How Netflix Turned Viewing Data Into Fashion's Most Powerful Market Research Tool

OPEN SOURCE by SSQRD

Fashion has always borrowed from screen culture, but something changed when streaming platforms replaced broadcast television and algorithmic recommendation replaced the programming schedule. The relationship between what people watch and what they buy is no longer being observed by fashion brands after the fact. It’s being engineered in advance, and the platform doing most of that engineering is one most people still think of primarily as a place to watch TV.

Netflix reaches over 300 million subscribers globally, generating behavioral data at a scale and granularity that no predecessor media format could match. Members watched over 94 billion hours on Netflix in the second half of 2024 alone, and the platform knows not just what they watched but when, for how long, what they rewatched, where they paused, and which thumbnails drew them in initially. That behavioral dataset is now being connected directly to fashion retail infrastructure in ways that fashion press coverage has been ignoring.

The argument of this piece is as follows: Netflix is no longer simply a platform that influences fashion trends as a cultural byproduct of popular storytelling. They’ve built commercial infrastructure that converts viewing behavior into targeted fashion commerce, with costume departments functioning as de facto trend forecasting operations and viewing data functioning as the market research that tells brands which aesthetics will convert before those aesthetics surface anywhere else.

The Netflix Effect, the documented phenomenon by which a show’s costumes generate measurable spikes in retail search and purchase behavior, has been visible since at least 2020. Bridgerton’s first season caused searches for “floral print dresses” to rise 146% and searches for “regency dresses” to rise 84%, according to e-commerce aggregator Love the Sales. Wednesday caused Depop searches for Wednesday-inspired outfits to increase by 1,000% in December 2022. Emily in Paris caused searches for “Jacquemus cardigans” to rise 18% and “Ganni bags” to rise 15% month-on-month following its fourth season in 2024. The pattern has been consistent enough across enough shows and enough years that describing it as coincidence stopped being credible.

What the press has largely treated as an interesting cultural phenomenon, audiences buying clothing inspired by characters they love, is from Netflix’s perspective a commercial signal with significant monetization potential. The platform has spent the years since Wednesday and Bridgerton building the substructure to capture that signal directly, rather than watching it flow to retailers who weren’t paying for it. The Google Lens partnership is the most visible expression of that strategy, but it’s not the beginning of it, and definitely not the end.

In August 2024, Netflix and Google announced a shoppable integration built around the fourth season of Emily in Paris. The partnership allowed viewers on all Netflix plans to use Google Lens technology to scan looks worn by the show’s characters directly on their screens, with the scan directing them to similar items available for purchase. For viewers on Netflix’s ad-supported tier, the integration went further: shoppable pause ads encouraged members to scan the paused image on screen using Google Lens, routing them to a shopping page without leaving the viewing experience.

This was the first time Netflix built a direct transactional bridge between a specific show’s costumes and the purchase infrastructure of a major retail platform. The Emily in Paris wardrobe, curated by costume designer Marylin Fitoussi, was no longer simply influencing what viewers searched for after an episode ended. It was a shoppable catalog available in real time, mid-viewing, requiring nothing more than a phone scan. The fiction and the fitting room, which had always been adjacent in fashion culture, were collapsed into a single interface.

The partnership also marked the first time Netflix executed title sponsorships on existing library content, with Google serving as title sponsor for not just season four but the previous three seasons retroactively. Google’s shopping infrastructure is now attached to content that was produced years before the partnership existed, converting an entire show’s archive into a commerce channel without changing a single frame of the original. A viewer who discovered Emily in Paris through Netflix’s recommendation algorithm in 2023 and decided to rewatch it in 2025 is now navigating a show that has been commercially instrumented in ways it wasn’t when they first saw it.

Netflix launched its ad-supported subscription tier in late 2022 and has since grown it to more than 190 million monthly active viewers globally as of late 2025. The significance of this growth for fashion brands is not primarily the audience size, though 190 million is a substantial number. The significance is the data infrastructure that the ad tier required Netflix to build, and what that infrastructure now makes possible for advertisers with the budget and sophistication to use it.

At its May 2025 Upfront presentation, Netflix unveiled the Netflix Ads Suite, its in-house advertising platform, and announced that advertisers could now incorporate their own first-party data through LiveRamp or directly with Netflix to match datasets for behavioral insights and targeting against Netflix’s audience. Netflix also opened third-party data access to partners including Experian and Acxiom, and announced a clean room strategy for data collaboration and partnerships. A fashion brand can now bring its own customer data to Netflix, match it against Netflix’s viewing behavioral data, and build targeting strategies around the resulting combined profile in an environment where neither party has to share raw data with the other directly.

