diff --git a/hub/management/commands/import_christian_aid_campaign_organisers.py b/hub/management/commands/import_christian_aid_campaign_organisers.py
new file mode 100644
index 000000000..e6a59f8dd
--- /dev/null
+++ b/hub/management/commands/import_christian_aid_campaign_organisers.py
@@ -0,0 +1,62 @@
+from django.conf import settings
+
+import pandas as pd
+
+from hub.models import AreaData, DataSet
+
+from .base_importers import BaseImportFromDataFrameCommand
+
+
+class Command(BaseImportFromDataFrameCommand):
+    help = (
+        "Import data about number of Christian Aid campaign organisers per constituency"
+    )
+
+    data_file = (
+        settings.BASE_DIR
+        / "data"
+        / "Christian Aid climate campaign organisers - Data.csv"
+    )
+    cons_row = "Constituency"
+    message = "Importing Christian Aid climate campaign organisers data"
+    uses_gss = False
+
+    defaults = {
+        "data_type": "integer",
+        "category": "movement",
+        "subcategory": "supporters_and_activists",
+        "description": "Number of Christian Aid campaign organisers per constituency.",
+        "release_date": "February 2023",
+        "source_label": "Data from Christian Aid.",
+        "source": "https://www.christianaid.org.uk/",
+        "source_type": "google sheet",
+        "table": "areadata",
+        "default_value": 1,
+        "data_url": "",
+        "unit_type": "raw",
+        "unit_distribution": "people_in_area",
+        "comparators": DataSet.numerical_comparators(),
+    }
+
+    data_sets = {
+        "constituency_foe_activists_count": {
+            "defaults": defaults,
+            "col": "organisers",
+        },
+    }
+
+    def get_dataframe(self):
+        df = pd.read_csv(self.data_file)
+        df = (
+            df.groupby("Constituency")
+            .count()
+            .reset_index()
+            .rename(columns={"Postcode": "organisers"})
+        )
+        return df
+
+    def get_label(self, defaults):
+        return f"Number of Christian Aid climate campaign organisers"
+
+    def delete_data(self):
+        AreaData.objects.filter(data_type__in=self.data_types.values()).delete()