Great job guys! Been following for a long time and it's impressive how far you've taken the company during this time! Kudos and great article!!
How we grew from 0 to 4M women on our app, with vertical machine learning
11–20 of 21 posts
Re: How we grew from 0 to 4M women on our app, with vertical machine learning
#12How much have you spend on Mixpanel??? ;) How did you get to insights/assumptions like "If people don’t do [action] during their first 7 minutes in their first session, they will not come back"?
Thanks for the question furilo. We run behavioral cohorts. We do cohorts over everything, every action people do, every screen they visit, every piece of value they receive. We also know when those actions take place (first 5 minutes, first hour, day, etc). With the above, we've learnt what actions have the strongest retention. Now we need to look at the duration of the first session, which we have. We know that if w…
Which action has the strongest retention in a fashion app like yours?
Re: How we grew from 0 to 4M women on our app, with vertical machine learning
#13Article suggests they are using perceived value of an outfit to train their Machine Learning model. I wonder what are those actions, Likes? Add to cart?
Re: How we grew from 0 to 4M women on our app, with vertical machine learning
#14Fantastic article and way to go on the accomplishments. Looks like you are in an amazing space to be. I am a big big fun of recomender systems.
Re: How we grew from 0 to 4M women on our app, with vertical machine learning
#15Awesome article with tons of learnings and details <3. I'm a big fan of them.
Re: How we grew from 0 to 4M women on our app, with vertical machine learning
#16Article suggests they are using perceived value of an outfit to train their Machine Learning model. I wonder what are those actions, Likes? Add to cart?
Thanks for the comment soci.
There is a lot of actions that express taste - sharing your own tagged outfits, searching for something, creating a specific album, and many more. And actually, each expression of taste has its own value. As we move forward, we'll need to get smarter as how we can help people, based on what data.
Re: How we grew from 0 to 4M women on our app, with vertical machine learning
#17Fantastic article and way to go on the accomplishments. Looks like you are in an amazing space to be. I am a big big fun of recomender systems.
thanks quarizmi!
Lets see how recommender systems evolve in this space. The tech and implementation will need to be very different to traditional recommenders, and access to data will be a huge barrier imho. We'll see:)
Re: How we grew from 0 to 4M women on our app, with vertical machine learning
#18Great job guys! Been following for a long time and it's impressive how far you've taken the company during this time! Kudos and great article!!
thanks abarrera :)
Re: How we grew from 0 to 4M women on our app, with vertical machine learning
#19I know you're just trying to get attention for some good work, but promotional voting and—especially—promotional commenting are the sort of thing that drive HN readers crazy and cause them to use unkind words like 'shill' and 'spam'. The HN community smells these things like a truffle pig smells truffles and they regard it as manipulating the system here. So it's definitely not in your interests to do this! In practice that means you should get your friends and team-mates to not vote and especially not to post booster comments in the thread.
Since it looks like the underlying work here is good, I suggest waiting a week or two and then reposting it, and make the title less buzzwordy and more neutral. If you email us at hn@ycombinator.com when the post is up, we can make sure it doesn't get flagged.
Re: How we grew from 0 to 4M women on our app, with vertical machine learning
#20I know you're just trying to get attention for some good work, but promotional voting and—especially—promotional commenting are the sort of thing that drive HN readers crazy and cause them to use unkind words like 'shill' and 'spam'. The HN community smells these things like a truffle pig smells truffles and they regard it as manipulating the system here. So it's definitely not in your interests to do this! In practi…
Thanks for the heads up, dang.
Truth is: for the first time ever, we've decided to talk about our machine learning approach and how we've managed to build our project, and we've thought many of the lessons learnt have value for the community.
We've really worked hard on the content of the post, trying to offer valuable insight on a number of things: how we work retention, onboarding, what's our learning process, and most importantly how we understand fashion taste. Lots of tips that imo are valuable for the community. And all this work, we've wanted to share it here on HN. Our friends are as excited as we are, and some have asked for questions / congrat'ed us here. No questions were planned.
About the title, it's what we've managed to do! While others spend millions on acquisition, we haven't, it's been product based, no tricks, its been done by building an efficient product, step by step, countless nights. Few people in this industry, outside the fashion space, know Chicisimo, and we wanted this to come to an end. I'd appreciate the flag to be lifted.