In September 2025, Netflix made its inventory available programmatically through Amazon’s demand-side platform, giving buyers access to Amazon Audiences, which are segments built from Amazon’s shopping, streaming, and browsing signals. A fashion brand advertising on Netflix can now layer Amazon’s purchase history data on top of Netflix’s viewing behavioral data to identify and reach consumers whose watching habits align with their purchasing patterns. Categories in which Amazon’s purchase data is particularly relevant, including apparel, are specifically identified as well positioned to benefit from this integration. The viewer who binged three seasons of Emily in Paris and purchased a Ganni bag on Amazon is now a targetable profile that a fashion advertiser can reach with a campaign specifically designed for someone whose viewing and purchasing behavior fit that pattern.

The commercial infrastructure Netflix has built around its content changes the role of the costume department in ways the industry has not yet fully articulated in its coverage of either fashion or media. Costume designers have always influenced fashion, but historically that influence was indirect and unquantifiable. A costume became a trend when audiences responded to it emotionally and then expressed that response through purchasing behavior, a process that played out over months and was observable only in retrospect, through retail data and social media trend reporting that lagged significantly behind the actual moment of cultural resonance.

What Netflix’s viewing data does is make that process visible in real time and in advance. The platform knows which scenes viewers rewatch, which character’s wardrobe generates the most pause-and-search behavior, and which aesthetic directions are resonating with which demographic segments before any of that data surfaces in retail search terms or social media trend reporting. A costume designer working on a Netflix show whose aesthetic choices are generating unusually high engagement signals in early viewing data is, in practical terms, a trend forecaster with access to market research that no independent forecasting agency, including WGSN or Heuritech, can replicate from the outside.

Netflix spent approximately $17 billion on content in 2024, and every production decision, including costume budget and aesthetic direction, is informed by behavioral data from previous content. The shows that get greenlit, the characters that get costumed in specific ways, and the aesthetic worlds that get built with significant production investment are all downstream of what the data shows about audience engagement and conversion potential. When Bridgerton’s corseted silhouettes generated the retail response they did, that signal fed back into decisions about which shows to commission next and how to costume them. The trend forecasting and the content production have become mutually reinforcing, with viewing data connecting the two in a feedback loop that operates at a speed and scale the traditional fashion industry’s forecasting infrastructure was not designed to compete with.

The infrastructure Netflix has built systematically advantages the brands with the largest advertising budgets and the most sophisticated data operations. Categories in which Amazon’s purchase data is particularly relevant, including apparel, are well positioned to benefit from the Amazon Audiences integration with Netflix’s ad tier, which in practice means the brands already selling at scale on Amazon are the ones best positioned to convert the viewing behavioral data Netflix is generating into targeted fashion commerce. The brands that can afford to participate in Netflix’s data clean room partnerships are the brands that already have the customer data infrastructure to bring to those partnerships.

An independent designer whose aesthetic is resonating with viewers of a Netflix show has no access to the data showing that resonance, no mechanism to be surfaced in the Google Lens shopping results that the show’s pause ads direct viewers toward, and no budget to participate in the data partnerships that would allow them to match their customer profiles against Netflix’s audience. They will observe the trend their aesthetic helped inspire showing up in retail search data weeks or months after the fact, by which point the brands with the infrastructure to act on early signals have already produced and marketed their version of it. The pattern documented in Open Source’s earlier piece on the clean girl aesthetic and quiet luxury, in which cultural practices originate in communities without capital and are later commercialized by brands with the resources to move quickly, now has a new and considerably more technically sophisticated accelerant operating inside it.

Netflix’s ad-supported tier now accounts for over 45% of sign-ups in all markets that carry the offering, meaning the majority of new Netflix subscribers are entering an environment where the content they watch is directly connected to commerce infrastructure they have no particular reason to be aware of. The platform that most intimately captures what people find aspirational, through sustained emotional engagement with characters and narrative worlds built with the explicit goal of generating that engagement, has built a monetization layer that converts that aspiration into targeted retail transactions. The shows themselves are not changing, it’s the foundation running underneath them, and the brands best positioned to benefit from it are the ones with the most capital to invest in the data partnerships that make the infrastructure useful.