Old school vs shiny new technology

I think people are too happy to dismiss “old school” in favor of new technologies. Old vs New should not be the singular criteria but rather, appropriateness given the situation. This being one of my pet theories, I was delighted to find (via Treehugger) that there is an active traditional knowledge inventory of older technologies being redeployed toward sustainable ends. At the forefront is Low Tech Magazine; consider this counter intuitive argument that bicycles are faster than cars (circa 1978):

The model American male devotes more than 1,600 hours a year to his car. He sits in it while it goes and while it stands idling. He parks it and searches for it. He earns the money to put down on it and to meet the monthly installments. He works to pay for gasoline, tolls, insurance, taxes, and tickets. He spends four of his sixteen waking hours on the road or gathering his resources for it. The model American puts in 1,600 hours to get 7,500 miles: less than five miles per hour… With his much lower salary, the Chinese acquires his durable bicycle in a fraction of the working hours an American devotes to the purchase of his obsolescent car. The cost of public utilities needed to facilitate bicycle traffic versus the price of an infrastructure tailored to high speeds is proportionately even less than the price differential of the vehicles used in the two systems.

fitting_robotCaveats abound, no need to argue the point but it is interesting to think about. Shortly after I read this, I found notice of a new exciting technology courtesy of BBC News. An Estonian firm has engineered a fitting robot with the purported intention of spurring online clothing sales.

“Only 7% of all clothing sales in the world happen online,” says Heikki Haldre, chief executive of Fits.me. “And the reason is that there’s no way to really try clothes on before you buy”.

Although it is irrefutable you can’t try on clothes virtually, it is not a given that a robot could provide this virtual function. I argue a better approach involves analyzing assumptions of the nature of sales and how to maximize them. Which is not to say the technology isn’t shiny (there’s a video, very very cool) but appropriateness is key. My approach would be to analyze who is buying clothes online, why they do it, which brands they’re buying and which they are not. For the record, it’s women aged 35-55 buying clothes online. It would be more useful (old school) to discover which vendors are better at capturing this market to reproduce its effects.

A fitting robot is not going to solve enough problems for enough people to be cost effective. First, the solution relies on a robot having volume and pattern measures of myriad styles across manufacturers embedded in its database. Most manufacturers don’t have that information internally so how could it be supplied to a third party (assuming they even would)? Why would manufacturers go through the considerable expense and time of gathering and supplying data when styles change every season?

You could argue a fitting robot would be great for a perennial style such as the Levi’s 501 but it is not so simple. Because each of Levi’s contractors is charged with making their own pattern, Levi’s would need data sets from multiple facilities they have in each country (Argentina plant 1, 2, and 3, lather, rinse and repeat for Brazil, Mexico, Turkey etc). The customer is only served if the jeans displayed, exactly matched the country of origin and supplier code from the care label to cause the given data set to be loaded into the robot’s working memory -and for said exact pair to be shipped to the customer. It is such a heady challenge as to be insurmountable.

An old school person would look for ways to increase Levi’s 501 sales by (arguably) more cost effective means such as standardization. If Levi’s used one pattern for all of their 501 production (destined for US consumers), their fit would be far more predictable. If their fit were more predictable across contractors, a customer wouldn’t need to try the jeans on. They could buy it online and be done with it. But no, if you want a well fitting jean, you are compelled to go to a store and try it on.

Technology is great to solve problems but it will never be a cost effective or appropriate application if its primary use is to compensate for inefficiencies or mistakes in our processes. If your refrigerator stinks, you can use some kind of high tech deodorant to mask the odor but the better solution is old school -clean the fridge. New technologies should be used to solve complex problems, not relatively simpler ones of our own making or within our control to mitigate. If your sizing is consistent and predictable, more people are going to buy it online even though buying online is a trade off. A consumer is trading the cost of their time in exchange for less uncertainty and a trouble free transaction.

