document: A study on the impact of product images on user clicks for online shopping In this paper we study the importance of image based features on the click-through rate ( CTR ) in the context of a large scale product search engine . Typically product search engines use text based features in their ranking function . We present a novel idea of using image based features , common in the photography literature , in addition to text based features . We used a stochastic gradient boosting based regression model to learn relationships between features and CTR . Our results indicate statistically significant correlations between the image features and CTR . We also see improvements to NDCG and mean standard regression .
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