Fashion e-commerce is suffering from an unsustainable returns habit that damages profitability, ruins customer loyalty, upsets shoppers, is wasteful and extremely damaging to the environment. The majority of these returns are reported to be due to 'fit issues'. It's a no-brainer that the industry needs to find a way to send out clothing that can be relied upon to fit its consumers.
One flank of the battle is for the fashion industry to ensure that the apparel being manufactured is 'fit' for purpose. To do so, it's necessary to understand exactly what clothing sizing and gradings should be produced in order to reflect society and satisfy demand. This will entail a study of one of the most complex entities in the universe: the human consumer, both body and brain. Due to the considerable variability of the population, it is going to result in a much broader range of sizing offers than has been produced up to this point.
The battle's other flank involves tech companies developing the tools that solve the myriad technical issues involved in targeting customers with suitably sized and graded garments, a task made more difficult when involving the more comprehensive range of apparel that will be on offer. For this to be achieved, it's necessary not only to match the level of population metrics expertise of their fashion colleagues, but also to acquire their thorough technical knowledge about all garments being retailed – the matrix of measurements, fabric characteristics, relevant construction specs, usage information and designer preferences.
When it comes to fit, the most challenging sector of fashion e-commerce is plus-size womenswear, which is what I will be addressing in this post. Here, the rates of return can be swingeing: much higher even than in 'mainstream' fashion.
The legacy of plus-size fashion's sizing (and the root cause of its inflated fit problem) is that the grading has been 'extrapolated up' from 'mainstream' sized women, where historically, sizing research tended to originate. The idea that curve women are simply larger versions of smaller women may be true to a certain extent, but this is far too reductive: these larger consumers have much more exaggerated body shapes than their smaller equivalents, so, where they have been graded on a false premise of conformity, it's all too easy for garments to completely miss the essential fit points. It would actually be more informative to create a range of diverse cuts based on the physiques of larger women, and shrink these down to their smaller counterparts, who would, in all likelihood, be delighted with the subsequent advances in the fit of their garments.
With the growth in the proportion of fuller sized individuals in the population, both these considerations are fading away: the younger generation no longer balks at seeing brand ambassadors who vary from the traditional models' slender bodyshape, whilst it has come more widely accepted that any shortfall in the spend associated with plus-size women is caused primarily by the poorer offer available to them – which actually represents an opportunity for forward-looking companies.
Now that these reservations are being removed, in order to develop this sector to its full potential, the industry will need to reduce fashion returns significantly, necessitating a specific and comprehensive study of female bodies – from the smallest to the largest – in the kind of depth that has never been achieved or attempted before.
There are two general methods of collecting consumer body metrics: those undertaken by professionals, and consumers' self-reporting. Some enquiries have involved experts who have reached out into the population to weigh, measure, scan, take surveys and live-test volunteers. In others, subjects have been asked to either measure themselves, fill out surveys – or allow their bodies to be scanned in some way. We already know that far fewer plus-size women are willing to participate in such studies, yet we are relying on this work because we will not gain a complete understanding of the customer base without it. Is there a particular group of larger women that is more likely to step forward to provide data? Is this going to have an effect on the quality of the information collected?
When designing anything for larger people (be it tech or clothing), it is advisable to think about people holistically, and consider, not just their physiques, but also their preferences, personalities, emotions, experiences and thinking. This is particularly relevant to the prickly subject of how to go about finding a realistic plus-size sample of the population to study. Many larger people (with good reason) are resistant to having their bodies categorised, scanned, analysed, measured or observed. Putting aside the differences brought about by the vagaries of personality types (which varies across all women of every size and body shape), there are particular reasons why the body confidence of certain groups of larger women is more resilient than others.
A clue can be seen when observing the shapes of larger women who are happy to exhibit themselves, and compare them to the rest of the population (who largely don't). 'Curve' fashion models are women who make a living out of the fact that they (and society) find their bodies aesthetically pleasing, and these women usually tend to have certain features in common. They are young, with a balanced physique, tall with smooth lines, and usually have either 'perfectly proportioned' or 'hourglass' body shapes. They usually tend to share a European physical type. These women are not at all representative of the plus-size population as a whole.
Larger women come in a range of highly distinct body shapes, the rarest types being the 'perfectly proportioned' and 'hourglass'. This should come as no surprise to anyone: we don't really expect models to represent an 'average' woman. What may come as a shock to the uninitiated is how resistant most plus-size women (who do not share this 'aspirational' shape: indeed, they vary from it considerably) are to being accurately measured. When calling on the population to volunteer body metrics, it is necessary to be extremely careful not to end-up with a highly self-selected, un-representational sample.
If this happens, the industry will be creating a fashion inventory – and a set of fit tools – for a largely imaginary consumer base. Leaving it in exactly the same highly unsatisfactory situation as it is now, in fact.
The battle's other flank involves tech companies developing the tools that solve the myriad technical issues involved in targeting customers with suitably sized and graded garments, a task made more difficult when involving the more comprehensive range of apparel that will be on offer. For this to be achieved, it's necessary not only to match the level of population metrics expertise of their fashion colleagues, but also to acquire their thorough technical knowledge about all garments being retailed – the matrix of measurements, fabric characteristics, relevant construction specs, usage information and designer preferences.
When it comes to fit, the most challenging sector of fashion e-commerce is plus-size womenswear, which is what I will be addressing in this post. Here, the rates of return can be swingeing: much higher even than in 'mainstream' fashion.
The legacy of plus-size fashion's sizing (and the root cause of its inflated fit problem) is that the grading has been 'extrapolated up' from 'mainstream' sized women, where historically, sizing research tended to originate. The idea that curve women are simply larger versions of smaller women may be true to a certain extent, but this is far too reductive: these larger consumers have much more exaggerated body shapes than their smaller equivalents, so, where they have been graded on a false premise of conformity, it's all too easy for garments to completely miss the essential fit points. It would actually be more informative to create a range of diverse cuts based on the physiques of larger women, and shrink these down to their smaller counterparts, who would, in all likelihood, be delighted with the subsequent advances in the fit of their garments.