Summary: the difference between old school vs shiny new technologies is that old school seeks to reclaim that which we once knew to solve problems that were never solved when newer technologies were lain over them. Both are useful and have their place provided the problem has been analyzed so you know you are trying to solve the appropriate one. It is less a matter of having the right answers than it is having the right questions.

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  1. Rocio says:

    -“If Levi’s used one pattern for all of their 501 production (destined for US consumers), their fit would be far more predictable. If their fit were more predictable across contractors, a customer wouldn’t need to try the jeans on.”-

    I made sure to keep ALL PATTERNS and Grading in-house while in charge of Garment Technology at Perry Ellis Europe… suffice to say that we had 65% of the British target market and the returns levels were under 1% while the volume doubled in a little under a year.
    Additionally, we were able to catch those vendors who tried to “sneak through” their own patterns (manipulated to use less fabric at the expense of fit standards) as soon as the goods arrived (vs having to hear about it from the buyer)

    While the technology does look interesting, I completely agree with you that the main problem is not being addressed.
    It almost reminds me of a few people who back in 2004-2005 thought that hiring me to create 3D images would signal the end of samples….

    P.S. I love the fridge analogy!!!

  2. NancyDaQ says:

    A fit robot–how would the consumer even access such a thing? It suggests to me that the consumer would have to go somewhere to be scanned or measured by it, which basically negates the convenience of purchasing online?

    Speaking from a consumer perspective, it would be so much simpler to buy online if companies made it easier and cheaper to return garments once they’ve been tried on. Something along the Zappos.com model perhaps? We’re saving the retailer the cost of operating a brick and mortar store so why gouge us with shipping and handling?

    I also like the option of returning internet-ordered garments to a retail location if the retailer offers both types of shopping. I think it benefits the retailer as well because in-store returns can buy additional sales. The consumer will often find other items in the store that she will then buy.

  3. David S says:

    “An old school person would look for ways to increase Levi’s 501 sales by (arguably) more cost effective means such as standardization.”

    Levi, Strauss can’t be bothered to make their contractors use the same color of thread for all the top stitching in a single pair of jeans. (I’ve got a pair of 501s that have mis-matched top stitching. Not a theoretical quality control problem.) I doubt they’re in a position to impose that sort of control. Who does the sourcing for fabric, thread, and findings? If it’s the factories, it’s unlikely they could use the same patterns.

  4. LizPf says:

    I read this while my husband and I were eating breakfast … and told him about the non-standard 501s … he was appalled that the American public would stand for inconsistent fit.

    Can you tell he only buys clothing (from LL Bean only) when his old clothes are in tatters?

  5. I’m with NancyDaQ. I think the problem of fit is unavoidable because of the massive variables, that have nothing to do with the manufacturer, the best thing online retailers can do is to work around this inherent “return aversion” that makes you not click “checkout” after all that fun shopping cart filling. Zappos has it right, they make returns so easy and painless, there’s no excuse not to try something. (It’s so easy you can order multiple sizes, as you would in a store.)
    Perhaps the 35-55 demo is inherently less return averse as a group because they are more established in their likes/dislikes, and are more willing to deal with snail mail returns. Just a thought.

  6. Barb Taylorr says:

    Perhaps it could work if they sold the fitting robots to the on-line retailers. Then it would be up to the retailer to build their own bank of all their styles on different body types each season. Depending on the cost of the robot maybe it would help sales…perhaps especially for bussinesses that sepcialize in non-standard sizes. Lands End had a virtual fitting room for a while. It was pretty simple though, you just selected a basic body shape, hair style, skin color & size – but it does not seem to still be part of their site anymore. I am assuming it did not turn out to be worth the cost of maintaining it. The one time I used it I decided not to buy the garment.

  7. Kathleen says:

    Not long ago, I was consulting with a company that wanted to start one of those fit info sites targeted to consumers. You know, you input your measurements and clothing parameters (work attire, dressy dresses, casual etc) and the site returns results with product suggestions that match. It’s nothing new, others have tried doing it but I don’t think it has been successful to the extent investors had hoped. The reasons I told them this wasn’t what they wanted to do if they wanted a rapid and high return (and they did) are the same reasons this fit robot won’t work.

