Increasing conversion rates is always a priority for ecommerce brands aiming to grow without increasing acquisition costs. Even when traffic is strong, small friction points on product pages; such as slow loading times, confusing navigation, or unclear product details can prevent visitors from taking action. One proven way to address this is through focused A/B testing as part of broader landing page optimization, where individual elements are tested to understand how users actually behave.

In this case study, we share how Rockwell Razors improved engagement on a key product page by adjusting the placement of their Add to Cart button, resulting in a measurable lift in click performance.

Background & Problem

Rockwell Razors is a premium grooming brand known for its high quality safety razors. The Rockwell 6S is one of their flagship products and attracts a steady volume of traffic from users with clear purchase intent.

Despite this, the product page was underperforming when it came to Add to Cart clicks. Visitors were viewing the page, selecting options, and scrolling through details, but many were not interacting with the primary CTA.

The issue was traced back to layout and visual hierarchy. The Add to Cart button appeared lower within the product information section, competing with upgrade offers, add ons, and supporting details. As a result, the CTA did not stand out immediately, particularly for desktop users scanning the page quickly.

Although the page followed common ecommerce best practices, Rockwell Razors needed data to confirm whether a small layout change could improve engagement.

Case Study

To solve this, the CausalFunnel team designed a controlled A/B test focused on a single variable: button placement.

Two versions of the Rockwell 6S product page were tested:

• Control: Original Add to Cart button position

• Variant: Add to Cart button moved higher within the product details section

No other changes were introduced; pricing, copy, imagery, reviews, and product options all remained identical. This ensured that the test isolated a single variable at a time, rather than introducing multiple changes simultaneously. By splitting traffic evenly between the two versions, we could accurately track the impact of the specific adjustment without confounding factors.

The test ran for eight days and collected data across more than 1,300 total views.

A/B Test Results

The results showed a clear improvement in user engagement for the variant with the higher button placement.

• Overall click rate: 10.61 percent
  This represented a 9.7 percent improvement over the control.

   

• Desktop performance:
  Control click rate: 10.83 percent
  Variant click rate: 15.04 percent
  Resulting in a 38.9 percent increase in desktop clicks.

   

Mobile performance:
Click behavior remained stable, confirming that the change did not negatively impact mobile users.

These results validated that visibility and visual priority of the CTA played a direct role in influencing user action.

How CausalFunnel AI Fixed the Problem

CausalFunnel AI was used to set up, run, and monitor the A/B test from start to finish. As one of the conversion rate optimization tools used in this experiment, the platform enabled the team to isolate a single element test and track performance with clarity.

Using the CausalFunnel dashboard, the team monitored:

• Button click activity

   

• Session level engagement

   

• Device specific performance trends

   

The A/B test dashboard made it easy to compare control and variant results in real time and clearly attribute performance improvements to the button placement change. Device level insights revealed that desktop users benefited most, providing guidance for future layout decisions across other product pages.

Key Takeaway

This test highlighted the impact small layout changes can have when user intent is already high. Improving clarity and reducing friction at the moment of action can drive meaningful gains without redesigning the page.

CausalFunnel AI allows teams to test these changes quickly, measure results accurately, and implement improvements with confidence.

Conclusion

By repositioning the Add to Cart button on the Rockwell 6S product page, Rockwell Razors achieved a higher overall click rate and a significant uplift in desktop engagement.

This case study shows how structured A/B testing, guided by real user behavior data and powered real user behavior data with support from CausalFunnel AI, helps ecommerce brands validate changes that directly improve performance.