Historically, the plus cohort has been underserved by the clothing industry, of which this lack of specific research is an example. It was long assumed that larger people are not as valuable to fashion commerce as their 'mainstream' counterparts, partly as they have traditionally averaged a lower spend, but also because their association with a brand was considered negatively. Putting it bluntly, many companies did not like the aesthetics associated with larger people.
With the growth in the proportion of fuller sized individuals in the population, both these considerations are fading away: the younger generation no longer balks at seeing brand ambassadors who vary from the traditional models' slender bodyshape, whilst it has come more widely accepted that any shortfall in the spend associated with plus-size women is caused primarily by the poorer offer available to them – which actually represents an opportunity for forward-looking companies.
Now that these reservations are being removed, in order to develop this sector to its full potential, the industry will need to reduce fashion returns significantly, necessitating a specific and comprehensive study of female bodies – from the smallest to the largest – in the kind of depth that has never been achieved or attempted before.
There are two general methods of collecting consumer body metrics: those undertaken by professionals, and consumers' self-reporting. Some enquiries have involved experts who have reached out into the population to weigh, measure, scan, take surveys and live-test volunteers. In others, subjects have been asked to either measure themselves, fill out surveys – or allow their bodies to be scanned in some way. We already know that far fewer plus-size women are willing to participate in such studies, yet we are relying on this work because we will not gain a complete understanding of the customer base without it. Is there a particular group of larger women that is more likely to step forward to provide data? Is this going to have an effect on the quality of the information collected?
When designing anything for larger people (be it tech or clothing), it is advisable to think about people holistically, and consider, not just their physiques, but also their preferences, personalities, emotions, experiences and thinking. This is particularly relevant to the prickly subject of how to go about finding a realistic plus-size sample of the population to study. Many larger people (with good reason) are resistant to having their bodies categorised, scanned, analysed, measured or observed. Putting aside the differences brought about by the vagaries of personality types (which varies across all women of every size and body shape), there are particular reasons why the body confidence of certain groups of larger women is more resilient than others.
A clue can be seen when observing the shapes of larger women who are happy to exhibit themselves, and compare them to the rest of the population (who largely don't). 'Curve' fashion models are women who make a living out of the fact that they (and society) find their bodies aesthetically pleasing, and these women usually tend to have certain features in common. They are young, with a balanced physique, tall with smooth lines, and usually have either 'perfectly proportioned' or 'hourglass' body shapes. They usually tend to share a European physical type. These women are not at all representative of the plus-size population as a whole.
Larger women come in a range of highly distinct body shapes, the rarest types being the 'perfectly proportioned' and 'hourglass'. This should come as no surprise to anyone: we don't really expect models to represent an 'average' woman. What may come as a shock to the uninitiated is how resistant most plus-size women (who do not share this 'aspirational' shape: indeed, they vary from it considerably) are to being accurately measured. When calling on the population to volunteer body metrics, it is necessary to be extremely careful not to end-up with a highly self-selected, un-representational sample.
It could be that a survey of plus-size consumers finds that 90% of them have hourglass or well-proportioned body shapes, when in fact, only 10% of the general population shares this profile.
If this happens, the industry will be creating a fashion inventory – and a set of fit tools – for a largely imaginary consumer base. Leaving it in exactly the same highly unsatisfactory situation as it is now, in fact.
There is evidence, possibly because they vary from the ideal to a more exaggerated degree than their smaller equivalents, that those who are not 'conventionally attractive' or 'balanced', physically, are far less likely to come forward to be tested by a professional, nor can they be expected to enter correct measurements into any fit system, even in the privacy of their own homes. They may be slow to volunteer to be scanned, and extremely reluctant to want to know their own metrics. They are likely to be very concerned about privacy, and many of them will not even possess the tools (a tape measure, or a weighing machine) with which to gather their data, choosing to enter invented measurements if pushed.
If developers are not careful, this is a situation that may be carried forward into the new generation of e-commerce retail fit tools and scanning devices, causing a diminution of effectiveness.
It's not all doom and gloom, however. Forewarned is forearmed, and, with anticipation of these issues, strategies can – and will – be put in place to collect an accurate, representative sample of fashion consumers, and the development of effective fit tools. In order to do this, it is necessary to abandon the wishful thinking, the 'common sense' (that is not backed-up by empirical knowledge), the prejudice, myths, or the incorrect extrapolation that has plagued the plus-size fashion sector for too long.
Most of all, we should see the end to imaginary plus-size, standardised female consumers, and replace them with the rich diversity of real women.
If developers are not careful, this is a situation that may be carried forward into the new generation of e-commerce retail fit tools and scanning devices, causing a diminution of effectiveness.
It's not all doom and gloom, however. Forewarned is forearmed, and, with anticipation of these issues, strategies can – and will – be put in place to collect an accurate, representative sample of fashion consumers, and the development of effective fit tools. In order to do this, it is necessary to abandon the wishful thinking, the 'common sense' (that is not backed-up by empirical knowledge), the prejudice, myths, or the incorrect extrapolation that has plagued the plus-size fashion sector for too long.
Most of all, we should see the end to imaginary plus-size, standardised female consumers, and replace them with the rich diversity of real women.
Apparel fit and inclusivity
With consumer apparel purchasing increasingly moving online, the subject of apparel fit is at the heart of fashion e-commerce. In this article, four industry insiders come together to merge their differing viewpoints:- Mark Charlton – Fit & sizing thought leader/strategist - https://www.linkedin.com/in/mark-charlton-fit-leader/
- Jessica Couch – Fit tech consultant – consumer tech product manager – fit tech expert strategist – body positivity champion #womenintech – https://www.linkedin.com/in/jessicavcouch/
- Richard Irons– Lead Engineer at Rakuten Fits Me – https://www.linkedin.com/in/richard-irons/
- Emma Hayes – Plus-size womenswear sizing and fit consultant and expert – linkedin.com/in/emma-hayes-3a58553b
Mark Chalton:
'Diversity inclusion' is a term used frequently by corporations intending to ensure everyone has a voice and that there is equal representation of gender, race, religion and other human variations. Equally important is diversity of thought.