    Other than the basics I mentioned above (manufacturers refusing to provide actual measures, it is proprietary information assuming they even collected it), retailers could do a work around by measuring product themselves but it invites a whole host of problems.

    One, you can have 3 people measure the same person and they will come up with 3 different sets of measurements. I have less confidence garments will be measured better than a person because garments don’t have the same kinds of obvious landmarks a body does. If too few know how to measure a body, why would they know how to measure garments? Let’s face it, it is boring work, they won’t be recruiting highly skilled garment technologists to do it; it will be clerks and sales people. If it is a nightmare when designers have sent data of garments they’ve measured, I don’t have any confidence sales clerks (who traditionally make products floor ready) will do any better than designers who know more.

    Then there are grey areas such as waist. Where does the pant “waist” fall? Five inches above the hip? This is significantly larger than the waist of a person yet people will compare a low cut waist dimension to their high waist measure and be upset when the pants don’t fit.

    Probably the biggest stumbling block for retailers is that they won’t be able to collect measures until after they receive the product, meaning they will need a lot of work done (measuring and web site work) in a very short period of time (overnight basically). Retailers have a hard enough time getting appropriate images from manufacturers that I don’t have a lot of confidence that something as complex as this will be facilitated sufficiently to satisfy anyone.

    As painful as it is, I think the best thing DEs can do is post the basic dimensions of their fit profile on their websites, listing size x was intended to fit a person of xhgt, xwgt, xchest etc AND mention the size that a model depicted on site is wearing along with her/his rough dimensions.

  8. Marie-Christine says:

    Alas, I see that My Virtual Model http://www.mvm.com/cs/ has bit the dust http://fashiontech.wordpress.com/2010/02/20/gregory-saumier-finch-general-manager-my-virtual-model/ This was the original, and I’d guess they probably closed because they were too focused on getting large firms to spend a lot of money. Now they seem to be going completely opposite, trying to up circulation by letting users play by themselves (and the losing weight model, eeck!).

    But I used it and liked it a lot, as a consumer. They were used extensively by Lands’ End, a place I patronize(d) mostly because they had consistent fit standards. You’d setup your mvm once, either picking a standard size or giving a pretty extensive set of measurements, finally customizing with facial shape/hair that reflected you. Then when you were contemplating some purchase you’d click on the ‘try it on’ button and pop! got to see that in the right color on your model, in 3D. Saved me from many bad ideas :-), steered you toward better choices. While the model was not a portrait, it was staggering how much like me it was. Having a different face was actually helpful in looking at the results with a critical eye. But having a good body model seems to me much preferable than the mannequin proposed here. I hope they get back to functioning, somehow.

    That said, I totally agree with Kathleen’s conclusion: it’s not necessarily the right answers, unless you’ve asked the right questions. Bravo to Rocio for enforcing standard fit. And I’d like to point out to NancyDaQ that I’d be a happy customer of zappos.. if they shipped outside the US. Trust me, there is a lot of demand out there in the world that’s not being met, and it’s a smart thing to even consider international distribution. That said, easy returns was another reason I shopped from Lands’ End when I was stuck in nowhereland, so I’m not knocking that philosophy.

    But Kathleen, you’re setting the bar way too high here in your description of fit problems. Unless you get scanned in one of those booths that have been around for 10 years without much concrete results, the robot fit you’re going to get is closer to ready-to-wear, that’s true. But that’s already a lot better than what you’re getting now online most of the time. And if mvm could do such a good job by allowing you to enter a few measurements, there’s no reason it couldn’t be refined to let you enter even more and so get even closer to your real body. Then all that’s limiting the consumer is their ability to take good measurements. And their patience of course, but that’s not such a big deal for a process you do once and use for several years afterwards, even for several retailers as was the case with mvm.

