👗 Fashion Forward

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How AI helps in trend forecasting

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In Other News - a few interesting developments we're tracking

AI is transforming the fashion industry, especially in trend forecasting, by analyzing vast amounts of data from social media, search trends, and consumer behavior. This enables designers and fashion companies to predict upcoming trends and create collections that resonate with consumers' tastes and preferences.

AI-powered tools can analyze millions of posts from platforms like Instagram, Pinterest, and TikTok to identify emerging patterns. By examining hashtags, mentions, images, and influencers' activities, AI can determine what styles, colors, and accessories are gaining popularity.

Heuritech

Heuritech, a French company, uses AI to analyze over 3 million images shared daily on social media. Their technology can identify the rise of specific patterns, fabrics, and colors. AI also takes into account influencers' impact and consumer reactions to new styles. For instance, Heuritech can predict whether oversized jackets or particular shades will be in demand, allowing brands to adapt their collections accordingly.

Nextatlas

Nextatlas is an AI-driven trend forecasting platform that uses data from social media platforms to predict trends up to six months in advance. Their AI scours user-generated content to detect signals that indicate an emerging trend, offering insights into things like new silhouettes, textures, or even subcultural movements that might influence fashion design.

Using Search Trends for Consumer Preferences

Search engines provide a wealth of information about what people are actively looking for. AI can analyze search data to identify changes in consumer interest, which helps brands predict demand for certain styles or products.

Google Trends and Edited

Brands often use tools like Google Trends combined with fashion-specific AI platforms like Edited. Edited is a data-driven company that tracks search data, product availability, pricing, and discounting strategies across fashion retailers. By combining search trends with product data, they can advise fashion companies on what’s currently selling and what’s projected to be the next big thing, helping retailers plan their inventories and collections.

Combining Data Sources for Enhanced Prediction

By combining data from multiple sources—social media, search engines, online retail platforms, and customer reviews—AI can generate a holistic view of the fashion landscape. This comprehensive analysis helps designers and brands stay agile, responding quickly to shifting consumer demands.

Lyst

Lyst is a global fashion search engine that uses AI to track millions of online searches and social media mentions across thousands of brands. Their AI analyzes data in real-time to provide insights into trending products, brands, and even individual fashion items. For instance, if a particular sneaker style starts gaining attention across multiple platforms, Lyst's AI will quickly detect this and highlight the trend for both consumers and brands.

AI-driven trend forecasting is revolutionizing how fashion companies predict and react to consumer preferences. Companies like Heuritech, Edited, and Lyst are pioneering these technologies, enabling brands to stay ahead of the curve and align their collections with evolving trends.