So how does this concept relate to the fit of apparel?
It's our opinion that most of these advances are instigated and developed within the somewhat rarefied environment of the tech industry – employing one very specific way of thinking. We note – not as a criticism, but as an observation – that there is an opportunity to redress any imbalance of reasoning by introducing some art into the science.
This observation is not a novel one: for example, it is supported in principle by The Medici Effect (Harvard Business School Press, 2004), which explores why the most powerful innovation happens at the intersection where ideas and concepts from diverse industries and disciplines collide.
Apparel fit is part art/emotion and part science/tech
Think about the last time you purchased a garment that fitted amazingly... how did it make you feel? Apparel fit speaks to, and stimulates, the senses. It creates an emotional connection greater than the sum of its parts: much more than mere body dimensions and garment measurements.
So what's raising the age-old problem of apparel fit among the tech solutionists?
E-commerce apparel return rates are eroding brands' and retailers' margins and profitability. As e-commerce continues to grow, this erosion can no longer be sustained... or masked.
But as a consumer, what do I care? If I don't know what size I am, know for certain that I will like a certain product, or that it will suit me, I have the option to order it anyway – perhaps in multiple sizes – hoping to figure out for myself whether it will work.
We all know that so-called 'free shipping' and 'free returns' are, of course, nothing of the kind. It's these delivery costs, coupled with the task of processing returned products back into inventory, and attempting to balance stocks when over half of demand is returned, that are causing margin erosion and higher prices to the consumer.
Reasons for high returns
Apparel e-commerce return rates on average hover around the 50% mark Р70% of which are attributed to poor fit. It's a clich̩, but for such a tiny word, 'fit' is a very complex process!
To put it in a nutshell, 'fit' is where individual consumers' body measurements meet brands' sizing and garment specifications; designers' fit ideas meet consumers' fit preferences; real-life material properties meet consumers' fabric expectations; and designers' styling decisions meet the pace at which consumers are willing to adopt trends.
Emma Hayes:
Many of us are aware that in future we will be able to take 3D scans of ourselves from our mobile phones or similar devices. These will generate accurate avatars of our bodies, complete with all our measurements, upon which we will be able to virtually 'try on' potential purchases – checking our images on-screen in three dimensions for how good the fit is, and whether the style suits us.
At the time of writing, all over the world, many apps, devices and methods are being developed that are advancing rapidly towards this dream. For example, there is an app on which you can see a three-dimensional avatar of your body – complete with measurements – after simply taking front and side view photographs on your phone. Another app allows you to upload pictures, and your virtual-reality self will then try on the clothing of your choice – draping naturalistically. There is a clever hand-held device that takes your measurements by scanning you. There are even smart body suits and scanning pods, which offer the promise of the gold standard of human measurement: a perfectly accurate rendition of your entire body in three dimensions. These all exist today at various levels of development.
Such devices are exciting and headline-grabbing, but it's unlikely that most of the companies selling us apparel online will opt for them quite yet – partly for technical reasons, but also because they need to be integrated into the systems currently employed in the fashion industry. In the early stages, retail companies will need to 'grow out' their operation to merge with the technology – and many changes will be required.
Fit tools are clever online algorithms that work out which sizes of apparel need to be ordered, based on 'inputs' – and it is these tools that are making the big inroads right now. Inputs are various pieces of customer information – weight, height, age, perhaps body measurements, ordering/returns history, and body shape – which the consumer loads into the tool. In the near future these will also include personal preferences. A vital ingredient of these tools is profound apparel knowledge, allowing them to match the consumer with the optimum garment.
Even at this early stage, this tech is proving to be effective – the best tools boasting a considerable reduction in the number of product returns. They also have the advantage that they are already doing a lot of the heavy lifting required for the digital transformation of the fashion industry. This is what is building the infrastructure that will plug into all the extra data that's collected.
The human angle
However, like all new technologies there are going to be issues surrounding adoption by the public. Predictably, the tech people may think that the problems are all centred on the technology, but there are considerable social, psychological and emotional difficulties to overcome. As consumers, we have to learn how to travel around this new technology.
Whatever tools we use, we are asked to take some time gathering – and inputting – information. But there are problems with asking people to do this, and they fall into two categories...
The measurement problem
Studies show that our measurements are in a state of constant flux, so measuring will not be a one-off activity. We are being asked to continually monitor our measurements and weight – possibly on a monthly basis – regardless of whether we use a tape measure or scanning device.
There are confidentiality issues to think about. If we are not going to have to keep repeating ourselves with every company we buy from, we will have to develop methods whereby our information can be shared between various organisations.
Our experience is that people only substantially change their behaviour and attitudes when there is something in it for them, and that something often has to be more important to them than a new pair of jeans – even if they fit beautifully.
The phrase 'conform to new habits' fills consumer experts with a mixture of dread and concern. Can we consumers really be expected to be 'educated' into new habits? In our leisure time (and shopping is supposed to be that) most of us want to undertake enjoyable activities with an instant reward, rather than toiling through worthy chores in the hope that something better will come along later.
We need to create usable, enjoyable tech that will draw everyone in from the inception; ideally, fun tech that we don't even notice we are using.
The revelation problem
The second problem is revelation. Many people don't know, don't want to know, don't believe and/or would never tell you their accurate measurements.
We need tech that is 'unconscious': having given our permission for the data to be collected, we should have the right not to have to have any interface with our body metrics unless we choose to do so.
Jessica Couch:
The future of fit technology
Fit is becoming a buzzword and everyone has an answer to the online returns problem, but the best solutions have two qualities:
1. Ease of use – How simple and convenient the solution is: mobile phones vs. specialist devices for example?
2. Ease of integration – How easy it is for brands to integrate the technology into their current systems?
Neither do the best technologies try to do everything. Instead they connect to existing technologies and enhance outcomes.
