diff --git a/doc/user-guide/groupby.rst b/doc/user-guide/groupby.rst
index b41bf3eeb3a..42acc75a014 100644
--- a/doc/user-guide/groupby.rst
+++ b/doc/user-guide/groupby.rst
@@ -81,9 +81,11 @@ You can index out a particular group:
 
     ds.groupby("letters")["b"]
 
-Just like in pandas, creating a GroupBy object is cheap: it does not actually
+Just like in pandas, creating a ``GroupBy`` object is cheap: it does not actually
 split the data until you access particular values.
 
+To group by multiple variables, see the section on `Grouper Objects`_
+
 Binning
 ~~~~~~~
 
@@ -276,7 +278,15 @@ is identical to
 
     ds.groupby(x=UniqueGrouper())
 
-and
+We can use this to group by multiple dimensions:
+
+.. ipython:: python
+
+    from xarray.groupers import UniqueGrouper
+
+    ds.groupby(lat=UniqueGrouper(), lon=UniqueGrouper()).sum()
+
+Similarly,
 
 .. code-block:: python