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Like food business must deal with the cold-chain, Clothes businesses have distinctive features other retail areas don't have, there's a reason fitting rooms exists in clothing brick & mortar stores.

How do you replicate the fitting room experience online? with colors you can see differently on a monitor, texture you can't feel, sizes for each body type that are different, etc. , the best way today is to order more and return.

> Why exactly is this unbelievably damaging to environment is an exercise left to the reader.

Well people need to find clothes that fits them. So they're either left with going to a brick & mortar store, or ordering online and returning items that don't fit.

Me and all other customers driving to the outlet malls (assuming that mall has all the stores we're interested in, otherwise drive to each store separately), and driving back in our cars is certainly more damaging to the environment than one extra shipping, given that UPS, USPS, Fedex and everybody involved in the transportation business is making sure they're wasting the least amount of gas.



I get where bitL is coming from.

I was just thinking about a compromise model: what if a retailer would deal with the send/return cost once as a bit of configuration and customer acquisition cost and profile the choices to a standard type of fit. Then from that point on you could shop just for the type of clothing that will fit you well, and would only be able to return if you could show that it wasn't the case.

It obviously wouldn't work with standard brands of clothing since the fit there can be so variable, but if they clothing would be engineered for this I could see it working. It would be an interesting trade off for customers to consider. In the end you get lower prices, unless the real standardization is too costly.

Seems like something lots of people would go for. It seems like more and more people are aware of all the things that are priced into goods, like the cost of physical shops or the cost of shipping/returns for online retailers.


Yes, if we could employ some advanced model (ML or alike) to estimate fit depending on previous experience of the customer, that would be a huge efficiency gain. Actually, it might be the next big thing when you think about it...




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