Many smaller brands find it difficult to integrate fit technology because their current 'solutions' are unable to connect to other solutions, and buying an entire suite of IT products is not an affordable option.
Expensive, rigid technologies are out. The best technologies are those which integrate easily with existing platforms and create more efficiency. Because tech has not existed in fashion in the past, many departments are siloed and are not properly integrated for it. Great technology companies have to take this fact into consideration before they can succeed.
How fit is your competitive advantage?
Fit and fit technology are customer experience tools – A lot of brands believe that implementing more lenient return policies can somehow impact the quantity of returns. In our view this is similar to putting a Band-Aid® on a gash... it simply doesn't treat the real issue of customer expectation.
According to an article on online apparel returns myths:
By the time a customer has had to return an item, you have lost them for future opportunities. Customer expectations must be met and returns avoided. This can be done through building confidence with consumers, whether in-store or online, and helping them understand what to expect in regard to fit.
Fit and fit technology are loss management tools – Implementing fit technology helps to increase consumer confidence in products. $62.4 billion worth of apparel and footwear is returned every year due to incorrect fit. That works out to about 57% of footwear and 64% of apparel purchases, according to a recent Footwear News study. The same study found that if fit were not a concern, 51% of respondents would purchase footwear more often, both online and in-store, while 58% would purchase clothing more frequently.
Excellent communication around fit is important because it helps build confidence with the shopper – increasing sales and generating fewer returns. Implementing fit technology tools that create directive shopping experiences and manage expectations can help to reduce the amount of unsold inventory.
Fit can help reduce fashion's carbon footprint – A recent op-ed piece published in The Business of Fashion revealed that dead inventory (unsold clothing) costs the US retail industry $50 billion a year. Although brands may be able to absorb some of these costs through write-offs on the balance sheet, the environment (through landfills, toxin pollution, etc.) cannot.
Newsweek published an article stating that Americans alone produced 15.1 million tons of textile waste in 2013 and around 85% of that ended-up in landfill, according to the Environmental Protection Agency.
Fit technology allows brands to create better-fitting clothing for shoppers, and helps to match them to their products – so clothing is not created unnecessarily, quickly ending up in landfill. Although changing the shopping habits of consumers is a difficult task, brands have to take more responsibility for their impact on the environment. Implementing fit technology can help to fix fashion's misaligned supply and demand issues.
Fit is inclusive: more people shopping equals more money – In a survey conducted by Fung Global Research, some 72% of respondents did not believe that fashion designers create their designs with the average American woman in mind.
Approximately 78% of people would be willing to spend more money on clothing if more designers offered plus-size options. Some 68% are interested in participating in fashion trends, but 67% feel that there are not as many fashionable clothing options available in their size as they would like. This isn't just a plus-size issue.
According to a Business Insider report on petite people, over 70 million US women fall into the 'special' size category, and 50% of the population is under 5' 4" tall, but brands' size offerings do not reflect this. In addition to these categories, there are also tall women, big and tall men, petite men, and people with physical handicaps that are also opportunities for brands to target.
Richard Irons:
Fit tool desired output
When thinking about creating a fit tool, firstly it's necessary to think about what is needed from that tool. For instance, whilst producing a custom-made dress, a pattern with all the correct measurements will be required from the outset.
However, in this piece we're not talking about bespoke garments, but clothes that are already manufactured, and are available in a finite number of sizes.
Best size
When shopping in a store for clothes, most consumers who are not sure what size to pick opt to try them on – and when a size doesn't fit correctly they may examine different sizes until either finding a good fit, or deciding that none of the available options is suitable. It's this process that we want to duplicate in a fit tool – essentially the algorithm 'tries on' every available size on a body, selects the best size for that body, or concludes that none of the sizes are any good.
So really what is being asked from a tool is 'best size, if any'.
Ideal garment measurements
In future, if manufacturing processes change so that fit plays a greater part, we may want the tool to provide us with a list of 'ideal' measurements for a garment. This could, for example, be used as input into some sort of electronic manufacturing system that makes every garment to order.
But perhaps this is jumping ahead.
Required inputs
In order to get the best results from a tool it needs consumer information to work with. To return to the analogy of trying clothes on in a shop, there are two things involved: a body and a garment. A tool needs information about both.
Clearly, a fit tool needs the body-in-question's measurements, and the most obvious way of obtaining them would simply be to measure with a tape, the way a tailor would. This is actually the best way to get accurate metrics, if it were a professional who was undertaking the measuring. However, for a customer at home, it's not a great system. Firstly, the subject needs to possess a tape measure, and secondly, they need to be willing to stop in the middle of shopping in order to take measurements.
These issues are problematical in themselves, but worse, the majority of people don't know the correct measuring method, so will ultimately supply inaccurate metrics. And if the data is inaccurate, there's no way the tool can give a good result.
AI method – 'pertinent questions'
An easier and more reliable way to get the information needed is to ask the customer some pertinent questions – age, weight, height – simple information that people already know about themselves. Once it has this information, the tool can use a neural net, armed with a great deal of knowledge that has been previously collected, to deduce that user's measurements surprisingly well. This method is usually significantly more accurate than asking consumers to measure themselves.
Garment info
The information that is required about a garment is a little more complicated. It's not enough to simply know the physical dimensions (although these are necessary), since other considerations, such as how closely the garment is meant to fit at certain points, and how stretchy the material is, must be taken into account.
The easiest place to get this information is from the manufacturer. All the details about the apparel's dimensions, the fabric's 'handle', and the design's 'preferred fit', are known to them, because this information is needed for the manufacture of the garment. However, sometimes the retailer doesn't have a direct relationship with the manufacturer and won't have access to that information.
Without these details, it's necessary to use one of a number of methods. The most accurate would be for a garment technologist to acquire the apparel in each size and undertake accurate measurements, using their expertise, along with product photography to judge the preferred fit. However, with a large number of products, this approach becomes prohibitively expensive. Other available methods include generic size charts, information from similar garments, and artificial-intelligence inference from product descriptions and photography.
