New Normal in Fashion e-Commerce

New Normal in Fashion e-Commerce

Trend Analytics powered by AI and the Bottom-up Consumer Revolution

CONSUMER DRIVEN FASHION TRENDS

Throughout modern history, fashion trends were traditionally based on forecasts and intuition. Fashion editors highlighted what individuals on the street should wear. While designers dictated the look and feel of a range, and buyers and stylists curated an assortment based on future consumer demand — all backed by little or no data. However, fashion today is seeing continuous waves of a revolution led by digitalization and consumer sovereignty.

Through digitalization, consumers today have greater access to the fashion industry than ever before. Hence, they are able to communicate and drive tastes through social media and across geographies, in real-time. This calls for an approach that analyzes demand from a consumer behavior perspective, rather than top-level macro predictions. As the fashion industry becomes more complex and competitive, fashion trend forecasts have not changed even though we now have so much data about consumers. Referring to conventional one-size-fits-the industry trend reports on what to wear and produce next has become obsolete and no longer relevant.

With the growing power of social media and influencers, trends are increasingly established by consumers as opposed to retailers, editors, and forecasters, flipping the control from an industry that pushes products out to its consumers, to an industry where a product is pulled by the consumer. Therefore, understanding ‘actual consumer demand’ is vital for success.

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Check out this week’s most popular influencer images and hashtags associated with “leggings” trending on Instagram and social media at a single glance with OMNIOUS STUDIO.
Check out this week’s most popular influencer images and hashtags associated with “leggings” trending on Instagram and social media at a single glance with OMNIOUS STUDIO.
According to The State of Fashion 2020 Coronavirus Update-It’s Time to Rewire the Fashion Industry, co-published by BoF and McKinsey & Company — evidence from China suggests that consumers there increasingly embraced digital solutions for shopping, entertainment, and communications thanks to the response of brands and retailers who quickly enhanced their digital capabilities by launching or improving innovative new channels. Nike — whose digital sales in the region grew 36 percent in the third quarter ended February 29 — leveraged Taobao Livestream bloggers during the lockdown in China, while local fashion group Peacebird grew retail sales as a result of innovative customer engagement on their WeChat channel, which featured over 100 live broadcasting sessions with influencers and drew over one million consumers.

TREND ANALYTICS DRIVE NEW GROWTH OPPORTUNITIES

Fashion brands are powered with retail and consumer data that is now tracked, collected and managed through AI real-time from their own websites, external sites, and social media. Through AUTOMATED PRODUCT TAGGING AI is able to analyze market performance and fashion trends on a meta-data attribute level basis. Buyers are informed not only on the final products that are selling well but also on specific detailed data attributes such as color, prints, sleeves, necklines, etc.

[Using computer vision technology and automated product tagging — our AI collects and analyzes images from over 30,000 Instagram influencer accounts, 3,000 brands each week.]
[Using computer vision technology and automated product tagging — our AI collects and analyzes images from over 30,000 Instagram influencer accounts, 3,000 brands each week.]

The meta-data, when layered with structured analytics and examined in detail, offers actionable insights to inform decision-making on product development and design and also implement competitive sales and marketing business strategies.

Fashion retailers who fail to recognize the value of getting the right product quickly, are slow to react to the right consumer trends, will lose out in sales and eventually market share. In contrast, the strongest players will quickly scale up and strengthen their digital capabilities- which will allow them to capitalize on future opportunities and protect their businesses from risks.

Predictive analytics incorporates real-time data to provide actional insights on current product performance, supporting informed decision making for your fashion business. AI optimizes consumer trend analytics to chase bestseller re-ordering and leverage current demand momentum while reducing the influence of intuition bias in business decisions- hence lowering the risk of overstocking while maximizing profit. Predictive analytics powered by AI unlocks the possibility of launching a dynamic just-in-time production system, and timely go to market strategic planning within your fingertips.

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GAIN CONSUMER DRIVEN FASHION TREND ANALYTICS WITH OMNIOUS STUDIO TODAY!

Turn consumer data into an actionable business strategy. OMNIOUS STUDIO works on an intuitive user interface easy to filter through and search catalog analytics in a single view.

Using its industry-leading patented deep learning computer vision technology, our AI-powered trend analytics solution enables processes that significantly influence fashion design and buying, with insights on the specific style, silhouette, and color direction with an average 95% accuracy [Client’s review results].

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About OMNIOUS blog

OMNIOUS, an AI startup, was founded in 2015 by the co-founders researching deep learning algorithms at KAIST. AI and fashion experts work together to transform fashion data to work. Our mission is to accelerate the digital transformation in fashion, and provide AI and data that companies need in their business.

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