diff --git a/flox/core.py b/flox/core.py
index 4179bc236..728d8b186 100644
--- a/flox/core.py
+++ b/flox/core.py
@@ -1465,9 +1465,11 @@ def _assert_by_is_aligned(shape, by):
     for idx, b in enumerate(by):
         if not all(j in [i, 1] for i, j in zip(shape[-b.ndim :], b.shape)):
             raise ValueError(
-                "`array` and `by` arrays must be aligned "
-                "i.e. array.shape[-by.ndim :] == by.shape. "
-                "for every array in `by`."
+                "`array` and `by` arrays must be 'aligned' "
+                "so that such that by_ is broadcastable to array.shape[-by.ndim:] "
+                "for every array `by_` in `by`. "
+                "Either array.shape[-by_.ndim :] == by_.shape or the only differences "
+                "should be size-1 dimensions in by_."
                 f"Received array of shape {shape} but "
                 f"array {idx} in `by` has shape {b.shape}."
             )
diff --git a/flox/xarray.py b/flox/xarray.py
index 35d99b6fa..2a2b27bdc 100644
--- a/flox/xarray.py
+++ b/flox/xarray.py
@@ -265,6 +265,14 @@ def xarray_reduce(
 
     # broadcast to make sure grouper dimensions are present in the array.
     exclude_dims = tuple(d for d in ds.dims if d not in grouper_dims and d not in dim_tuple)
+
+    try:
+        xr.align(ds, *by_da, join="exact")
+    except ValueError as e:
+        raise ValueError(
+            "Object being grouped must be exactly aligned with every array in `by`."
+        ) from e
+
     ds_broad = xr.broadcast(ds, *by_da, exclude=exclude_dims)[0]
 
     if any(d not in grouper_dims and d not in obj.dims for d in dim_tuple):
diff --git a/tests/test_xarray.py b/tests/test_xarray.py
index 0bee41c15..42e6ee17f 100644
--- a/tests/test_xarray.py
+++ b/tests/test_xarray.py
@@ -499,6 +499,12 @@ def test_mixed_grouping(chunk):
     assert (r.sel(v1=[3, 4, 5]) == 0).all().data
 
 
+def test_alignment_error():
+    da = xr.DataArray(np.arange(10), dims="x", coords={"x": np.arange(10)})
+    with pytest.raises(ValueError):
+        xarray_reduce(da, da.x.sel(x=slice(5)), func="count")
+
+
 @pytest.mark.parametrize("add_nan", [True, False])
 @pytest.mark.parametrize("dtype_out", [np.float64, "float64", np.dtype("float64")])
 @pytest.mark.parametrize("dtype", [np.float32, np.float64])