Ideal future
Manufacturers who want to make sure that an accurate fit could be calculated for all their products would be best advised to make all the measurements and design information easily and freely accessible.
If this became an industry norm, customers would find obtaining a good fit much easier, and the level of expectation and competition would ultimately cause manufacturers to raise their game with regards to fit.
Checks
To make sure a tool is reliable, developers need to check that the results make sense. There are certain ways to do this.
One simple method is for a specialist to test tools by entering lots of different measurements and then see if the recommended size 'looks right'. Of course, this method can be subjective and inaccurate, as, for example, it depends on the manufacturer's idea of 'size 10' broadly agreeing with the technologist's.
More accurate testing can be done, albeit more expensively, by buying garments in the recommended sizes for many people of different shapes and sizes, and judging the fit when trying them on. Information from this process can then be fed back into the tool to improve its accuracy.
In conclusion... Mark Charlton:
The diversity that exists across the human race meshes with the complexity of each fashion brand's design aims, layered to the multiplicity of fabric properties and fit preferences, both of designers and consumers. These issues create a mind-bogglingly intricate problem of achieving the perfect fit.
But this is only part of the challenge: for example, optimal fit can also differ across POMs (points of measurement). An instance of this would be where stretch jeans would require greater elasticity in some areas than in others, so that there is flexibility on the hips, but a snug fit on the waist: a combination of variable body shape, but also of preference.
We need the vision to collaborate with fit solutions across the entire fashion industry, whilst still competing in this space. A necessary step towards this is to understand that we must solve the issue of apparel fit by rising above simply thinking of it as returns problem. It is far more important than that.
Each week brings fresh potential technical solutions to bear on the current apparel fit problem. This is a Good Thing, as the tech geniuses are recognising fit as an area where technology can offer a significant contribution.
It's our opinion that most of these advances are instigated and developed within the somewhat rarefied environment of the tech industry – employing one very specific way of thinking. We note – not as a criticism, but as an observation – that there is an opportunity to redress any imbalance of reasoning by introducing some art into the science.
This observation is not a novel one: for example, it is supported in principle by The Medici Effect (Harvard Business School Press, 2004), which explores why the most powerful innovation happens at the intersection where ideas and concepts from diverse industries and disciplines collide.
Apparel fit is part art/emotion and part science/tech
Think about the last time you purchased a garment that fitted amazingly... how did it make you feel? Apparel fit speaks to, and stimulates, the senses. It creates an emotional connection greater than the sum of its parts: much more than mere body dimensions and garment measurements.
So what's raising the age-old problem of apparel fit among the tech solutionists?
E-commerce apparel return rates are eroding brands' and retailers' margins and profitability. As e-commerce continues to grow, this erosion can no longer be sustained... or masked.
But as a consumer, what do I care? If I don't know what size I am, know for certain that I will like a certain product, or that it will suit me, I have the option to order it anyway – perhaps in multiple sizes – hoping to figure out for myself whether it will work.
We all know that so-called 'free shipping' and 'free returns' are, of course, nothing of the kind. It's these delivery costs, coupled with the task of processing returned products back into inventory, and attempting to balance stocks when over half of demand is returned, that are causing margin erosion and higher prices to the consumer.
Reasons for high returns
Apparel e-commerce return rates on average hover around the 50% mark Р70% of which are attributed to poor fit. It's a clich̩, but for such a tiny word, 'fit' is a very complex process!
To put it in a nutshell, 'fit' is where individual consumers' body measurements meet brands' sizing and garment specifications; designers' fit ideas meet consumers' fit preferences; real-life material properties meet consumers' fabric expectations; and designers' styling decisions meet the pace at which consumers are willing to adopt trends.
Emma Hayes:
Many of us are aware that in future we will be able to take 3D scans of ourselves from our mobile phones or similar devices. These will generate accurate avatars of our bodies, complete with all our measurements, upon which we will be able to virtually 'try on' potential purchases – checking our images on-screen in three dimensions for how good the fit is, and whether the style suits us.
At the time of writing, all over the world, many apps, devices and methods are being developed that are advancing rapidly towards this dream. For example, there is an app on which you can see a three-dimensional avatar of your body – complete with measurements – after simply taking front and side view photographs on your phone. Another app allows you to upload pictures, and your virtual-reality self will then try on the clothing of your choice – draping naturalistically. There is a clever hand-held device that takes your measurements by scanning you. There are even smart body suits and scanning pods, which offer the promise of the gold standard of human measurement: a perfectly accurate rendition of your entire body in three dimensions. These all exist today at various levels of development.
Such devices are exciting and headline-grabbing, but it's unlikely that most of the companies selling us apparel online will opt for them quite yet – partly for technical reasons, but also because they need to be integrated into the systems currently employed in the fashion industry. In the early stages, retail companies will need to 'grow out' their operation to merge with the technology – and many changes will be required.
Fit tools are clever online algorithms that work out which sizes of apparel need to be ordered, based on 'inputs' – and it is these tools that are making the big inroads right now. Inputs are various pieces of customer information – weight, height, age, perhaps body measurements, ordering/returns history, and body shape – which the consumer loads into the tool. In the near future these will also include personal preferences. A vital ingredient of these tools is profound apparel knowledge, allowing them to match the consumer with the optimum garment.
Even at this early stage, this tech is proving to be effective – the best tools boasting a considerable reduction in the number of product returns. They also have the advantage that they are already doing a lot of the heavy lifting required for the digital transformation of the fashion industry. This is what is building the infrastructure that will plug into all the extra data that's collected.
The human angle
However, like all new technologies there are going to be issues surrounding adoption by the public. Predictably, the tech people may think that the problems are all centred on the technology, but there are considerable social, psychological and emotional difficulties to overcome. As consumers, we have to learn how to travel around this new technology.
Whatever tools we use, we are asked to take some time gathering – and inputting – information. But there are problems with asking people to do this, and they fall into two categories...
The measurement problem
Studies show that our measurements are in a state of constant flux, so measuring will not be a one-off activity. We are being asked to continually monitor our measurements and weight – possibly on a monthly basis – regardless of whether we use a tape measure or scanning device.
There are confidentiality issues to think about. If we are not going to have to keep repeating ourselves with every company we buy from, we will have to develop methods whereby our information can be shared between various organisations.
Our experience is that people only substantially change their behaviour and attitudes when there is something in it for them, and that something often has to be more important to them than a new pair of jeans – even if they fit beautifully.
The phrase 'conform to new habits' fills consumer experts with a mixture of dread and concern. Can we consumers really be expected to be 'educated' into new habits? In our leisure time (and shopping is supposed to be that) most of us want to undertake enjoyable activities with an instant reward, rather than toiling through worthy chores in the hope that something better will come along later.
We need to create usable, enjoyable tech that will draw everyone in from the inception; ideally, fun tech that we don't even notice we are using.
The revelation problem
The second problem is revelation. Many people don't know, don't want to know, don't believe and/or would never tell you their accurate measurements.
We need tech that is 'unconscious': having given our permission for the data to be collected, we should have the right not to have to have any interface with our body metrics unless we choose to do so.
Jessica Couch:
The future of fit technology
Fit is becoming a buzzword and everyone has an answer to the online returns problem, but the best solutions have two qualities:
1. Ease of use – How simple and convenient the solution is: mobile phones vs. specialist devices for example?
2. Ease of integration – How easy it is for brands to integrate the technology into their current systems?
The best technologies do not try to train users to have habits that are not simple or natural. They allow end-users easily to add technology into their everyday lives. Accuracy is key, and the less effort required the better.
Neither do the best technologies try to do everything. Instead they connect to existing technologies and enhance outcomes.
Many smaller brands find it difficult to integrate fit technology because their current 'solutions' are unable to connect to other solutions, and buying an entire suite of IT products is not an affordable option.
Expensive, rigid technologies are out. The best technologies are those which integrate easily with existing platforms and create more efficiency. Because tech has not existed in fashion in the past, many departments are siloed and are not properly integrated for it. Great technology companies have to take this fact into consideration before they can succeed.
How fit is your competitive advantage?
Fit and fit technology are customer experience tools – A lot of brands believe that implementing more lenient return policies can somehow impact the quantity of returns. In our view this is similar to putting a Band-Aid® on a gash... it simply doesn't treat the real issue of customer expectation.
According to an article on online apparel returns myths:
- Most returns are made by one-time buyers.
- Good returns policies do not affect sales.
- Most shoppers don't think about returns before buying.
- Most people are not concerned with free return shipping.
- Bad returns policies don't affect sales, and a returns policy won't impact future sales.
By the time a customer has had to return an item, you have lost them for future opportunities. Customer expectations must be met and returns avoided. This can be done through building confidence with consumers, whether in-store or online, and helping them understand what to expect in regard to fit.
Fit and fit technology are loss management tools – Implementing fit technology helps to increase consumer confidence in products. $62.4 billion worth of apparel and footwear is returned every year due to incorrect fit. That works out to about 57% of footwear and 64% of apparel purchases, according to a recent Footwear News study. The same study found that if fit were not a concern, 51% of respondents would purchase footwear more often, both online and in-store, while 58% would purchase clothing more frequently.
Excellent communication around fit is important because it helps build confidence with the shopper – increasing sales and generating fewer returns. Implementing fit technology tools that create directive shopping experiences and manage expectations can help to reduce the amount of unsold inventory.
Fit can help reduce fashion's carbon footprint – A recent op-ed piece published in The Business of Fashion revealed that dead inventory (unsold clothing) costs the US retail industry $50 billion a year. Although brands may be able to absorb some of these costs through write-offs on the balance sheet, the environment (through landfills, toxin pollution, etc.) cannot.
Newsweek published an article stating that Americans alone produced 15.1 million tons of textile waste in 2013 and around 85% of that ended-up in landfill, according to the Environmental Protection Agency.
Fit technology allows brands to create better-fitting clothing for shoppers, and helps to match them to their products – so clothing is not created unnecessarily, quickly ending up in landfill. Although changing the shopping habits of consumers is a difficult task, brands have to take more responsibility for their impact on the environment. Implementing fit technology can help to fix fashion's misaligned supply and demand issues.
Fit is inclusive: more people shopping equals more money – In a survey conducted by Fung Global Research, some 72% of respondents did not believe that fashion designers create their designs with the average American woman in mind.
Approximately 78% of people would be willing to spend more money on clothing if more designers offered plus-size options. Some 68% are interested in participating in fashion trends, but 67% feel that there are not as many fashionable clothing options available in their size as they would like. This isn't just a plus-size issue.
According to a Business Insider report on petite people, over 70 million US women fall into the 'special' size category, and 50% of the population is under 5' 4" tall, but brands' size offerings do not reflect this. In addition to these categories, there are also tall women, big and tall men, petite men, and people with physical handicaps that are also opportunities for brands to target.
Richard Irons:
Fit tool desired output
When thinking about creating a fit tool, firstly it's necessary to think about what is needed from that tool. For instance, whilst producing a custom-made dress, a pattern with all the correct measurements will be required from the outset.
However, in this piece we're not talking about bespoke garments, but clothes that are already manufactured, and are available in a finite number of sizes.
Best size
When shopping in a store for clothes, most consumers who are not sure what size to pick opt to try them on – and when a size doesn't fit correctly they may examine different sizes until either finding a good fit, or deciding that none of the available options is suitable. It's this process that we want to duplicate in a fit tool – essentially the algorithm 'tries on' every available size on a body, selects the best size for that body, or concludes that none of the sizes are any good.
So really what is being asked from a tool is 'best size, if any'.
