diff --git a/tests/kpis_global_metrics_outlier_detection.sql b/tests/kpis_global_metrics_outlier_detection.sql
index ce80f8d..0ac47c1 100644
--- a/tests/kpis_global_metrics_outlier_detection.sql
+++ b/tests/kpis_global_metrics_outlier_detection.sql
@@ -8,7 +8,6 @@ There's chances that false positives are risen by these test. If at some
 point it becomes too sensitive, just adapt the following parameters.
 
 */
-
 -- Add here additive metrics that you would like to check
 -- Recommended to exclude metrics that represent new products,
 -- since there will be no history to check against. 
@@ -16,12 +15,7 @@ point it becomes too sensitive, just adapt the following parameters.
 {% set metric_names = (
     "Cancelled Bookings",
     "Checkout Bookings",
-    "Churning Deals",
-    "Churning Listings",
     "Created Bookings",
-    "Deals Booked in 12 Months",
-    "Deals Booked in 6 Months",
-    "Deals Booked in Month",
     "Deposit Fees",
     "Est. Billable Bookings",
     "First Time Booked Deals",
@@ -41,9 +35,6 @@ point it becomes too sensitive, just adapt the following parameters.
     "Invoiced Listing Fees",
     "Invoiced Operator Revenue",
     "Invoiced Verification Fees",
-    "Listings Booked in 12 Months",
-    "Listings Booked in 6 Months",
-    "Listings Booked in Month",
     "New Deals",
     "New Listings",
     "Total Revenue",
@@ -62,7 +53,7 @@ point it becomes too sensitive, just adapt the following parameters.
 -- thus it will be more tolerant.
 -- A lower value means that the chances of detecting outliers 
 -- and false positives will be higher. Recommended around 10.
-{% set detector_tolerance = 10 %}
+{% set detector_tolerance = 8 %}
 
 -- Specify here the number of days in the past that will be used
 -- to compare against. Keep in mind that we only keep the daily