For many of us, the toughest decision of the day doesn’t happen at work, school, or at the nearest Starbucks (although that one often comes close). It happens in front of an overstuffed closet and sounds as mundane as “What should I wear today?” Each outfit that leaves our homes is an equation of a multitude of fluctuating variables (What’s on my work calendar? What’s on my personal calendar? What impression do I need to make? What is clean? What fits? Dress up or down? What do I feel good in? What do I feel like today?).
While users are enjoying the convenience of choice-reducing platforms such as Lyft, Blue Apron, or Hipmunk, the weight of fashion-related choices still lays on their shoulders. Add to that the unparalleled external pressure from the fashion industry that swears you will feel better if you buy another shirt, and we have an environment with just three alternatives: unbounded consumption, ceaseless frustration, or withdrawal into a uniform.
Meanwhile, the change is sweeping across the fashion industry itself: household brands are drowning in debt and shutting down, and even e-commerce fails to keep up with the fickle economy. Numbers don’t lie: for the last two years, ASOS, a British clothing retailer, doubled its revenue while the profit stagnated.
Amazon is often referenced as the catalyst for these changes — as well as an example, a threat, and an e-commerce giant turned US fashion market leader in the same two years. Unlike the struggling retailers, Amazon seems to really get data. Which gives them a major advantage — they know what to sell and to whom.
But what if we were to use all this data with customers’ interests in mind? What if we helped them figure out what will bring them real value and not just the fading buzz of an impulse buy?
AI can analyze past purchases, help determine the time a customer is ready to buy, determine what people of a similar profile bought and hundreds of other parameters to make a sale. Or, it can leverage the same dataset to empower mindful consumption.
For the individual, it will mean simpler and more satisfying fashion choices. And it will help the fashion industry reduce waste, improve work conditions globally, and scale sustainability efforts.
My company analyzes user’s wardrobe to first unlock its full potential, and only after that recommend an add-on of a few essentials that will provide a maximum number of looks. Instead of selling them 10 shirts for each pair of pants, we encourage them to buy less.
The same approach converts to other areas. For example, imagine taking a picture of your fridge, and instead of ordering what you’re out of, you get recipes from what you have left. If AI can make consumption more mindful and sustainable by putting the customer front and center, could this be a way to compete with giants?
Both millennials and younger age groups expect brands to give back, value authenticity and sustainability and search for personal connection with the products they use.
In the new world they are building, which business model is more likely to succeed?
Anastasia Sartan is a seasoned fashion-tech entrepreneur, the founder of AI-based stylist bot Epytom and a finalist of “Entrepreneur of a year 2015” by Ernst&Young.