diff --git a/products/tests.py b/products/tests.py
index d0f979b..7d1c462 100644
--- a/products/tests.py
+++ b/products/tests.py
@@ -780,9 +780,9 @@ class ProductSearchTest(TestCase):
 
     def test_anon_user_can_filter_by_category(self):
         expected_instances = [
-            self.factory(tags="lunares/rojos", category='ropa/nueva', description="zapatos verdes", discount=None),
-            self.factory(tags="lunares/rojos", category="ropa/nueva", discount=0.00),
-            self.factory(attributes='"zapatos de campo", tono/rojo', category="ropa/nueva", discount=9.00),
+            self.factory(tags="lunares/rojos", category='nueva', description="zapatos verdes", discount=None),
+            self.factory(tags="lunares/rojos", category="ropa", discount=0.00),
+            self.factory(attributes='"zapatos de campo", tono/rojo', category="ropa", discount=9.00),
         ]
         unexpected_instances = [
             self.factory(description="chanclas", tags='rojos'),
@@ -790,7 +790,7 @@ class ProductSearchTest(TestCase):
         ]
 
         q = quote("zapatos rojos")
-        url = f"{self.endpoint}?q={q}&category=ropa/nueva"
+        url = f"{self.endpoint}?q={q}&category=ropa&category=nueva"
         # send in request
         response = self.client.get(url)
         # check response
diff --git a/products/utils.py b/products/utils.py
index 1d53c49..eba2d0b 100644
--- a/products/utils.py
+++ b/products/utils.py
@@ -124,7 +124,7 @@ def get_related_products(product):
     return total_results[:10]
 
 
-def ranked_product_search(keyword, shipping_cost=None, discount=None, category=None, tags=None, price_min=None,price_max=None):
+def ranked_product_search(keyword, shipping_cost=None, discount=None, categories=None, tags=None, price_min=None,price_max=None):
     """
     Ranked product search
 
@@ -135,7 +135,7 @@ def ranked_product_search(keyword, shipping_cost=None, discount=None, category=N
     allow filtering by:
     - shipping cost
     """
-    vector = SearchVector('name') + SearchVector('description') + SearchVector('tags__label') + SearchVector('attributes__label') + SearchVector('category__label') + SearchVector('company__company_name')
+    vector = SearchVector('name') + SearchVector('description') + SearchVector('tags__label') + SearchVector('attributes__label') + SearchVector('category__name') + SearchVector('company__company_name')
     query = SearchQuery(keyword)
 
     products_qs = Product.objects.annotate(
@@ -143,8 +143,8 @@ def ranked_product_search(keyword, shipping_cost=None, discount=None, category=N
     ).filter(rank__gt=0.05, active=True)
 
     # filter by category
-    if category is not None:
-        products_qs = products_qs.filter(category__name__in=category)
+    if categories is not None:
+        products_qs = products_qs.filter(category__name__in=categories)
 
     # filter by tags
     if tags is not None:
diff --git a/products/views.py b/products/views.py
index 13e90ad..75776be 100644
--- a/products/views.py
+++ b/products/views.py
@@ -162,7 +162,7 @@ def product_search(request):
         else:
                 discount = None
     # category = request.GET.get('category', None)
-    category = request.query_params.getlist('category[]') or None
+    categories = request.query_params.getlist('category') or None
     tags = request.GET.get('tags', None)
     price_min = request.GET.get('price_min', None)
     price_max = request.GET.get('price_max', None)
@@ -185,8 +185,8 @@ def product_search(request):
             products_qs = Product.objects.filter(active=True)
             if tags:
                 products_qs = Product.objects.filter(tags=tags)
-            if category:
-                products_qs = Product.objects.filter(category__name__in=category)
+            if categories:
+                products_qs = Product.objects.filter(category__name__in=categories)
             # serialize and list data
             serializer = ProductSerializer(products_qs, many=True)
             result_list = [dict(i) for i in serializer.data]
@@ -194,7 +194,7 @@ def product_search(request):
             # split query string into single words
             chunks = q.split(' ')
             for chunk in chunks:
-                product_set, min_price, max_price  = ranked_product_search(chunk, shipping_cost, discount, category, tags, price_min, price_max)
+                product_set, min_price, max_price  = ranked_product_search(chunk, shipping_cost, discount, categories, tags, price_min, price_max)
                 # update price values
                 if product_set:
                     if prices['min'] is None or min_price['price__min'] < prices['min']: