On large-scale e-commerce platforms with tens of millions of active monthly users, recommending visually similar products is essential for enabling users to efficiently discover items that align with their preferences. This study presents the application of a vision-language model (VLM) -- which has demonstrated strong performance in image recognition and image-text retrieval tasks -- to product recommendations on Mercari, a major consumer-to-consumer marketplace used by more than 20 million monthly users in Japan. Specifically, we fine-tuned SigLIP, a VLM employing a sigmoid-based contrastive loss, using one million product image-title pairs from Mercari collected over a three-month period, and developed an image encoder for generating item embeddings used in the recommendation system. Our evaluation comprised an offline analysis of historical interaction logs and an online A/B test in a production environment. In offline analysis, the model achieved a 9.1% improvement in nDCG@5 compared with the baseline. In the online A/B test, the click-through rate improved by 50% whereas the conversion rate improved by 14% compared with the existing model. These results demonstrate the effectiveness of VLM-based encoders for e-commerce product recommendations and provide practical insights into the development of visual similarity-based recommendation systems.

Next week, Adobe is rolling out'visual similarity recommendations' which offer AI-powered product suggestions based on what consumers are considering purchasing. And this on-the-fly use of visual interpretation and recommendation is just the start. Now that more people are shopping online during the pandemic, brands need to facilitate the myriad ways people hunt, browse and discover products. But it's not so easy to do that if a shopper doesn't quite know what she wants until she sees it. Enter AI and visual similarity.

There is not a single industry where artificial intelligence hasn't created a new trail. And customer experience, which is established to be a key differentiator and even an inducement for customers to pay a premium price, is no different. In 2020, and beyond too, AI is going to have a prominent influence on customer experience -- an influence that will enable businesses to deliver better customer experience without having to tear down their workflows and build new ones from scratch. For example, chatbots that have been considered a fancy addition will come to the forefront as a must-have or table stakes for businesses. There are several other trends like these that are in the offering. Let's take a quick look at them.