Automating outfit advice

At Chicisimo, we are building the infrastructure to automate outfit advice, and we are shipping it to people via our consumer app.

Vision: Three years from now, the clothes in our closets will be digitized. They will be available to each of us through an app, which will act as a personal assistant: it will know our clothing habits, will tell us how to combine our clothes, and what to buy next. It will capture the attention and data of hundreds of millions of people. It’s a Spotify for clothes, and that’s what we are building.

Our infrastructure to build the above is composed of four assets:

1. A consumer app where people are storing their clothes, and seeing outfits uploaded by other people wearing those same clothes. Read more below;

2. A data platform that is receiving the data from the consumer app, and producing a dataset of clean, structured and correlated data that technology can interpret, and offer services on top of it. We call it the Social Fashion Graph. Read more below;

3. A dataset of correlated descriptors, outfits and people. These descriptors are a list of people’s what-to-wear needs, expressed in different forms. This dataset is exposed via a dataportal, which provides us with transparency and control. Read more below;

4. An IP portfolio protecting our innovations: tagging images with shoppable products; extracting correlations among clothes, in outfits and closets; outfits search. Read more here.

The above infrastructure is solving the single biggest problem people have with their clothes: How to wear them. There are other use cases, but all related to this problem. It affects people who absolutely know how to combine their clothes, and also people who do not; it affects fashion lovers, or people who simply need to decide what to wear.

Machine learning and deep learning in fashion are going to make people’s lives better, much better.

The Social Fashion Graph

The Social Fashion Graph is the name we’ve given to our data platform. It learns about people’s what-to-wear needs, and attaches those needs to outfits and to people.

The backbone of the Social Fashion Graph is our ontology, which is a list of the most relevant what-to-wear needs.

We’ve learnt that the top need we all have is how to wear our specific clothes. We can proudly say that we have found a way for women to tell us, in seconds, what clothes they have in their closet, and for the Social Fashion Graph to deliver the correct outfit ideas for those clothes, also in seconds. We believe this system is here to stay, and will end up coexisting with other mechanisms as we move forward.

The result of the above is a dataset of clean, structured and correlated data that technology can interpret.

We’ve exposed all this data thru a dataportal, which has provided the team with transparency and control. As a result, it’s easier to understand where we are, and what’s next.

Search and discovery, machine learning, deep learning… technology is going to transform closets.

Our consumer app

Chicisimo’s iPhone and Android apps connect the Social Fashion Graph to the reality of people’s needs, and captures clothing data.

Most important of all, the apps help us learn, they bring unique impact to our learning process. Thanks to our app, we receive daily direct feedback from many people, which helps us learn.

We think this is the most interesting aspect of building a consumer product. The fact that, regularly, we access new corpuses of knowledge that we did not have before. This new knowledge helps us improve the tech and product significantly, and it is a great reminder that we are not in the upper part of the learning curve -we are simply moving up.

When we’ve obtained these game-changing learnings, it’s always been by focusing on two aspects: how people relate to the problem, and how people relate to solutions.

Iterating a consumer app is a unique learning experience.

You can read about our learning process in this Medium piece, and see how we deal with retention, onboarding, etc. And in this link, you can read Apple’s description of Chicisimo - they feature our app regularly in more than 60 countries. Hey, we had to mention it!

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