A/B Test Example That Led to 40% Increase in Conversions

Pacific Whale Foundation (pacwhale.com) came to us here at CausalFunnel wanting to improve their online booking process and make it easier for potential customers to make a purchase. As part of their digital optimization strategy, they partnered with CausalFunnel to implement a conversion-focused A/B test example. By running structured experiments, they aimed to uncover small but impactful user interface changes that could drive more bookings.

Problem and Background

The challenge they were facing became clear: pacwhale.com generated significant traffic, too many users dropped off before completing their bookings. Visitors often navigated the calendar availability tool without taking immediate action, leading to a missed opportunity for conversions. The site needed a simple but effective change that would encourage users to take the next step without overcomplicating the user’s journey.

Case Study

Our work here at CausalFunnel began by an analysis of user flow and heatmapsgrowth team analyzed user flow and heatmaps to identify key points of drop-off. We discovered that users were engaging with the calendar but hesitated before committing to the booking. To address this hesitation, our team hypothesized that an additional call-to-action could be the solution by providing the right nudge at the right moment.

The experiment focused on introducing a strategically placed “Book Now” button in a bright orange color, positioned just before the calendar availability. This design choice created visual contrast, caught user attention, and gave customers an easier path to conversion without requiring them to scroll further or navigate extra steps.

How CausalFunnel AI Fixed the Problem

Our proprietary CausalFunnel AI provided the framework to design, launch, and measure this test in a structured way. This is crucial as unbiased, randomized data is needed to properly evaluate A/B tests. Instead of relying on guesswork, our platform leveraged automated setup to create multiple A/B testing examples that compared the existing booking flow with the new variation featuring the orange “Book Now” button.

Test Variant A

Test Variant B

Our CausalFunnel AI is able to continuously monitor performance in real-time, which allows us to detect statistical significance faster than traditional testing methods. By automating test tracking and ensuring accuracy, CausalFunnel AI removed the manual guesswork marketers often face. This accelerated the learning cycle and reduced wasted ad spend by quickly identifying which version was driving better results.

Key Takeaway:  Our platform delivered the data and insights needed to make a change while beyond surface-level metrics. We were able to identify not only the uplift in clicks on the “Book Now” button but also confirmed that the variation led to more completed bookings. This distinction was critical because raw clicks alone don’t always translate to revenue impact, but for pacwhale, they saw a 40% increase in conversions. With this clarity, the pacwhale.com team was confident in rolling out the winning variation across all booking pages.

A/B test results 

Conclusion

This pacwoale.com A/B test case study highlights how even small, targeted changes can yield significant results when backed by structured testing and advanced AI analysis. By introducing a single orange “Book Now” button before calendar availability, Pacific Whale Foundation saw measurable improvements in conversions. This is where they saw a 40% increase in conversions. More importantly, the process validated CausalFunnel AI as a reliable partner for scalable growth, turning a simple A/B test example into a long-term optimization strategy. So stop waiting and get started today.