E-Commerce Case Study
NEOH
How NEOH introduced A/B testing for the first time using AI and achieved a +25.74% revenue uplift in 7 days.
How NEOH introduced A/B testing for the first time using AI and achieved a +25.74% revenue uplift in 7 days.
Many companies want to run tests but struggle to get started. Ideas for their website and optimization potential already exist. However, due to competing priorities and the high pace of day-to-day business, structured A/B testing often remains a strategically important topic held back by time and resources.
This was also the case at NEOH. As an e-commerce brand focused on reduced-sugar alternatives to traditional sweets and snacks, NEOH has experienced rapid growth. But this fast development led to a prioritization challenge: despite being aware of the importance of testing and validating website content, there was no structured testing process in place before using pagent.
In e-commerce, the website directly determines revenue. Every visit is a potential conversion, and small differences in communication can have measurable effects. Teams that optimize systematically gain a better understanding of which content builds trust, simplifies purchase decisions, and ultimately drives conversions.
Florian Springer“Pagent has enabled us to introduce data-driven decision-making despite limited resources. Extremely helpful for us. Especially when decisions aren’t clear, we now have transparency and a validated basis for decision-making thanks to the test data.”
That is exactly why A/B testing became a crucial next step for NEOH in improving customer communication. With pagent, the team found a solution that allows them to implement tests easily.
Instead of developing new campaigns or designs, NEOH uses pagent to optimize directly within its existing communication. NEOH defined a clear strategic direction: focusing on taste and satisfaction, with the goal of reducing skepticism toward “better-for-you” snacks.
Pagent automatically analyzes user data and derives new variants for headlines and product categories. Without complex manual setup, NEOH achieves data-driven messaging optimization for the right communication within its product world. The focus shifted from brand promises to purchase reassurance.
Florian Springer“The time required for a test is very low. We let pagent analyze the page with planned changes and sometimes even surprising optimization suggestions, and within the next week we have clarity while we can focus on our core tasks in the meantime.”
The hypothesis and content changes for the first A/B test variant came from the NEOH team. Without a lengthy concept phase or additional operational complexity, the test could begin: implementation, execution, and evaluation of the results were handled directly through pagent.
After just 7 days, a clear effect became visible: the optimized variant achieved a performance increase of +16.81% and a measurable revenue uplift of +25.74%.
Florian Springer“We were surprised by how much of a difference small changes in wording can make.”
For NEOH, this marked the beginning of a new workflow. A/B testing evolved from a resource-intensive special project into a realistically executable process. This is exactly where AI-powered optimization provides real leverage for many smaller companies: not only by generating relevant variants faster, but by removing the internal barriers to getting started with testing in the first place.
With the right tools, A/B testing becomes accessible. Tests are faster to implement, workflows become more efficient, and results are backed by meaningful analyses based on real user behavior.