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The world of retail has become increasingly digitalized and fast-paced. With digitally native generations such as millennials and Gen Z making up a majority of buying power (Gen Z alone constitutes 40% of global consumers [1]), it’s no wonder brands are tirelessly looking for ways to keep up.
These digitally native shoppers value speed and prefer to discover new items to buy on social media — specifically in the form of short videos [1]. As such, TikTok has become the go-to social media platform for all content and trends. Considering the platform has over one billion monthly active users, visibility is sky-high, causing trends to go viral quickly and frequently.
The aesthetic-obsessed platform has encouraged romanticizing characteristics and categorizing styles, resulting in an endless cycle of new “cores” that retailers have to sift through to determine what will stick.
Through social media and hyper-personalized and trend-forward consumer expectations, trends have also become consumer-established rather than solely dictated by designers on the runway. This means the trend lifecycle is based on preference, making demand forecasting difficult.
To understand what is going to trend on social media and for these buyers, a nod from the runway is one indication of trend relevance. Retailers have to monitor if any elements of the trend are featured in the spotlight, where leading designers, press, media, and fashion enthusiasts may draw inspiration.
Buyers and merchandisers must also access real-time and historical data to consider a product’s promotional adaptability before investing. For example, can the product be reframed into an alternative narrative if interest levels off?
Amongst all this noise of new trend after trend, how can retailers keep up?
Retail technology is more than a productivity-enhancing solution. It allows nearly every aspect of the organization to become more efficient. With connected retail data analytics that are market-informed, profit-aware, and customer-centric, brands become more relevant to their customers, reduce costs and resources, and boost customer experiences.
While businesses operate under harsh economic conditions and strive to keep up with the accelerated pace of fashion, there isn’t room for mistakes in trend identification when assortment planning. Investing in a viral trend, only to have excessive inventory pile up and face excruciating markdowns, would be dangerous for profit, not to mention customer satisfaction.
AI-powered retail intelligence allows retailers to perform at their optimum level in the market. McKinsey & Co. estimated that applying integrated digital solutions to merchandising could lead to a 50% faster time to market, an 8% rise in full-price sell-through, and a 20% decline in manufacturing costs [2].
The leopard print trend saw roaring success in SS24. How could brands know to invest? Using connected retail intelligence data, retailers could track this trend and see that leading fashion brand GANNI doubled its in-stock options from 2022, increasing from 41 to 80 in 2024 and expanding its leopard offering with new additions such as the Bou bag and buckle ballerinas.
The mass market capitalized on its virality, noting several copycat styles, including denim, smock dresses, and midi skirts in SS24.
Marks and Spencer paid attention to this data and landed a midaxi dress, priced £195.50 cheaper than its GANNI counterpart, that saw a majority sell-out 18 days after landing.
Similarly, ASOS and Topshop have been able to capitalize on copycat styles by landing denim and ballet flats that saw majority sell outs 11 and eight days after launching, respectively.
EDITED is the world’s leading AI-driven retail intelligence platform that empowers world-leading brands to make intelligent decisions across the product life cycle. Using connected metrics, we help retailers understand what, where, and when to invest their time and money.
Using EDITED’s market data, retailers are able to identify which of their competitors are investing in the latest viral trend and how it is performing. Retailers can track runway and social as well as the number of sell-outs vs. arrivals for assortments and the percentage of markdowns across the market.
Buyers and merchandisers are able to use this comprehensive data to evaluate the assortment’s pricing structure to determine whether they can compete with their prices. Conversely, with a market-wide view, users can identify areas of opportunity where other players aren’t meeting customer demand.
Sound like a solution for your organization? Chat with us today and ensure you invest in all the right retail trends.
Sources:
EDITED Market™
EDITED Digital™
EDITED Omni™
EDITED Signal™
EDITED Data™
EDITED Messaging™
EDITED Match™
EDITED Overlay™
EDITED Research™
