As a Danish fast fashion brand that entered the Chinese market in 1996, ONLY once became a wardrobe staple for a generation of young people through its proactive online and offline strategies. However, with the rise of Generation Z consumers, the speed of fast fashion clothing turnover has accelerated, leading to more brand choices for consumers.
Represented by ONLY, the over 20-year-old established fast fashion women's clothing brand inevitably faces issues of brand aging and declining market share.
Image source: ONLY official blog
Against this background, ONLY decided to take the initiative to seek change and actively embrace new strategies for fast fashion brands.In 2021, we collaborated closely with Zhi Yi Technology to reshape brand competitiveness through a data-driven selection strategy.This article will analyze how ONLY utilizes big data to empower and reconstruct a new product selection methodology.
Trend positioning
Data-driven market trend capturing
Established clothing brands have a significant "inertia" in their selection process — they used to heavily rely on designers' experiences and online and offline store feedback to choose products, but this model has a long cycle and poor stability, which has gradually become ineffective in the fast-paced e-commerce era.
In the rhythm of major emerging internet celebrity fast fashion brands releasing 100 new items every month, the first step for brands that do not want to fall behind is to keep up with or even exceed their pace of new releases, showcasing the advantages of an 'established powerhouse' in product development capabilities.
But how can we quickly, accurately, and decisively develop new products to cater to the ever-changing demands of the younger generation of consumers?
ZhiYi provides ONLY with a 'fast track' to quickly surpass its competitors through the aggregation and insights of global fashion data.
First, with the help of"Category Insights" feature of "Industry Insights", Zhi Yi provided ONLY with the distribution data of new women's clothing products over the target period in recent years (for example, the historical Q3 quarters). By referencing the distribution of new product categories from the same period in previous years, it helps the product planning department make a preliminary plan for allocating new product categories.
Zhi Yi - Women's Clothing Category Insights - Distribution of New Product Releases
In addition, it can also be represented by e-commerce and Douyin.Analysis of popular terms and search keywords on social media platforms to dynamically grasp the real-time demands of consumers on e-commerce platforms.For example, in the third quarter of 2024, Zhiyi captured the decline of the "dopamine dressing" trend and the surge in search volume for the keyword "quiet luxury." ONLY can use this as a key reference for the color design of its 2025 spring/summer new products, adjusting the theme for 2025 spring/summer to accurately grasp the latest market trends.
Douyi - Analysis of Hot Terms in Women's Clothing Category
In addition to data insights, Zhi Yi also provides professional market trend interpretation reports, offering more specialized and intuitive trend analyses and forecasts based on big data in the fashion industry.
ONLY's explosive product methodology is fundamentally based on macro insights and data research on the consumer market.
Detailed design
Closed-loop optimization from data to product
A macro understanding of the category market is just the starting point for a blockbuster. To grasp the 'discerning hearts' of young consumers, one must start from every detail of clothing design, identifying the true preferences and needs of consumers.
However, for ONLY, to more accurately meet the dynamic consumer demand, it is essential to develop more SKUs, which tests both supply chain capability and the accuracy and hit rate of product selection, otherwise it may lead to the risk of inventory buildup.
However, in the face of such problems, ONLY can also leverage big data in clothing to create a new model for precise research and development.
For example, in terms of fabric selection for women's tops in summer, using the comment analysis module of Zhiyi, we conducted a comprehensive analysis of the top 100 products in similar categories and found that 'breathability' and 'wrinkle resistance' are high-frequency keywords in 1-2 star negative reviews.
In response to negative feedback on popular products, brands can quickly gain inspiration and ideas for redesign, adjust the proportion of polyester, and incorporate cool-feeling Tencel cotton blended fabrics, thereby gaining consumer approval.
Know Your Clothes - Consumer Feedback - Women's T-shirt Negative Sentiment Volume Statistics
Similarly,Through the 'Attribute Insights' feature, brands can define target subcategories.For example, for women's T-shirts, select items from the best-selling list and conduct separate research on attributes such as sleeve length, neckline, fit, patterns, and fabric. This will help understand which design elements or workmanship in similar best-selling products are more popular in the market and align with public aesthetics.
Know Clothes - Attribute Insights - Analysis of Sleeve Types for Top 500 Best-Selling Women's T-Shirts
For example, in the winter of 2024, Zhiyi Big Data found that the popularity of puff sleeves in women's spring and autumn tops continued to decline, while the proportion of "bat sleeves" and "raglan sleeves" increased. Brands can promptly adjust their designs based on this insight and launch multiple bat sleeve products. Zhiyi Technology observed that ONLY, with just its Tmall flagship store, produced several bat sleeve items with sales exceeding 1000 units.
Zhi Yi - ONLY new batwing sleeve top
Using apparel big data as the basis for launching new styles and consumer feedback as the idea for making adjustments, this new product launch logic, which is driven by consumer demand, helps ONLY to more quickly and accurately capture the hearts of young consumers.
Social Media Insights
Old brands accurately capture new customer groups.
Once the main stronghold in shelf e-commerce, ONLY has actively laid out its plans for content e-commerce platforms represented by Douyin in recent years, following the shift of young consumers' shopping grounds.By utilizing the DouYi product under ZhiYi, brands can quickly build a "heat-conversion" model for content e-commerce platforms.。
In addition to its own e-commerce section, the content section of the Douyin platform provides crucial directional references for brands in selecting and launching products. By using the filtering function in the Douyi work library, brands can filter and combine videos based on influencer characteristics, work features, product design style elements, fans' characteristics, and other criteria to identify trending and highly rated videos related to their business category. This helps brands understand recent influencer styling and audience feedback in that category and capture social media trends.
Douyi - Women's Clothing Portfolio - Brand Hot Recommended Works
In the fall of 2024, ONLY captured the rapid growth in readership around the 'old money style' topic and the number of best-selling products, quickly partnering with influencers to launch 'affordable old money style' dressing tutorials. The video garnered over 20 million views, leading to a month-on-month increase of 65% in sales of related products.
In addition,Through the 'Smart Image Search' feature, users can also conduct a comprehensive search for similar styles of clothing and products featured in short videos, analyzing the popular design elements of these items.。
Douyi - Intelligent Image Search
Amid the wave of digitalization, ONLY has not blindly chased after traffic but instead used 'Know Your Clothing' big data as a compass, finding a balance between adhering to brand philosophy and innovating new products.
This strategy of 'slow within fast' may become a new paradigm for the apparel industry to cope with uncertainty. Nowadays, with the maturity of technologies such as AI-generated design, the methodology for selecting products by clothing brands continues to iterate, but the core logic remains unchanged: measuring every inch of consumer demand with data as a ruler.
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