Updated: Mar 21
Big Data provides a new opportunity for testing products and marketing campaigns in innovative ways.
As we have discussed in our series on influential digital fashion trends, data-driven innovations are some of the most impactful trends we are seeing in the fashion industry today. From deep analysis of shopping behaviors, to department stores increasingly leveraging data to help predict the rise and decline of future trends, to algorithms that create new designs, data is front-and-center in the future of fashion. And in this post, we’ll dive deeper into data in the fashion industry.
The Influence of Shopify on Data-driven Fashion Trends
According to an article from The Business of Fashion (BOF), Shopify is the second largest e-commerce platform in the US, covering 1 million retail partners across 175 countries and accruing over $1.5 billion in revenue in 2019. Shopify was founded in 2004, during a time of distinct digital disruption in retail. Its 16-year history includes a successful IPO in 2015, where shares traded 60 percent higher than its offering price on the New York Stock Exchange, and the platform has adapted over time to meet its community’s business needs.
Shopify has launched apps, API platforms, payment solutions, marketing products, and even its own fulfilment network. In 2014, the company also launched Shopify Plus, a division of Shopify that focuses on serving high-volume businesses. Shopify Plus provides a platform that enables integrations and customization through Shopify apps and partners, as well as an accelerated and customisable checkout to over 7,000 brands.
Due to its wide range of retailers, many of which are part of the fashion industry, Shopify Plus has a rather enviable perspective on the retail market and the entire fashion industry. But at least it isn’t keeping these insights to itself - Shopify Plus is launching its dedicated Fashion Industry Report, compiling its findings into an accessible report that summarizes both the biggest challenges and opportunities that retailers face today. For example, the report suggests that while manufacturing elsewhere is not yet at the same quantity or quality level as China, it makes sense for retailers to begin diversifying production outside of China.
Breaking Down Future Data-driven Trends Shaping Fashion
As Shopify continues to leverage data to gain (and share) insights about fashion, the rest of the industry has plenty of access to helpful data for analysis. And while the amount of data and ways it can be utilized might seem a bit overwhelming, we’ll help you break it down. There are four core ways in which big data is positioned to advance the fashion industry.
1. Discovering trends
Until recently, the fashion industry had been using Last Year (LY) sales data to determine the popularity of trends and styles. However, as more real time data becomes available, designers have access to much better predictors of future trends. Rather than relying on LY sales data to make clothing for the coming year, designers and retailers are beginning to adapt and make clothing that consumers are more likely to buy based on new data sets that contain information about what is currently happening. For example, by accessing data on Google search queries, companies can identify what potential customers are searching for and thus more rapidly fulfill those demands.
Companies such as EDITED and Worth Global Style Network (WSGN) are at the forefront of this shift, changing the way fashion designers and retailers are able to engage with big data. In addition to leveraging more useful, real time data to predict what items they should create, they also help brands identify successful pricing models and timelines to inform better decisions about when to adjust pricing to meet changing demand.
Meanwhile, the powerful brand Zara has been known to collect sales data and analyze performance of features of different SKUs. After, Zara then leverages these insights to design and manufacture models that have the most popular features that will satisfy customer demand.
2. Identifying Emerging Artists
In general, retailers have typically preferred to source style and products from designers who have a proven track record of strong sales performance. However, as such, these designers can command higher prices, which can be an obstacle for mid-tier retailers with fashion savvy but price conscious customers. The ability to analyze data in more complex ways is transforming this notion, facilitating the identification of designers that are gaining popularity with consumers but who are not yet signed to a major brand.
How is this done?
Brands are leveraging social media analytics, and doing so is a great way for mid-tier retailers to discover talented designers and produce sought-after pieces at a lower cost. This trend is, of course, immensely advantageous for rising stars in design as well, who, in the past, would have experienced more obstacles breaking onto the scene and becoming discovered.
3. Changing the Way Companies Conduct R&D
Because advertising, brick-and-mortar merchandising, and social media effectiveness can all be evaluated close to real-time, companies can quickly pivot and invest into methods that prove to be most effective. For example, a retailer could track the performance of an advertisement on its website, collect data, change the language of the advertisement, and then rinse and repeat. This can help designers and retailers make more strategic decisions in a much shorter timeframe to drive outcomes.
4. Upgrading performance
Designers and retailers can now conduct experiments that were previously not possible.
Data in fashion goes even beyond predicting trends and becoming more efficient - even the consumers themselves want access to and to track data. Smart fashion is the new wave of tech development in the fashion space, and it is driven entirely by this desire for data, such as wearables that track health and fitness performance.
Smart fashion has started to blur the line between tech and fashion companies, with household names such as Ralph Lauren, Samsung, and Sensoria all innovating in this space and creating products that enhance people’s fitness journey and performance. The products they are creating are becoming technologically versatile, offering many capabilities from tracking body heat, recording heart rates, providing adjustable bra support, and charging via solar power. While some of these products are still in their early stages and have not become mainstream, this paradigm is often seen as the way of the future.
Another area of fashion that has seen improved performance through data is returns and refunds and pin-point sizing. As point-of-sales (POS) systems continue to improve, retailers can track what items are returned most commonly due to poor quality or to defects, which informs both purchasing and manufacturing decisions. Likewise, data captured on exchanges can assist retailers in adapting the sizes they provide more accurately reflect customer preferences and body types.
The Bottom line
Many people refer to data as the “oil” of the 21st century, and the fashion industry is certainly a prime example. Access to and insights from data are disrupting ways in which fashion companies and brands operate, enabling a customer-centric world where things happen more efficiently and everybody wins. And in the next post about hyper-personalization of fashion, we’ll further examine this shift to an emphasis on personalized fashion and how it affects consumers.
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