diff --git a/pymc_marketing/mmm/transformers.py b/pymc_marketing/mmm/transformers.py
index bb12b4b6a..a8a6304c6 100644
--- a/pymc_marketing/mmm/transformers.py
+++ b/pymc_marketing/mmm/transformers.py
@@ -20,6 +20,7 @@
 import numpy.typing as npt
 import pymc as pm
 import pytensor.tensor as pt
+from pymc.distributions.dist_math import check_parameters
 from pytensor.tensor.random.utils import params_broadcast_shapes
 
 
@@ -235,6 +236,10 @@ def geometric_adstock(
        with carryover and shape effects." (2017).
 
     """
+    alpha = check_parameters(
+        alpha, [pt.ge(alpha, 0), pt.le(alpha, 1)], msg="0 <= alpha <= 1"
+    )
+
     w = pt.power(pt.as_tensor(alpha)[..., None], pt.arange(l_max, dtype=x.dtype))
     w = w / pt.sum(w, axis=-1, keepdims=True) if normalize else w
     return batched_convolution(x, w, axis=axis, mode=mode)
diff --git a/tests/mmm/test_transformers.py b/tests/mmm/test_transformers.py
index c1454c324..232711a3f 100644
--- a/tests/mmm/test_transformers.py
+++ b/tests/mmm/test_transformers.py
@@ -18,6 +18,7 @@
 import pytensor.tensor as pt
 import pytest
 import scipy as sp
+from pymc.logprob.utils import ParameterValueError
 from pytensor.tensor.variable import TensorVariable
 
 from pymc_marketing.mmm.transformers import (
@@ -148,6 +149,23 @@ def test_geometric_adstock_good_alpha(self, x, alpha, l_max):
         assert y_np[1] == x[1] + alpha * x[0]
         assert y_np[2] == x[2] + alpha * x[1] + (alpha**2) * x[0]
 
+    @pytest.mark.parametrize(
+        "alpha",
+        [-0.3, -2, 22.5, 2],
+        ids=[
+            "less_than_zero_0",
+            "less_than_zero_1",
+            "greater_than_one_0",
+            "greater_than_one_1",
+        ],
+    )
+    def test_geometric_adstock_bad_alpha(self, alpha):
+        l_max = 10
+        x = np.ones(shape=100)
+        y = geometric_adstock(x=x, alpha=alpha, l_max=l_max)
+        with pytest.raises(ParameterValueError):
+            y.eval()
+
     @pytest.mark.parametrize(
         argnames="mode",
         argvalues=[ConvMode.After, ConvMode.Before, ConvMode.Overlap],