How Predictive Analytics Can Boost Product Development
Fashion designers are futurists.
They play some of the most important roles in the fashion and retail industry. From having to be wary of the current trends that are happening at that moment, to thinking far ahead at what might be ‘cool’ for later on. It is no wonder that fashion designers are some of the most stressed, tired workers in the retail business.
And with social media and fast fashion changing the landscape of the fashion world, it is getting harder to keep up with the never-ending, always changing trends. To be on top of their game, fashion designers, much like technologists (programmers or engineers) need to be learning constantly.
Besides honing their craft in designing and creating, a great fashion designer must spend a limitless amount of time researching the market for what is and will pop off next.
How Big Data & Predictive Analytics Help A Designer
With all of the pressure and constant change thrown at a fashion designer’s path, the advent of predictive technologies has only served to help even out the playing field for designers.
Now, more than ever, rather than being pressed down by competition, flattened by all the flurry of social media influencers and ‘fast-fashion’ retailers, designers are able to utilize big data analytics to effectively look ahead.
One of the biggest ways that fashion designers can benefit big data and predictive analytics is through the aggregation of trends and sales across multiple channels. These days, there are so many areas to get data from, as apparel is being sold through social media avenues, offline, etc.
Beyond that, a designer can benefit largely from pulling from a pool of a wide variety of data sources, from runway reports to the millions of blogs that discuss what is trendy. With this treasure trove of information laid out in front of them, where companies like Chain of Demand summarize them into insights, and in turn transfer these into recommendable actions, designers can do what they do best: look and stay ahead.
All this information will provide designers the ability to plan for the next design far into the future. They can see what colors, patterns, styles are trending or may be of interest down the road, which in turn allows them to create products that their customers truly desire. With that, everybody wins.
There is an infinite amount of ways that big data and predictive analytics can help a retailer grow in regard to design. Beyond just predicting trends in what clothes will be big in the market, offline fashion brands can also utilize shopping behaviors to improve the management of their shops as well.
Although there are quite a lot of advantages that predictive analytics does provide a fashion designer, it is definitely not a be-all-end-all. What this means is that, just like any technological support, it is there to assist, not to make the final decision. At the end of the day, the insights that are provided or gained are simply extra information for the designer to make the final call. No matter how much detailed data the analytics show, human intuition is ultimately what governs the final say on how to go.
Moreover, for fashion designers to benefit from predictive analytics, they must work together with marketing, management, and planning to truly execute the best. While machine learning has helped retailers move forward and obtain great gains, it is the collaboration of each role that garners the optimal outcome for the company.