Ideal garment measurements
In future, if manufacturing processes change so that fit plays a greater part, we may want the tool to provide us with a list of 'ideal' measurements for a garment. This could, for example, be used as input into some sort of electronic manufacturing system that makes every garment to order.
But perhaps this is jumping ahead.
Required inputs
In order to get the best results from a tool it needs consumer information to work with. To return to the analogy of trying clothes on in a shop, there are two things involved: a body and a garment. A tool needs information about both.
Clearly, a fit tool needs the body-in-question's measurements, and the most obvious way of obtaining them would simply be to measure with a tape, the way a tailor would. This is actually the best way to get accurate metrics, if it were a professional who was undertaking the measuring. However, for a customer at home, it's not a great system. Firstly, the subject needs to possess a tape measure, and secondly, they need to be willing to stop in the middle of shopping in order to take measurements.
These issues are problematical in themselves, but worse, the majority of people don't know the correct measuring method, so will ultimately supply inaccurate metrics. And if the data is inaccurate, there's no way the tool can give a good result.
AI method – 'pertinent questions'
An easier and more reliable way to get the information needed is to ask the customer some pertinent questions – age, weight, height – simple information that people already know about themselves. Once it has this information, the tool can use a neural net, armed with a great deal of knowledge that has been previously collected, to deduce that user's measurements surprisingly well. This method is usually significantly more accurate than asking consumers to measure themselves.
Garment info
The information that is required about a garment is a little more complicated. It's not enough to simply know the physical dimensions (although these are necessary), since other considerations, such as how closely the garment is meant to fit at certain points, and how stretchy the material is, must be taken into account.
The easiest place to get this information is from the manufacturer. All the details about the apparel's dimensions, the fabric's 'handle', and the design's 'preferred fit', are known to them, because this information is needed for the manufacture of the garment. However, sometimes the retailer doesn't have a direct relationship with the manufacturer and won't have access to that information.
Without these details, it's necessary to use one of a number of methods. The most accurate would be for a garment technologist to acquire the apparel in each size and undertake accurate measurements, using their expertise, along with product photography to judge the preferred fit. However, with a large number of products, this approach becomes prohibitively expensive. Other available methods include generic size charts, information from similar garments, and artificial-intelligence inference from product descriptions and photography.
Ideal future
Manufacturers who want to make sure that an accurate fit could be calculated for all their products would be best advised to make all the measurements and design information easily and freely accessible.
If this became an industry norm, customers would find obtaining a good fit much easier, and the level of expectation and competition would ultimately cause manufacturers to raise their game with regards to fit.
Checks
To make sure a tool is reliable, developers need to check that the results make sense. There are certain ways to do this.
One simple method is for a specialist to test tools by entering lots of different measurements and then see if the recommended size 'looks right'. Of course, this method can be subjective and inaccurate, as, for example, it depends on the manufacturer's idea of 'size 10' broadly agreeing with the technologist's.
More accurate testing can be done, albeit more expensively, by buying garments in the recommended sizes for many people of different shapes and sizes, and judging the fit when trying them on. Information from this process can then be fed back into the tool to improve its accuracy.
In conclusion... Mark Charlton:
The diversity that exists across the human race meshes with the complexity of each fashion brand's design aims, layered to the multiplicity of fabric properties and fit preferences, both of designers and consumers. These issues create a mind-bogglingly intricate problem of achieving the perfect fit.
But this is only part of the challenge: for example, optimal fit can also differ across POMs (points of measurement). An instance of this would be where stretch jeans would require greater elasticity in some areas than in others, so that there is flexibility on the hips, but a snug fit on the waist: a combination of variable body shape, but also of preference.
No individual company, however great their resources, can solve the fit question in isolation: one brand can hope (at best) to supply a solution for their own apparel – which only represents a fraction of their consumer's overall fit needs.
We need the vision to collaborate with fit solutions across the entire fashion industry, whilst still competing in this space. A necessary step towards this is to understand that we must solve the issue of apparel fit by rising above simply thinking of it as returns problem. It is far more important than that.
Apparel fit: big fashion and the glass wall
Large companies are not all the same. Take the big fashion retail brands, for example. It might be expected that there would be a high degree of industry-wide conformity, given that the overall activities of different companies are basically the same. Large e-commerce apparel businesses all either buy or manufacture clothing, which they then market to the public – but nevertheless there are wide areas upon which they diverge. Fast/low price-point fashion contrasts widely with classic/luxury wear, for example, and there are an infinite number of other vivid combinations of apparel genres that combine to create a massively varied, vibrant and exciting industry.All this 'difference' adds up to a sector with a great many players who revel in their diverse approaches – and not just about what they stock and how it is made. Because the fashion industry's very beauty lies in its originality and variation, some brands have created a culture which makes a fetish of singularity, that, when taken too far, can be detrimental to the bottom line.
Take my specialist subject, fit, for example. I'm not talking about the characteristic differences in grading between brands – I'm speaking about the process of fitting each brand's own customer base. This is something that should be of ubiquitous interest, due to the truly horrendous returns problem that is slicing away at margins throughout the fashion industry. Product returns can run at between 20–40% for mainstream-sized womenswear, rising to a whopping 70% for plus-size female apparel. Disappointed customers report that most of these returns are 'fit-related'.
The implications of the online fashion industry's returns problem now are truly horrendous: the ripples of cost from a single garment return spread out like a toxic spill in every direction – from credit card charges, to picking, packaging, consignment, carriage, loss of customer loyalty, disruption to the inventory and tainted and/or wasted stock. It's clear that this is an expensive, detrimental, ecologically damaging process that should be avoided if at all possible. Yet, with the growth of the proportion of consumers who choose to buy online (and of those who are plus-size) it is growing year-on-year.
In the pre-internet era most 'mail order' fashion retail companies simply offered their consumers a size chart. A customer was expected to take a measuring tape, expertly deploy it on a series of areas of the body, and then check their measurements against the chart, so as to judge for herself which size she should order. This was the legacy system of the fashion industry at the beginning of the online shopping era.
