+24 %
Revenue boost
+27 %
Returning users
+7.8 %
Conversion rate
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Snowbitch is an e-shop offering young, street, skate fashion. Its goal was clear - to increase sales!
Revenue boost
Returning users
Conversion rate
News on the homepage was set manually. Customers were often confused by the huge amount of different brands.
We added personal recommendations based on previous behavior, i.e., what the customer browsed, what types of clothes, colors, and brands. CTR increased five times to 16.5 %.
There were no recommendations in categories. Customers had to search, filter, or browse through multiple pages.
We sorted filters according to personal preferences and put them in the first line of product feed. We took into account the preferred color, brand, and what similar visitors are browsing, what the customer had not seen before, labeled products, and special offers. Best‑selling and most‑browsed products are being slightly preferred. Most men don’t see any difference between multiple swimwear, but trust us – picking the right color is not an easy task! CTR increased to 9.8 %.
There were no recommendations on product detail pages, so customers did not get the idea of buying a second, color-matching upper part for the swimwear.
We placed two feeds below product details: one with recently viewed products and the other with recommended products (according to customer preferences) from the same category. The CTR of recommendations increased to 47.1 %, and that of the recently browsed products was 10.2 %.
There were no recommendations in the pre‑checkout.
We added a feed of products related to what the customer put into the shopping cart to the checkout. The relation between these products was set according to what other customers bought together with the main product. CTR in pre‑checkout increased to 5.2 %.