Personalisation is one of the hottest topics at the moment. Many brands and fashion start-ups are using it to enhance the customer experience. However, personalisation tools are lacking when it comes to clothing and textiles, leaving a huge gap in the market for a pioneering new clothing brand where styling is creative, simple and completely personalised.
Fashion retail is worth US$1.5 trillion per year worldwide, with US$12.8 billion spent in Australia. While the value of having an online presence is generally understood, there is a growing demand for more personalised offerings based on data analytics. This gives fashion brands and start-ups a new value-added service for their clients, with the potential to boost digital channel sales.
There are three core trends driving the growth of the styling market:
Customer experience lacking innovation despite the huge growth of Ecommerce
While many retailers and fashion brands have already relocated their operations online, because customers prefer convenience and ease to the time-consuming experience of shopping in stores, the user experience frequently lacks innovation and fails to significantly improve the shopping experience. Customers must still navigate various websites, browse large quantities of merchandise, and return multiple items to multiple stores if they aren't what they expected.
In fashion retail, there is missing potential to save clients time and inconvenience while providing personalisation at scale.
E-commerce penetration in Australia is still increasing, accounting for roughly 10% of total retail, compared to 20-30% in the United States, Germany, and the United Kingdom.
Increased use of data in the fashion industry
Knowledge and insights can be extracted from structured and unstructured data through data science using a variety of procedures, algorithms, and systems. Data scientists in the fashion sector look for data that reflects target consumers' interests, behaviours, and potentially predict their future behaviour. This information is used to better understand consumer preferences, improve recommendation quality, and make product discovery easier for customers.
However, data has its restrictions. In reality, the sheer amount of factors involved in each purchase, such as size, body shape, and fit, makes this a challenging task. Furthermore, the ever-changing condition of fashion and consumer tastes means that the data used has to be constantly updated. In the realm of fashion, where numerous personal elements must be taken into account, it is frequently required to integrate a human element. Hybrid models, such as those used by Stitch Fix and Threadicated, take advantage of the consumer insights gained from data algorithms, giving human stylists more time to focus on taste and style.
Increased focus on personalisation in fashion
Personalisation is one of the most common uses of data analytics in the fashion industry.
Fashion has become significantly more intricate and intimidating for consumers than most other retail categories, with its myriad of sizes, collections, and trends. Consumers are similarly picky, wanting their purchases to represent their personalities and display their individuality. On the other hand, the overwhelming array of possibilities offered frequently leads to "analysis paralysis" and missed sales opportunities for fashion brands and start-ups, necessitating a strong need for adaptability.
Recognizing this trend, online fashion brands and start-ups are increasingly customising ecommerce sites for individual customers to reflect their onsite activity or purchasing history and lead them through the buying process. According to research, online merchants aim to boost their personalisation spend by 18 to 30 percent over the next three years. Customers are 80 percent more likely to make a purchase and become high-value customers as a result of these expenditures, according to surveys and transactional data.
Despite the fact that stylists and personal shoppers have been around for decades, there have been few attempts to bring this type of highly personalised service to the digital realm. For most people, style has always been excessively expensive, time-consuming, and difficult to obtain. Digital style through apps and other means has also failed to capture the essence of consumer tastes, resulting in high return rates. This opens the way for new fashion start-ups like Threadicated, which modernises the conventional concept of styling by allowing for granular personalisation in a digital setting.
How Threadicated is using AI to reimagine fashion styling
Threadicated is an on-demand and subscription-based, direct-to consumer personal fashion styling service. The Company markets its services directly to consumers and, increasingly, through online fashion retailing partners as a plug-and-play feature for deep customer personalisation.
At its core, Threadicated is reimagining fashion styling in Australia, to help people find clothes they love. Their innovative model combines the processing power of AI and the expert intuition of human stylists to deliver an affordable, high-quality and scalable service in a medium that is relevant for time-poor digital natives.
Customers request styled parcels that include a 5 item mix of clothing, shoes and accessories - with 60% of parcels delivered via subscription at one, two or three month intervals. Threadicated forms a complete picture of each customer’s style and needs, using the 60+ points of data shared during sign-up. Each parcel is then curated by a stylist, with assistance from Threadicated’s AI according to the customer’s preferences resulting in a selection of clothing, shoes and accessories personalised to each customer’s style, fit, and budget. Upon receiving the parcel the customer shares further feedback with Threadicated on each item. This data loop allows Threadicated to improve over time, adapting key learnings from each customer to enhance the overall experience.
Threadicated does not hold inventory and instead partners with leading brands and retailers. Having direct supplier relationships means Threadicated only purchases products at a reduced RRP after styling a customer, removing the need for large upfront inventory costs and reducing the working capital requirements of the business.
The process of Threadicated's platform to ensure each and every customer gets the perfect fit
Threadicated is launching an equity crowdfunding campaign soon on Equitise. The company intends to use the funds of the campaign to further the development of its AI, introduce new products and globally expand.