Study: Visual recommendations enhance online shopping experience

Fashion shoppers' purchases are more likely influenced by browsing social media and the majority of fashion searches are triggered by an existing image or a screenshot, according to a study conducted by ViSenze.

In the latest study "Supercharge your content strategy with visual recommendations", ViSenze suggested several global clients showing that up to 58% of images uploaded by shoppers show a model with a complete look, suggesting a strong desire to buy the complete look rather than a single item. Also, over 70% of fashion searches are triggered by an existing image or a screenshot. Of these, 33% screenshots are from social media platforms such as Instagram, Pinterest, Facebook, and WeChat while another 30% are from online shopping websites.

"The discovery stage is visually led and fairly easy, but the shopper experience usually dips from here on," said Brendan O’Shaughnessy, chief commercial officer of ViSenze.

The study has also revealed the common ways for brands to curate content, including using in-house stylists, partnering with celebrities or influencers to build their own collections and pulling user-generated content from social accounts. However, brands often begin content curation manually and witness positive results early on. But, they get stuck when trying to scale their efforts.

ViSenze suggests leveraging visual search technology to tackle the problem since brands can provide product recommendations that are relevant to their shoppers across the buying journey. By using visual recommendations, brands can convert static curated content into a compelling shoppable experience to stand out among their competitors and build strong brand loyalty and stickiness.

"Through the visual content on the website, brands can create relevant product recommendations based on visual similarities. This allows brands to automate your content at scale, build custom content for every user, and position it across the buying journey”, added O’Shaughnessy.

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