How AliExpress Boosted Organic Traffic Conversions with SplitMetrics Optimize

AliExpress is a leading online marketplace, offering millions of products worldwide across diverse categories at competitive prices. 

Challenge

As a global e-commerce leader, AliExpress depends on strong app store performance to deliver a great user experience. To achieve this and make data-driven improvements, the team relies on A/B testing.

However, A/B testing tools on Google Play and the Apple App Store come with limitations that slow down progress and make decision-making harder. Key challenges include:

• Simulating Real Natural Traffic Sources
  It is difficult to replicate authentic user behavior in testing environments. This makes it challenging to assess how changes in materials and copy will perform under real-world conditions.
• Slow Feedback and Uncertain Data Confidence
  The backend processing for Conversion Rate Optimization (CSL and CPP) on Google Play and the App Store takes 7–14 days. During this time, there is no clarity on the data’s confidence level.
• Predicting Traffic for Major Promotional Seasons
  Accurate traffic predictions for promotional campaigns are critical but difficult without A/B testing data. While historical data and competitor metadata offer some insights, they are insufficient to assess the broader impact of brand updates.
• Adjusting Materials and Copywriting Before Traffic Impact
  With fluctuating traffic structures during promotional seasons, validating the effectiveness of new materials and copy in advance is a major challenge. Without reliable preliminary validation, it’s hard to ensure natural traffic will not be negatively affected.

For AliExpress, these bottlenecks highlighted the need for a more efficient testing solution to drive better results during critical periods.

Solution

AliExpress shifted its focus to leveraging organic traffic on its mobile website (Msite) to address the high cost of paid traffic and its differences from organic traffic. The Msite includes features like a Smartbanner and hotspot areas in discount channels to encourage app downloads. Visitors who browse or purchase on the site often install the app for a better shopping experience, making organic traffic an ideal test pool for ASO.

To maximize this traffic, internal download links were upgraded with multidimensional redirect capabilities. These updates allowed specific traffic segments to be directed to SplitMetrics Optimize experiments based on the following conditions:

• IP country 
• Device type 
• User tags 
• Operating system.

By running small-scale A/B tests, AliExpress was able to generate reliable results within days and finalize optimized app store pages for launch.

Examples

This use case showcases AliExpress’s approach to testing visuals for high seasons like 11.11, Black Friday, and Christmas. The focus was on testing multiple seasonal variations tailored to each event. 

Double 11 (Global Shopping Festival)
Double 11 is AliExpress’s largest annual promotion. For this event, tailored A/B testing strategies were developed for different countries and regions, focusing on optimizing the campaign’s key visuals. 

Test results offered clear guidance for display strategies, such as how information was highlighted. Variation B outperformed the other designs, achieving a 13.6% improvement in conversion rates. 

Black Friday
For Black Friday, the AliExpress tested various visual elements, including the primary color, background color, screenshot sequence, and text display methods. 

The results identified the most effective design, which significantly boosted the conversion rate. Different concepts resonated with users in different regions, achieving improvements of up to 14% in conversion rates. This highlights the importance of tailoring designs to regional preferences for maximum impact.

Christmas and New Year
During the holiday season, a gift theme was incorporated into the in-app screenshot designs. However, different regions had unique perceptions of gift-related colors and designs. Based on these insights, the team developed multiple hypotheses and experimental designs. 

Each set of experiments used a controlled variable approach, adjusting product selection, screenshot order, and interest points to align with user preferences. Both variations achieved significant improvements, with Variation B delivering the highest performance:

• Variation A: 12.1% Improvement
• Variation B: 32.5% Improvement

Additionally, similar concepts tested in other storefronts demonstrated improvements of up to 24%.

Results 

With SplitMetrics Optimize, AliExpress achieved major success in app store optimization during key promotions and daily operations:

• Record Downloads During Double Eleven and Black Friday
  • The app achieved its highest-ever download numbers.
  • It topped the charts in key markets like Germany and the UK on both the Apple App Store and Google Play Store.
• Improved Performance in Emerging Markets
  • Rapid A/B testing in markets like Mexico and Brazil led to a more than twofold increase in organic traffic conversion rates compared to the app’s initial launch.
• Enhanced Daily Optimization
  • Testing the order of benefit point screenshots provided insights that improved app store operations.
  • These tests also guided feedback optimization for newly launched benefits tailored to different countries.

These results highlight the effectiveness of A/B testing in driving app performance and enhancing user engagement across global markets.