Discover What You Love.

TWYL. - Twyl.

discovery engine.

Technologists are missing the mark. We've built a shopping experience that assumes we shop with words, largely knowing what we want.

Once we purchase an item, we then assume that we want other items very similar to the one just purchased.

Historically the Fashion Industry and the Tech Industry has had a canyon of understanding between them.

It's Time to Change That...

People are Storytellers. One way that we express that story is through our clothes. Shopping for clothes is a very intimate, emotional experience. It calls on all of our senses. We experience all of this in a physical store.

We are going to recreate that emotional shopping
experience in the online world.

Online Shopping Experience assumes you already know what you want to BUY
Online Search & Retail built to address scarcity & lack of competition

Online Shopping Experience assumes you already know what you want to BUY

1. We shop for clothes visually, being led by our personal preferences, tastes and style, whether we know it or not. Words assume we shop according to specs (27" inseam, boot leg cut, dark denim). That speaks more to the buying part of the pipeline. Not the 'shopping experience.'

2. When we walk into a store, we automatically curate what our experience will be. We shut out what does not fit our style and tastes and instead go touch what we love/are drawn to.

3. Personalization tech works when it's a Harry Potter book and you might like...the next book in the series. It doesn't work with fashion because we're not asking the right questions. We're not asking 'why' people bought a certain item. We're only focused on 'what'. And exactly because I just bought a red shirt, means that I don't want another pink shirt identical to it. So stop telling me I do! We all of this data intelligence and now
it needs a layer of human intelligence (art + science).

4. assumes that we know what we want to buy, at least in broad outlines and that's not how women shop. that's how men shop. by specs.

1. Shopping is about discovering what is a match for your taste and style. We're creating a discovery engine not a word-based search engine. If we shop visually, why do we search using words? That paradigm only works if we know what we're looking for, not on a discovery path.

2. "Touch What You Love" demo

3. Right now we use backward-looking binary data from previous purchases and similar items to create Recommendations for purchasing. This data only captures one dimension of the purchase and user. We will add another human, preference-based profile for both the item and the user to create Recommendations that actually hit the mark.