A Vertical Machine Learning approach provides a competitive moat around your business
We at the Fashion Taste API follow a Vertical Machine Learning approach to fashion. We believe in the unique advantage of having a profound understanding of the consumer problems, end to end.
With a focus on the consumers, we've applied machine learning to automate the two processes that we've considered game-changing:
The Fashion Taste API is automating outfit and shopping advice, but always starting from the consumer.
We believe that fashion retailers have a clear advantage over newcomers: they are the domain experts. The specific benefits, however, need to be captured:
At some point, newcomers will offer In-Bedroom Fashion Stylist or Smart Mirrors to end consumers.
Apart from the increase in market share that this new category will generate, In-Bedroom Fashion Stylists will have two very relevant consequences:
And the current competitive moat around traditional fashion retailers will be gone.
The more digitally powered experiences you offer, the more taste data you will capture. The more data you capture, the better you can automatically serve your shoppers. The better you serve your shoppers, the more adrenaline you generate in your teams, the more ambitious they become.