features/esm.py
@@ -54,7 +54,8 @@ def get_esm_data(usernames: Collection) -> pd.DataFrame:
 
 def preprocess_esm(df_esm: pd.DataFrame) -> pd.DataFrame:
     """
-    Convert timestamps into human-readable datetimes and expand the JSON column into several Pandas DF columns.
+    Convert timestamps into human-readable datetimes and dates
+    and expand the JSON column into several Pandas DF columns.
 
     Parameters
     ----------
@@ -69,6 +70,11 @@ def preprocess_esm(df_esm: pd.DataFrame) -> pd.DataFrame:
     df_esm["datetime_lj"] = df_esm["double_esm_user_answer_timestamp"].apply(
         lambda x: datetime.datetime.fromtimestamp(x / 1000.0, tz=TZ_LJ)
     )
+    df_esm = df_esm.assign(
+        date_lj=lambda x: (x.datetime_lj - datetime.timedelta(hours=4)).dt.date
+    )
+    # Since daytime EMAs could *theoretically* last beyond midnight, but never after 4 AM,
+    # the datetime is first translated to 4 h earlier.
     df_esm_json = pd.json_normalize(df_esm["esm_json"]).drop(
         columns=["esm_trigger"]
     )  # The esm_trigger column is already present in the main df.