How we grew from 0 to 4M women on our app, with vertical machine learning

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"?

Re: How we grew from 0 to 4M women on our app, with vertical machine learning

#6

Post by gimenete » Tue, Jan 30, 2018, 5:05 PM UTC

Very interesting article. It's impressive the engineering effort you are making here.

Re: How we grew from 0 to 4M women on our app, with vertical machine learning

#7

Post by aldamiz » Tue, Jan 30, 2018, 5:17 PM UTC

michokest wrote: post #3

Thanks for sharing! You’ve talked about your ontology, can you explain a bit more about how you build it?

Thanks for the question.

The question we figured out we need to answer is: what type of outfit ideas are people looking for, and how do they describe their needs? And then, how can we match those needs with relevant content.

So what we did (what we do) is look at people's queries, and also at how people describe their clothes, their outfits or albums (combinations of outfits, like pinterest boards). There is a lot of data here, millions of keywords, but many of them are similar (pants and trousers, or pantalones in Spanish). So we’ve extracted the main concepts (pants) and built a system of equivalences. Basically, now, we know “all” the needs people have when it comes to deciding what to wear, and have a pretty complete view of different ways of describing those needs, and how good the system is at responding to those needs (database of outfits).

Re: How we grew from 0 to 4M women on our app, with vertical machine learning

#8

Post by aldamiz » Tue, Jan 30, 2018, 5:17 PM UTC

pab_rey wrote: post #2

Amazin job... thanks for sharing!!

thanks pab_rey!

Re: How we grew from 0 to 4M women on our app, with vertical machine learning

#9

Post by aldamiz » Tue, Jan 30, 2018, 5:18 PM UTC

gimenete wrote: post #6

Very interesting article. It's impressive the engineering effort you are making here.

Thanks gimenete! We actually do things as simple as possible. But complexity is increasing:)

Re: How we grew from 0 to 4M women on our app, with vertical machine learning

#10

Post by aldamiz » Tue, Jan 30, 2018, 5:27 PM UTC

furilo wrote: post #5

How 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 we dont convert people during their first session, they is no coming back - no push or email or anything, will bring them back.

Once we know what the lever of retention is/are, and much time we have to convert, we run user tests with different types of users (converted, non-converted, people who've abandoned the app, people who dont know the app), and observe how they discover the lever, how they describe it, how they use it. This is gold, and helps us iterate.