  9. Marie-Christine says:

    PS; Along the lines of the bike vs car analysis, the SF Chronicle once published a brilliant article comparing the good old kitchen knife with a shiny new robot. Sure the robot did in pounds of carrots in a flash. But if you were cooking for less than 20 people, the time spent cleaning the robot more than compensated for the speed of the operation itself. Likewise, just today I was reading an article http://www.rue89.com/passage-a-lacte/2010/07/26/et-si-les-animaux-de-trait-faisaient-leur-retour-dans-nos-champs-159922 about how Europeans are noticing that good old horses are actually a much more efficient (and economical) way to work a reasonable plot of land (say 15 acres).
    Many times, when technology seems incredibly more efficient it’s because some huge factor has been left out of the equation (like washing the cooking instrument). That said, I’d rather slit my wrists than live without a net connection :-)..

  10. Kathleen says:

    Were my french as good as your english M-C… what does it say about very small plots? My impression is that maintaining a horse will cost more than a small tractor. How about a mule? And what if it got sick or kicked me? Mr F-I (not sure if he was joking) suggested a sled dog to pull a small plow or mowing attachment.

  11. Note to non-francophones: a « robot culinaire » is a “food processor” in English. (I am loving the vision of all those folks in France discussing the merits of a size-efficient R2D2 model vs a bulky C3PO that can also handle table service, and calculating whether it’s worth the effort to spend their Sundays polishing it.)

    Kathleen, they say that donkeys are really nice pets. That they are beautiful, and even have a spiritual side. Maybe you could adopt a pet donkey and teach it to pull a plow.

  12. dosfashionistas says:

    Some years ago Mother Earth News had an article that made a good case for horses vs. tractors, especially in remote or rugged terrain. Horses, mules and donkeys can usually be adopted, although training one to the plow might be a long term project. I like the donkey idea. It seems like a good fit for a small piece of land. And donkeys are supposed to be good to defend against coyotes and other predators. People in Texas will run donkeys in with sheep and goats for that purpose.

    I will admit that I am biased on this. I would hope that appropriate technology would at least sometimes involve domestic animals.

  13. Marie-Christine says:

    A horse is much cheaper than a small tractor, and its upkeep not that different, once you factor in the relative costs of feed and diesel, vet and mechanic, etc. The relationship to living things is very different to motor-based ones, they warn :-), and work proceeds very differently.

    Mules and donkeys are a lot more efficient, as has been shown in many poorer countries. They’re also not quite as strong, but they tire less than a horse and eat less. I don’t see why a good sled dog couldn’t plow, except that sled dogs I’ve known to live in the SouthWest have been miserable creatures, given to spending the afternoon in the pool, and I don’t think the F-Is have a pool? But a sled dog is also a great fiber producer, so a friendly local spinner could furnish the F-Is with warm sweaters from the Spring molt alone, another factor to consider. Most tractors do not keep you warm in winter.

    I know several people who keep a few sheep to ‘mow’ yards of the range of at least an acre. All of them are very happy with the concept, and the practice. OK, one is from New Zealand so we can’t really count her because of prejudices :-).. But I’d definitely do it if I had a large area to keep brush-free. Goats are even more efficient and more fun, but it’s difficult to have pets as smart as yourself, they tend to get (you) into trouble.

  14. Heikki says:

    I’m from Fits.me Virtual Fitting Room – developing the Terminator bots as BBC dubbed us (I doubt it’s a good sign for the world of fashion). Really wanted to thank you for the insights in this article – you’re addressing some very important problems for the apparel e-commerce and fitting applications.

    At Hawes & Curtis, a British shirtmaker, where the Virtual Fitting Application is now used, the results are very promising. There’s a story about their experience in a recent Internet Retailer magazine:
    In trials the fitting room reduced the returns by 28%, on average, while increasing the sales by up to 3.1 times. The ROI of the online fitting application remains around 20-30x for a retailer, which should justify the expense of the technology, and should answer many questions about the feasibility of the technology.

