Can Artificial Intelligence help predict fast fashion trends?

The recent trends in the fashion world points to an amazing new possibility involving the use of AI to sort through Big Data and help businesses make better decisions by understanding their customer-base better.

The 2 main things I have noticed about fashion today is that it's fickle and slightly repetitive. Look at the emergence of y2k clothes based on fashion trends in the early 2000s (think Britney and Paris etc.). Fickle fashion is synonymous with fast fashion which is really popular especially with the younger generation. Clothes are made cheap and quick and allow for consumers to enjoy the ever-changing fashion trends as they happen. Of course since the clothes are made as such, they aren't of the best quality which means that they'll be worn for no more than a year (most likely) before being disposed off.

The turnover is incredibly fast and the timeframe is short and quick. If a retailer is unable to keep up with the demands of these trends, another will. I like to think of it as a tug of war - which brand can provide the trendiest clothes for the lowest price? And then when you start to look at more established brands that maintain a higher price point, the question then becomes, can the quality justify the price? Will this now trendy piece become a staple and be worn long after the turned has died down? And even then, who is that brand using the market and sell this product at such a price point.

⚡️ Anyone remember Cardi B and Balenciaga?? Or the fact that 25% of Nicki Minaj's songs reference a fashion brand which has led to a +1000% increase in the price of those designer shoes since 2007 according to this article.

Currently, we're only seeing AI being used in chatbots as a means for businesses to provide 24/7 customer support online and over the phone, or in providing a more personalized experience for customers that shop online by personalizing what they see when they go to the website using previous searches and purchases.

The Fourth Industrial Revolution brings about new pain points for consumers while also exposing the friction that exists when trying to convert data to meaningful human connections when selling a specific product.

I believe this can be done with AI, more specifically Natural Language Processing (or NLP). This is the way in which computers are programmed to be able to be able to process and analyze large amounts of natural language data - either text or spoken word (i.e., Big Data). Such an algorithm can be designed to help businesses make better decisions for their customers, not only by being able to predict trends before they blow up, but by also being able to help in operational decisions that would make the upstream and downstream supply chain more efficient. This is particularly important when you consider the tight schedules and high turnover that fast fashion brands undergo.

A more targeted tracking system that allows for the supply chain to be more easily managed is important for so many reasons:

↪ Business are able to have a better view of their sales forecast and implications of certain business ventures

↪ Suppliers and warehouses are also able to manage their time better and understand workload projections

↪ Brick and mortar stores are able to get a more realistic sense of inventory, particularly for more in-style pieces

Such an algorithm can be built to generate representational forecasting data under time and data constraints. This would be done using a web scraping (or data extraction) tool which uses keywords to pull content from all over the web (most likely targeting social media and online publications) to see what people are talking about and doing around fashion. The NLP algorithm would be able piece all this together by being able to convert that large amount of scraped data into meaningful information to be translated. I suspect that right before a fashion trends hits its peak, there are those few months where it bubbles for a bit before the general public catches on.

For months (nearly a year now), flared jeans and bright colors and patterns have been very on-trend - this is a stark contrast to skinny jeans and plain colors that previously very popular. It can easily be argued that as we (gradually) moved beyond skinny jeans into mom jeans and now flared jeans, the resurgence of y2k trends was also coming into the fold.

Spotting trends, such as this one, early enough is a great way to help brands make better consumer-focused decisions, forecast their demand and manage inventory.

In a few weeks I'll be discussing more ways that AI can help fast fashion stay on trend, while also highlighting the environmental price tag and potential AI-centric solutions!