Returns are an inevitable aspect of the e-commerce landscape, but they don't have to be a headache for online retailers. With the right tools and strategies, businesses can streamline the returns process and minimize associated costs. One tool gaining traction in the industry is Kiwi Sizing's size recommender feature.
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Product returns pose several challenges for online retailers. They not only result in lost revenue and higher operational costs, but also affect customer satisfaction and loyalty. One of the primary reasons for returns is sizing issues. When customers receive items that don't fit as expected, they're more likely to return them, creating additional expenses for the retailer.

Kiwi sizing, a leading provider of e-commerce solutions, offers a comprehensive size recommender feature designed to address the sizing challenge head-on. By leveraging advanced algorithms and machine learning technology, Kiwi's size recommender helps customers find the perfect fit for their body type and preferences.

The size recommender analyzes various factors, including body measurements, previous purchase history, and customer feedback. Using this data, the algorithm generates personalized size recommendations for each shopper, increasing the likelihood of satisfaction with their purchases.
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From the chart that you created. Click Start setting up recommender, then you will see 3 options for the recommender to use.

1. Advanced Apparel Recommender: The user enters basic information (i.e. age, weight, height) and we estimate the user's body size which is then used to make apparel size recommendations.

2. Basic Table Apparel Recommender: Users input different body measurements, and the app makes the best size recommendation based on that.

3. Custom Recommender: A programmable recommender where you can design the entire recommendation logic. Examples of products that are suitable for custom recommenders include bras.