Take the guesswork out of fashion. Big Data is your latest and hottest trends that’s taking the world of fashion by storm. In an industry where every color, cut, design and trend is micro analyzed and just as easily thrown out of the window with the next launch; you need to keep one step ahead of the competition. This is where Big Data puts its best foot forward (pun intended!)
Fashion as an industry is often regarded as frivolous or unnecessary, despite its global and money making capacity. But behind the scene is a very big business that can push the economy. The last projected revenues is around $3.75 trillion in 2016.
Fashion Data for retailers and designers
Big data solutions are increasingly become a part of the designers strategy. In an industry based on creativity, intuition and expression, applying cold data seems farfetched. But it is precisely this that helps the designers and retailers to accurately predict the latest fashion trends.
Big Data is all about turning extremely large quantities of data into useful information. When companies aggregate data and analyze them effectively, patterns emerge, ideas are born, and fashion companies become trend setters.
Aggregating global fashion trend and sales information from a wide variety of sources –including retail sites, social media, designer runway reports, and blogs–Competitive Intelligence (CI) is synthesized from the data, accessible in real time and can be customized to spotlight information relating to the unique priorities or focus of the company.
You can aptly use the term “Trend forecasting” that Wall Street Journal contributor Kathy Gordon used to describe information analysis using Big Data. Leading in this field is the Editd, an apparel data warehouse aimed at helping the world’s apparel retailers, brands, and suppliers deliver the right products at the right price and the right time.
Solutions for a distinct fashion problem
Agile retail companies are using Big Data analytics to identify consumer trends, utilize highly efficient production and distribution systems, and only sell online. The result is products that people want, at prices they can afford, without having to go to a mall.
So why should the fashion houses and e-retailers care about the immense valuable data available through data analytics? A look below will answer your question:
One constant issue faced by the designers is guessing the right volume of items to be sold. An incorrect value will result in excess items being produced, which will have to be sold at discounted rates to make up for the loss. Using Big Data analytics, you can determine the demand and supply ratio accordingly, and produce in appropriate quantities.
Customers now want quick service with instant gratification. Mass production is a guaranteed way of satisfying the huge demand. But, it can also backfire with items being produced which may or may not be consumed. Using Big data analytics, retailers can manufacture items based on which products are working and quickly alter the production accordingly.
Instead of pulling solely from internal datasets, companies today are able to pull from a variety of datasets across the web to determine not only what their customers want but also what their competitor’s competition wants. Social media shares, likes, tweets are used to analyze the trends and people’s response to any new design launched by the designers.
Through the use of big data from data collection tools, even the notoriously fickle and creatively driven industries like fashion can more efficiently deliver the products and services that meet consumer demands. Identifying designer influence allows producers, retailers and consumers to make more informed decisions about what they buy, as well as identify tomorrow’s influencers within the industry.
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