    By the way, you are absolutely right about 35-55 (actually its 35-65 group: http://online.wsj.com/article/NA_WSJ_PUB:SB124286245782441235.html). However, I believe that instead of building new brands online to capture this market better, every brand should stick to their target demographic groups. For example, Abercrombie & Fitch should never start targeting this majority group.

    The reasons for returns – when clothing is bought online – is 60% because of the poor fit, 15% due to “feel” of the fabric, and 5-7% due to color misrepresentation. Fits.me fitting application can only solve the issue with fit. A real brick-and-mortar fitting room accomplishes much more: seeing how the dress goes with the color of your hair, there’s the amazing smell of the new leather jacket, sounds and music playing in the store, social factors, feel of the fabric, and ability to move around. My guess is that we will see much of it within the next 3 years (except the smell of the leather jacket).

  15. kathleen says:

    Hi Heikki, great comment. Thanks for stopping by.

    In some ways, we’re talking about apples and oranges so I will elaborate on some of my points within the context you provided.

    First I want to clarify the wording of your statistics because some will think you said 60% of goods purchased online are returned [due to poor fit]. Total returns of apparel related goods purchased online is +/- 25%. It certainly wouldn’t surprise me if 60% of that 25% were due to poor fit but other research shows fit returns as closer to 17%. Just as many returns were because the customer was sent the wrong item or it was damaged.

    Your case study is very interesting but again, one’s mileage may vary in that men return product much less than women do. Still, the figure of 28% in your case study is higher than the broadly reported stat of 25% but that could be because of the profile of their customer. Generally, men’s returns are lower than women’s over all. Other than that they are not as picky as women, the nature of men’s sizing makes it easier to avoid buying the wrong size in the first place. A 42 is pretty much a 42. In women’s sizes, a size 10 can mean anything -and often does. I still think that fit related returns can be dramatically reduced by greater clarity (information) at the point of sale which is a great option for smaller firms that can’t afford this technology.

    However, there are extremely significant reasons why other retailers can expect very different results than the example used in your case study.

    First is the issue of semantics. You said

    At Hawes & Curtis, a British shirtmaker… The ROI of the online fitting application remains around 20-30x for a retailer

    You first described the firm as a shirtmaker (which they are) which is a huge difference from “retailer”. Using “retailer” liberally elsewhere, lends the implication that it would work for all/many retailers but retailers rarely control the means of production of the items they sell. A shirtmaker -such as in your case study- does. I realize that sounds nitpicky so I’ll explain it another way.

    One who produces the products they sell is better described as a vertical manufacturer rather than a “retailer”. Selling what you make means that as the maker, you have access to data of your product. The kind of company that would buy technology like yours likely has tight controls and tolerances that don’t vary much from item to item. We and they use block patterns; there is a great deal of predicability from style to style between the output of one firm.

    That it is one firm -the shirtmaker selling their own stuff- is critical. Most retailers sell a broad variety of products from many producers. This shirmaker has the data to upload to their own robot, how will your typical retailer collect data from each of their suppliers?

    The answer is, they won’t. Assuming suppliers even have it (many don’t) Sizing information is highly proprietary and manufacturers will be extremely reluctant to give a third party their most tightly held secrets.

    In the end, I think this technology could be great for some vertical clothing manufacturers (Levi’s being but one exception for my previously noted reasons) who have the means to purchase the technology and who can upload proprietary data to their own robot for the purpose of selling their own stuff. However, the case study is misleading in that it won’t help the majority of retailers who won’t have access to data from their suppliers.

  16. Heikki says:

    Hi Kathleen,

    I find this conversation so interesting. Indeed – how about going over to e-mail or doing a conference call where I’d call my CTO to join in.

    However here I’d like to write some which is of more public interest – about the return rates.
    On average, in apparel online sales, rate of returns is 25%. Polos and t-shirts have the lowest returns at 8-11%, the highest rate at 40% would be high ticket fitted fashion items. Trousers have also had high return rates 30-40%. In some countries, like Germany, the return rates are much higher due to open invoicing – it encourages more customers buy multiple sizes at once to return the wrong ones.

