Optimizing Conversion Rates with A/B tests @ KarHub

Learn how we transformed KarHub’s e-commerce platform by implementing a robust A/B testing culture, leading to significant increases in conversion rates and user engagement across the site.

After launching KarHub's initial e-commerce MVP, our team shifted focus to optimize conversion rates using data-driven strategies. We realized that following established e-commerce best practices wasn't enough to achieve our ambitious goals. By fostering a strong A/B testing culture and iterating quickly, we made continuous improvements that resulted in significant performance gains.

We conducted an A/B test comparing our traditional search functionality with a new AI-powered search. Despite concerns about a slightly longer response time, the AI search significantly boosted overall conversion rates by 80% and mobile conversion rates by 30%. This showed that more accurate search results were valued over speed. A conclusion made possible by testing only, as slower performance is generally unadvised.

Another A/B test focused on moving the product image gallery below the fold on mobile product pages to prioritize technical information. This change led to a 39% increase in product page to checkout, validating our hypothesis that technical details were more crucial for our niche market.

In a recent A/B test, we evaluated the impact of an on-pagevehicle filter versus the traditional Modal filter on catalog pages. With over 2,600 participants, the open filter proved to be 1.6x more likely to be used and resulted in a significant conversion boost, with 4% of users reaching checkout compared to 2.74% in the control group. The results were statistically significant, with over 99% certainty that the open filter outperforms the old version.

We aimed to systematically increase conversion rates across all touchpoints on the site. By leveraging data and continuous testing, we wanted to understand what truly resonated with our users and drove them to complete purchases.

Establishing a testing culture was crucial. We adopted a kanban model to explore various hypotheses and potential changes weekly, ensuring a steady flow of experiments and optimizations.

Our goal was to create an intuitive and seamless shopping experience. This meant refining elements on the homepage, search results, category pages, filters, shopping cart, and product pages based on user feedback and testing outcomes.

By building a strong A/B testing culture and making data-driven decisions, we significantly improved KarHub’s e-commerce platform. This approach not only increased our conversion rates and overall revenue but also ensured that our site evolved to meet user needs effectively. As a result, KarHub has seen a steady monthly increase in GMV since the beginning of 2024, demonstrating the power of continuous optimization and user-focused design.