diff --git a/_case_studies/11_improving_business_metrics_for_maximum_impact.md b/_case_studies/11_improving_business_metrics_for_better_impact.md
similarity index 85%
rename from _case_studies/11_improving_business_metrics_for_maximum_impact.md
rename to _case_studies/11_improving_business_metrics_for_better_impact.md
index e60bd98..af304db 100644
--- a/_case_studies/11_improving_business_metrics_for_maximum_impact.md
+++ b/_case_studies/11_improving_business_metrics_for_better_impact.md
@@ -1,11 +1,11 @@
 ---
-title: Improving business metrics for maximum impact using the CausalTune library
+title: Improving business metrics for better impact using the CausalTune library
 layout: page
 description: >-
   This tutorial provides an introduction to improving business metrics using the ERUPT metric and the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric for optimizing clickthrough rates.
 summary: >-
   This tutorial provides an introduction to improving business metrics using the ERUPT metric and the CausalTune library in Python. It shows a practical example and the use of the ERUPT metric for optimizing clickthrough rates. It also shows how to use ERUPT to evaluate previous experiments, as well as how to evaluate the potential effect of a future experiment with different assignments using a real business example. 
 image: assets/causaltune-targeting.png
-image-alt: Improving business metrics for maximum impact
+image-alt: Improving business metrics for better impact
 link: https://towardsdatascience.com/targeting-variants-for-maximum-impact-bdf26213d7bc
 ---