    While a return is a nuisance, the real cost for a retailer is the cost of time – usually more than 4 weeks from the initial sale. The garment sold in August, and returned to the sales cycle in October bears significant discounting costs.

    I would stick to saying that 60% of returns are due to poor fit and am afraid, I do not agree with the 1999 research that cited the 17% figure. There certainly are retailers with return rates where poor fit is much lower concern, but of hundreds retailers we’ve been spoken to by now – and of those most collect the data about reasons for returns – an average between 50-80% has emerged. In the end – it’s up to the retailer to decide if it’s the fit, or are there other issues that need to be solved first (for the record, I do believe that for most online retailers there are many other issues that should be prioritized over the fit).

    One of the concerns many commenters have voiced is the sizing differences throughtout different manufacturing sources, and as you point – the trade secrets on the fit of the brand. I guess, it might be due to some poor communication that Fits.me is projecting, but using the robots we can easily, cheapily, and en masse, reverse engineer these fit types. As it goes beyond the publicly interesting topic, I’ll stop here.

    I really love all you voicing your opinions! Please keep them coming! And if you’d like to get in touch personally, please do so at heikki/at/fits.me (remove the slashes).

  17. kathleen says:

    On average, in apparel online sales, rate of returns is 25%. Polos and t-shirts have the lowest returns at 8-11%, the highest rate at 40% would be high ticket fitted fashion items….I would stick to saying that 60% of returns are due to poor fit and am afraid, I do not agree with the 1999 research that cited the 17% figure.

    The 17% statistic dated tho it may be works in your favor in that it is higher than the 15% of the whole (60% of 25% = 15% returns due to poor fit). I don’t wish to be argumentative but I want to make this clear because I don’t want my readers who can’t afford your technology to throw in the towel before they even launch thinking they are doomed to have 60% returned of what they ship out when actual fit related returns is closer to 15%-25%. Zappos, which practically begs customers to return stuff, only gets 25% back. But that’s beside the point. For the sake of argument, let’s leave everyone with the impression that 60% of what they sell will come back if they don’t have your fit technology, it’s still a deal breaker to use it. In addition to the points I’ve already made, here’s why:

    I can’t see how the average ecommerce retailer can work it into their schedule as a matter of logistics. I have a friend who sells strictly ecommerce, I don’t know how many skus she has but it’s a lot (thousands). One of her problems in picking up a product line is product photography. When she selects a style at market, she has to beg/borrow the item from the vendor’s booth and run it over to the sample photographer so she can set up her web pages to feature it when it finally comes in -because from the time that product ships, she’s paying for it. She needs to turn it very quickly. Now, according to information on this site (and with which you concurred in your comment there):

    In order to use the technology, Fits.me requires samples of each clothing item (in each size). They then take up to 2,000 photos of each product. They digitalize the whole thing, set up a virtual fitting room, and charge retailers on a CPC basis. The whole thing takes 2-3 weeks of work.

    The 2-3 weeks doesn’t include ship time. A retailer would have to get their product in the door, process it and then pick and pack representative samples to you. Assuming Fit.me had the facilities and infrastructure to process the samples the second they got there, we’re looking at a 3-4 week turn around minimum before the retailer can even load the data on their site. Are you familiar with retail’s mark down schedule? Many retailers start marking things down after they’ve had the item for 4 weeks. Many retailers charge back the vendor for discounts on merchandise that isn’t moving. In short, I can only imagine that manufacturers are going to be very upset about it and it won’t take long for push to come to shove and something will have to give.

    Your own stats make it a difficult sell for retailers (tons of spam comments there, might want to look into it), with estimated 3% of revenue generated by ecommerce. Fwiw, this is close to what my same friend told me, she says that even flagship brands with immaculate sites, only generate 2% of sales online. Based on your case study report of a 3 fold increase in online sales, the best retailers can hope to exact from the process is 6% to 9%. Considering that they’re incurring payables on their inventory for the 3-4 week turnaround for Fit.me to process it and even if their online sales did treble, they would still lose money.

