The Lyst Index is a quarterly ranking of fashion’s hottest brands and products online, compiled by global fashion shopping platform Lyst. Its proprietary methodology combines demand data from 160 million annual shoppers using the Lyst platform with a curated set of signals across social, search editorial, and emerging AI discovery channels.
Launched in 2017, The Lyst Index has become a globally recognized authority on fashion brand heat, cited regularly by media including The New York Times, The Business of Fashion, Vogue Business, WWD, and CNN as a credible benchmark for brand and product trends and momentum. It’s a trusted barometer for the industry, referenced by executives, journalists, and analysts tracking what's shaping consumer demand worldwide.How is the Lyst Index calculated?
The Lyst Index methodology is structured around three interconnected dimensions of data: Desire, Demand and Discovery. Lyst platform data — the behavioural signals of 160 million shoppers connecting with 27,000 brands and stores online — is the core foundation of The Lyst Index formula. In combination, its signals map the arc of fashion’s digital attention economy, resulting in a comprehensive and culturally-attuned measure of brand heat.
The volume and sentiment of social conversation across platforms including Instagram, TikTok, Pinterest, Substack, Reddit and emerging channels. Not all attention is equal: social endorsement signals originating from Lyst’s Fashion Intelligence Network — a Lyst curated network of accounts identified as trend originators and brand heat catalysts — carry more weight, as a leading indicator of cultural relevancy and desire before it scales.
User-generated content on social media is one of the most authentic expressions of online desire. We track UGC volume and engagement as an indicator of grassroots online momentumfor brands and products.
The reach and resonance of organic coverage in fashion’s online editorial ecosystem: digital fashion publishers and newsletters weighted by outlet authority and sentiment. We track how brands move through the online editorial landscape from runway coverage to shopping stories.
Lyst’s proprietary fashion demand data, from 160 million annual shoppers connecting with 27,000 brands on the Lyst platform, captures measurable intent to shop. These insights are the foundation of The Lyst Index; no external source in our methodology reflects the actual online shopping behaviour of millions of real fashion consumers with comparable scale or granularity.The signals we track include:
The volume and velocity of brand and product searches on and off the Lyst platform, including signals from major search engines. We track not just absolute search volume, but also the rate of acceleration over the quarter. A leading indicator of brand heat, search is the most direct expression of active online demand.
Lyst shoppers’ behavioural data: following brands, saving pieces to wishlist, adding to basket. We track conversion rate and sales, product page engagement depth, and funnel progression data across Lyst’s global user base.
Data on whether Lyst customers are engaging with and purchasing products at full price, or through promotional mechanics and sales, and at what level. In today’s extremely competitive online retail environment, full-price online sell-through is a strong indicator of brand heat.
We track the number of individual products each brand has ranking within Lyst’s top 1000 trending items in a quarter.
We track stock levels and sell-out patterns on Lyst. Products that sell out quickly across multiple online retailers, or that sustain strong demand signals despite limited availability will score more highly than those with persistent excess supply.
As shoppers increasingly discover fashion through algorithmic feeds, creator content, and AI-powered search rather than physical retail or traditional media, the online discovery landscape is becoming a new engine for brand heat. The Lyst Index methodology tracks:Visibility in AI Search and DiscoveryCustomers are engaging with new ways to discover fashion, and we measure brand and product presence within these new environments. We track inspiration-led queries associated with brands and products, emerging search terms as well as referral data showing the new digital pathways through which shoppers are connecting with brands and products online.
We track the rate at which brands are reaching net-new shoppers versus deepening engagement with an existing base on Lyst. We distinguish organic online discovery from paid acquisition, treating the former as a more meaningful signal of genuine discoverability.
Signals of a brand being discovered beyond its core fashion shopper audience in adjacent online communities e.g. entertainment, music, sport, art, gaming, film. These cross-category moments can be powerful indicators in The Lyst Index methodology: a brand that begins appearing authentically in new online spaces is a brand whose cultural relevance is expanding
The Lyst Index is calculated quarterly. Within each measurement period, more recent signals carry greater weight, reflecting the pace at which online brand heat moves. Each data dimension - Desire, Demand, and Discoverability - is scored and weighted using a proprietary model refined by Lyst’s data team. We do not disclose the exact formula.
All of the signals we track, and the technologies we use to process and interpret them, help to power Lyst’s shopping recommendations and product experience. The Lyst Index will continue to evolve as our core shopping product transforms, and customers interact with Lyst in new ways. The Lyst Index is, in this sense, our flagship expression of Lyst’s platform intelligence; what more than 15 years operating at the heart of online fashion has made it possible to know, to measure, and to give back to the fashion industry we love.
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The Lyst Index is a quarterly ranking of fashion’s hottest brands and products online. Its proprietary methodology combines demand data from 160 million annual shoppers using the Lyst platform with a curated set of signals across social, search editorial, and emerging AI discovery channels.