ViSenze powers visual commerce at scale for retailers and publishers. The company delivers intelligent image recognition solutions that shorten the path to action as consumers search and discover on the visual web. Retailers like Rakuten and ASOS use ViSenze to convert images into immediate product search opportunities, improving conversion rates. Media companies use ViSenze to turn any image or video into an engagement opportunity, driving more new and incremental dollars. Oliver Tan, co-founder and CEO of ViSenze tells Fibre2Fashion about the organisation's plans and vision.
Why is visual commerce important for online apparel retailers?
Being able to view the object while shopping online is extremely important for shoppers, and visual cues help them experience the product better. According to a recent study by Deloitte, 2.5 trillion images were shared in 2016. Online retailers today understand this trend as well as the limitations of text-based search; hence, visual commerce is becoming essential. Visual commerce can be a platform for multiple things. At the crux of it, visual commerce is a concept that talks about enriching the customer's experience using inspirational, aspirational, and aspiring visual content. This content in turn encourages them to engage with a particular brand or online retailer, thus helping in conversion to sale.
What is the impact of visual commerce on consumers and brands?
From a retailer's perspective, the market is turning increasingly competitive. In the sea of brands, luxury and otherwise, retailers have generally stuck to the traditional medium along with in-store experiences. For consumers, visual commerce brings the capability to easily find products they are inspired to buy, without having to guess keywords. For brands, visual commerce delivers better conversions and brand loyalty, as customers interact and buy more.
Retailers today are becoming publishers, why?
Retailers understand that just having products isn't always enough. They need to have content that inspires and guides customers as well as to strike a chord with them. With the rate at which direct-to-consumer opportunities are rising, retailers have a greater chance at diversifying into e-commerce and other non-traditional areas. This, in turn, helps in widening their brand appeal. That is the reason we get to see more and more retailers investing in publishing information that helps their customers make more informed decisions.
ViSenze has developed "The Dress Challenge" to pit consumers' keyword searching skills to visual search technology. Please explain.
The dress challenge was developed to showcase the pitfalls of text-based search. You will notice that often it's difficult, or impossible, to describe a clothing item in words. One has to be proficient with fashion terminology that includes knowledge of patterns, styles, and tens of other attributes. On the other hand, our visual search technology powered by artificial intelligence can efficiently analyse an image and in turn surface visually similar products.
You have also developed a combined in-video search and recognition which is fully automated, how does it function?
In-video search and recognition work on the concept of image search on videos. Video consumption is on the rise, and often we see products in videos, television shows and movies that we might want to know more about. Through in-video recognition, we can help users identify the products and also surface online stores that have these products available.
Your visual search technology incorporates image search and in-video search. According to you, which method is more effective? Why?
Both methods solve a similar problem and can be equally effective in improving engagement and conversions. Image search can help online retailers improve search results and discoverability whereas video search can help publishers convert their existing videos into monetisable assets.
What percentage of your revenue is invested in R&D?
As an artificial intelligence company focused on computer vision and machine learning, the majority of the funding we have raised has gone towards improving our breakthrough technology and R&D activities. Over 75 per cent of our team comprises R&D personnel, scientists, solution engineers. We will continue to double down on our R&D and core deep learning technology as our competitive advantage.
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