    As an aside:

    but using the robots we can easily, cheapily, and en masse, reverse engineer these fit types.

    It doesn’t matter whether I agree that Fit.me can “easily, cheapily, and en masse, reverse engineer these fit types” it only matters that manufacturers may fear or suspect you can, meaning they aren’t going to send you anything.

    The deal killer on the whole thing is that somebody somewhere somehow is going to have to eat 4 weeks of stagnant inventory. That is going to take a lot of capital and with times as tight as they are, I don’t know who has it. To throw an extra month into the cycle would mean pushing the whole production schedule into disarray. With ZARA eating everyone’s lunch by leading the industry with a 2 week turnaround from sketch to product on the floor, everyone is trying to find ways to shorten the cycle, not lengthen it.

  18. Heikki says:

    It’s been such an interesting discussion, it’s a shame recent big developments didn’t let me answer sooner.

    We’ve launched the new version of the fitting room – which I invite everyone to critique. It’s accessible here: http://www.hawesandcurtis.com/mens-fashion-shirts-blue-plain-ref_YOPGE001-B40
    (Red “New! Visual Size Guide” link next to size selection buttons).

    Kathleen, your calculations are absolutely correct – 60% of garments sold online are not returned; on average 25% of garments are returned instead. Of those returned, 60% are due to poor fit. Indeed, Fits.me can address only those returns. Is it important? Unquestionably – returns are clothing retailers highest cost factor and reducing returns is the easiest way to impact P&L.

    However, as we all know, sizing scales for clothes aren’t consistent, and that makes shopping on the Internet risky. Remove the risk, and sales increase. Fits.me simply answers the customers’ final question “which size should I place into my shopping cart?”, without this answer the sales suffer. Just imagine a world of brick-and-mortar without fitting rooms.

    Jeff Bezos, CEO of Amazon.com, recently declared “we make it really easy for people to try clothes on,” explaining that they make returning products, after trying them at home, guilt free. Guess, their acquisition of Zappos.com, always welcoming returns, was for the better. Making returns easy increases sales, but is a very costly option for the retailer. It’s better to sell the right size in the first place (oh, the customers will like it too).

    Today, apparel online sales remain only 9% of total apparel retail sales, but it’s share is estimated to increase to 35% by 2018. Or put another way – one in every four brick-and-mortar clothing shops will close, a trend observed today in the sales of books, and with travel agencies.

    Several issues remain: size consistency of the brand, errors in self-measurement, and timely access to garments.

    Many brands require their suppliers adhere to stringent size specifications. Building the target market takes years, educating the customer base to the sizing is invaluable, and yet the suppliers often fail to deliver size consistency. Saying this, some brands are better at quality control, some not so much. Fits.me is most effective with brands with high sizing quality control – and still delivers benefits, albeit lower, to those with lower consistency. At some point, the benefit becomes so low, there is no justification for the investment though.

    Errors in self-measurement are a problem. As people make errors, they keep receiving clothes that fit wrong. While we are double checking the measurements entered comparing them to some 10’000 3D body scans, they will not be perfect. However, the idea is not to reduce the returns by 100%, but just deliver enough to benefit the retailer the most. 20% reduction in returns, will still increase the online retailer’s profits by 10%, on average.

    Access to samples is the major issue, thus Fits.me focuses on only 4-7 generic fit sample garments. Timeless styles which will remain the same across seasons. The garments are handled once, and turnaround time can be longer, without hurting the business. True, the customers won’t be able to try on everything, but will still get a great idea how this brand fits their body size and type.
    This approach requires that the retailer has even more focus on size consistency, but again, the end result will need not be perfect – we simply need to increase the sales a bit, reduce the returns (and costs) a bit, and the profits will increase a lot.

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