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Sizes are never standard--you really have to try something on to know if it fits. How have you solved this problem?


Most of the women I know who are serious about their fashion are pretty certain when it comes to their size at a particular store. Sure a six isn't always a six. But a six at Forever 21 is usually consistent with other sixes at Forever 21. And they know their size at each particular store.


No, sizes differ within stores as well.


Maybe they could crowdsource this type of information.

"People who said this item fit well, also said these items fit well..."


I don't imagine that crowd-sourcing would work well -- body types vary wildly withing a given size. A size 6 isn't a size 6 isn't a size 6 . . .


I'm guessing the long term of the suggestions would be you would see that this dress fits similar to how a dress you own fits, thus implying that you could probably wear it.


1) Not every person wants the same kind of fit(snug,slim,skinny,relaxed,classic,natural, etc) or drape.

2) Look at this image to see the difference between different brands and their size 8 measurements.

http://www.nytimes.com/imagepages/2011/04/24/business/201104... via http://thesocietypages.org/graphicsociology/tag/womens-size-...

There's many variables to sizing. It wouldn't be impossible to create a database of measurements for every single piece of clothing.

And then there's the issue of shrinkage.


1) Not every person wants the same kind of fit(snug,slim,skinny,relaxed,classic,natural, etc) or drape.

Those are irrelevant details. The basic form of input is "person A gives rating R to item B". This is precisely the formulation behind successful solutions to the netflix problem.


You would need a pretty well-populated training set (assuming SVD or similar ML algorithm), I imagine, and somehow I think that might be difficult with so many unique item Bs. With Netflix you have many people watching the same movie, but I think there are many more dresses around, and women probably won't be rating hundreds/thousands of them (which is easier to do on movies).


The Yahoo Music dataset has these characteristics (more items than users), and a combination of methods (including the SGD-based matrix factorization that people call "SVD" in recommender lore) did pretty well on it (KDD Cup 2011: http://kddcup.yahoo.com/).


Interesting, thanks for the link.

What I find a little disappointing is that the top 3 prizes for this Netflix-Prize-style competition total $7,000 in value. Is technical brainpower, even that of students, really worth that little? Maybe startups should band together to hold their own optimization contests if the 'market rates' are so low.


Right. I'm not sure why others are misunderstanding how crowd-sourcing this information helps solves the problem.

People saying that size numbers vary greatly are missing the point. If I say a particular piece fits me well (regardless of its listed size) and then a bunch of other people say it fits them well (regardless of its listed size), the site can then aggregate the other pieces of clothing that those people said fit them well to show me clothes that potentially fit me well (regardless of their listed sizes).


Very true. However, once there is some data generated about how well the item fit the user, you can probably make some correlations and determine just what will fit who.

I would just call it data analysis, not crowd-sourcing


My guess: they haven't solved the "fit" problem, they won't bother trying (too hard), and it doesn't matter.

These dresses are equivalent to "found money."

Woman has a closet full of dresses. They're old, uninteresting, unwearable, etc. She posts them online, earns "buttons," and buys dresses that look like they might work. Some do, some don't. Net result: more dresses to wear.


And those that don't can just go back into the system again, too. Positives all around.

The "buttons" part is even more clever, in that they're building a real ecosystem that doesn't center on cash. Also, I can see this working incredibly well for pregnant women; they only need their maternity clothes for 5-6 months or so.


This does seem like a bit of a problem, but I'd imagine the idea is you "re-sell" anything you no-longer want-- which may mean it didn't fit you right.

What it strikes me this business needs are small pre-paid boxes which will fit in US mailboxes or can be left for your mailman.


I don't know if it's something that needs to be addressed. People who are more lenient are the target demographic more than people who would otherwise not rely on an online service.

EDIT: On an unrealted note, the name "Forever 21" is incredibly sad.


I've always assumed that Forever 21 appealed most to the under-21 crowd.


Just as "Seventeen" magazine is typically read by girls under the age of seventeen.


True. But the interesting part is how those above 21 will shop there for the disposable clothing. A 30 year old can get a dress, in their size, for around $25 (further supporting 99dresses' business model).


Why do you think Forever 21 is sad?


I agree. Peddling the illusion that a woman can remain 21 -- or should even want to -- is depressing.


Couldn't the system learn quickly? Like person A and B both wear a dress from person C. Now the system knows that person A could also exchange dresses directly.


I meant of course A and B could exchange dresses.


Suggestion: measure the dresses.

Sizes in women's clothing have no objective standards at all (I do so envy men's pants, which come in 34x30 rather than Size 8 Slim Petite), but Kendall Farr opens her well-known book by suggesting that women break out the tape measure anyway. Measure yourself, and then measure anything you're thinking about trying on -- it saves time.


It helps a litte but not completely. Women may be the same size and measurements, but a completely different shape (men have this problem too, right?) What we need is technology that can 3D scan an item and virtually drape it. Then I can get myself scanned and try on the virtual draping. Only then will I fully be comfortable spending real, non-returnable money on the internet for clothes (shoes and accessories are less of a big deal for fit).


Women tend to know their size within a given brand. As long as they stick to those, they'll be fine.


Roughly, "my measurements are X, and this item fit like Y" is how I would want it to boil down. I'm not sure it would go over if implemented just that way, but the idea is there somewhere.


Good luck getting women to post their detailed measurements on a public website....

Not sure this will work.


Your opinion of women on that matter is ill-informed. Where on the web do you see men actively sharing their pant-sizes? Those places just don't exist. Outside weight-sensitive communities like sports and performing arts, size is mostly irrelevant.


What I'm saying is of course from anecdotal experience. I am certain that many women I know who would otherwise fit the target market for this website would definitely not want to post publicly their measurements.

Obviously your experience is different. Happy to agree to disagree about the outcome, but lets not pretend like either of us have a definitive knowledge of all women.


Well, it could be anonymized, or a completely different take, perhaps a DSL for size and fit could be developed. Now that's a CS-level problem for an enterprising startup, "qualitative translation" or something. I'm sure there's entire classes on turning qual into quant.


It's not that difficult or important. I'm in fashion IT.


I guess I didn't understand your previous comment, then.

However, it could be totally anonymized, with measurements being used only to filter what is displayed. Think of it like a dating site, where whether someone smokes, or is a vegetarian, or whatever can be used to gauge compatibility (such as it is). Nobody knows my search criteria on a dating site.


Rent-the-runway lets you select an alternate size in case the thing you receive just doesn't fit right.


You just put it back into the system if it doesn't fit.


I would say that the virtual currency solves that a lot.


what?




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