Designers,
retailers, companies, creators, drawers, merchandisers all rely on big data to
create and market their clothing properly. Collecting customer data and analyzing it, is crucial in
the fashion industry. With modern business analytics tools, designers can
capture data sets that give them insight into the market penetration rate of a
specific trend, the longevity of the trend and the variability of the prices
and styles within that trend. As big data figures more prominently into
fashion, designers and retailers can more accurately predict and adapt to
changing market patterns. Every
customer has their own taste in clothing so finding the right clothing for the
right market can be a tough challenge. Peoples tastes strongly vary in
accordance to what type of clothing they prefer over others and big data helps
break down these walls. “Big data derived from places like the Hadoop BI provide more than enough information
for designers to create lines of products that will sell. Fashion designers who
use big data will come to startling conclusions about their designs”.
While
fashion companies need to understand trends at large, a fashion house will need
to meet colors favored by their customers at large. Big data can tell you
various factors in relationship to fashion such as a range of colors that were
purchased, and from there you can decipher which colors were most popular. This way a fashion designer can guide
production properly without losing track of what customers want to see. Data modeling tools can chart
customer preferences for color choices based on geographical location, seasonal
purchasing, and other localized metrics that can help retailers customize their
offerings for various markets. Jackets with dark blue and electric green colors
will sell more effectively in the Pacific Northwest, due to the proximity of the
Seattle Seahawks, versus markets in Arizona or New Mexico, for example.
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