Bracketing in fashion retail, a phenomenon significantly amplified by TikTok and influencer marketing, has become a prominent trend in e-commerce. Initially driven by content creators for showcasing a variety of outfits and styles, this practice has taken on enormous proportions, influencing consumer behavior on a large scale.
While the glitz of social media and influencer marketing captures our attention, it's crucial to recognize that this is just a fraction of the broader issue. Beyond the influencers and content creation, bracketing originated from brands' inefficiency in producing pieces that fit well and in effectively communicating their sizing, and has evolved into a common practice among everyday consumers, leading to a multitude of challenges for retailers.
Bracketing, where consumers buy multiple sizes or variations of an item to return what doesn't fit, has surged, partly due to social media influence. This trend not only highlights the demand for a perfect fit but also exacerbates return rates, posing challenges for retailers. It underscores the need for improved sizing accuracy and better communication around product fit to mitigate unnecessary returns.
The main issues with bracketing are multifaceted:
While some suggest charging for returns or reducing shipping costs as solutions, these approaches only scratch the surface. The real issue lies deeper: the challenge of ensuring a proper fit. Traditional methods like sizing charts are often ineffective as they don't account for the unique fit of each garment and the variance in sizing across brands. Customers, uncertain of their size, resort to bracketing as a safety net.
Enter SAIZ, our AI-powered technology that is transforming how brands address the fit problem. SAIZ stands at the forefront of this change, boasting the largest fashion data warehouse on human measurements, product dimensions, and client success stories.
SAIZ's groundbreaking approach allows for the prediction of product fit before the items are even made. By analyzing cross-brand, multilateral data, SAIZ offers insights into product improvements and operational strategies for targeted sales.
With minimal input from users, SAIZ AI accurately determines the likely body shape, utilizing over 2 million data points to achieve an estimated accuracy level of 95%. This precise size guidance for each product enables brands to tailor their offerings to specific target groups and preferences.
Our clients have witnessed remarkable results with SAIZ, reducing returns by up to 7%. A testament to its effectiveness comes from the Head of E-commerce from one of our clients: "We have compared almost all sizing solutions, SAIZ stood out from the beginning due to the recommender usability but also the approach to come from the product-side."
In conclusion, the challenge of bracketing in fashion retail requires a solution that addresses the root cause – the fit of the clothes. By leveraging advanced technologies like SAIZ, brands can not only enhance customer satisfaction but also contribute to a more sustainable and efficient retail environment. The future of fashion e-commerce lies in understanding and adapting to customer needs, and SAIZ is leading the way in this transformative journey.