I've worked with a number of companies (and looked at many others) that are developing the new generation of sophisticated fit tools, which generally perform two functions. They identify the sizing and shape of individuals with better accuracy, and they use that information both to assist consumers to obtain the correctly fitting apparel, and to feed back large quantities of precious customer metric data to brands, allowing them to create stock better suited to demand.
All of the IT e-commerce fit tools that I have seen have offered a significant reduction in returns. They are extremely cost-effective, so with the plethora of IT fit solutions for fashion e-commerce now emerging, we should be seeing a stampede from the large retailers... each busily transforming their systems to stem the tide of unnecessary returns. We should also be witnessing the tech companies seeing their client lists growing exponentially.
However, as with everything in fashion, the picture is mystifyingly varied, and there are a wide range of approaches in play. Finding out how each apparel 'e-tailer' addresses the subject of fit is the easiest thing in the world. Simply click on a given fashion website and see. Extraordinarily, there is a significant proportion of websites that still employ technology whose principles haven't changed substantially since the middle of the last century – having dragged those old size charts on to their websites. A few have high-end fit tools created by the best minds in the field, and some seem to have produced their own in-house systems. Because the genius of the apparel industry tends to be in fashion, rather than IT, many, if not most of the latter, are lacklustre, crude and basic. So what is going on?
It's easy to see why company officers have to screen those who have access to them. If a director of a major retailer read every email trying to interest her in a new service, she would never have any time to do anything else. If she allowed cold-callers from all those promising her profitable new innovations, she would be driven mad within a day. And if she agreed to meet with everyone who was trying to talk her into an offer she couldn't refuse, she would instantaneously fill her calendar with enough meetings for the remainder of her career. Top company directors get remorselessly pestered, and they have to build a carapace around their world, so it's easy to understand why they are not easily accessible to the men and women in shiny suits trying to sell sparkly new technological ideas to them.
When I talk to companies who create IT fit tools, the most pressing subject on their mind is recruiting new clients – particularly among the bigger brands. It seems that even the best of them are finding that they cannot break through the plate-glass windows that protect the big fashion decision-makers from unwanted contact. The chatter is that those businesses that don't have fit tools have failed to get them because they don't really know how effective they are. Trapped inside their glass towers, they indulge in a counsel of despair: apparently returns (like death and taxes) are just a 'fact of e-commerce life', and nothing can be done to avoid them. Put simply, there is disconnect between many big fashion brands and the IT industry. Those trying to sell fit tools are having trouble getting a foot in the door.
This situation is a miserable one: on one hand we have fashion retail, where many large companies are suffering from a horrendous returns problem, and on the other we have a tech industry that has already achieved substantial advances, but which needs enough clients to make every further solution financially viable. It's a chicken and egg situation: the fit tools will ultimately prove to be the instigator of transformation in the fashion industry, yet they need to be taken-up in greater numbers in order to facilitate progress. The money people who are backing the IT start-ups in this field are getting impatient.
Where fashion companies are privately owned any reluctance of the board to bring in outside tech expertise could be argued to be no-one else's business than their own. However, for a publicly quoted fashion brand to neglect to equip its website with a cutting-edge fit tool that is going to substantially improve the bottom line, is a dereliction of duty. To see a major brand with a sizing box in their online store is frankly an embarrassment.
Shareholders could be forgiven if they look on out-dated sizing systems on websites as unacceptable, and evidence of managerial complacency: especially where they are mirrored with a profit-draining returns problem.
Some readers will be impatient with my thesis, asking when all the other benefits from a better sizing system are going to be mentioned. It's true; we can see a slew of advantages for our diverse population – ranging from better social justice to improved levels of happiness. However, I have written about those rewards before, and will do so again. In this post I am focusing on one thing: money.
All fashion e-commerce decision-makers should be looking to acquire the very best fit tools available as a matter of urgency. This should become the new industry-wide norm. Shareholders should be clamouring for it, and business analysts should be investigating where and why it is not happening. It will not be costly: rather, the whole point of them is that they will save a lot of money. Directors who do not have the expertise, time or energy to undertake the search for an appropriate IT fit solution for their business can, for now, outsource the search to independent consultants. In the future, they will be expected to own the brief for themselves.
There really is nothing to lose and much to gain.
The implications of the online fashion industry's returns problem now are truly horrendous: the ripples of cost from a single garment return spread out like a toxic spill in every direction – from credit card charges, to picking, packaging, consignment, carriage, loss of customer loyalty, disruption to the inventory and tainted and/or wasted stock. It's clear that this is an expensive, detrimental, ecologically damaging process that should be avoided if at all possible. Yet, with the growth of the proportion of consumers who choose to buy online (and of those who are plus-size) it is growing year-on-year.
In the pre-internet era most 'mail order' fashion retail companies simply offered their consumers a size chart. A customer was expected to take a measuring tape, expertly deploy it on a series of areas of the body, and then check their measurements against the chart, so as to judge for herself which size she should order. This was the legacy system of the fashion industry at the beginning of the online shopping era.
I could write an entire piece on the failure of this method, beginning with the not unimportant fact that less than 10% of the population have measurements that can in any way be shoehorned into the proportions assumed by these charts. However, as it is not the subject of this article, I shall make just this observation: this system does not work, it has never worked, and it will not work in the future. Indeed, the proof is there for all to see: the continued use of this legacy 'method' (and the thinking behind it) is largely to blame for the high level of returns that we are seeing today.
I've worked with a number of companies (and looked at many others) that are developing the new generation of sophisticated fit tools, which generally perform two functions. They identify the sizing and shape of individuals with better accuracy, and they use that information both to assist consumers to obtain the correctly fitting apparel, and to feed back large quantities of precious customer metric data to brands, allowing them to create stock better suited to demand.
All of the IT e-commerce fit tools that I have seen have offered a significant reduction in returns. They are extremely cost-effective, so with the plethora of IT fit solutions for fashion e-commerce now emerging, we should be seeing a stampede from the large retailers... each busily transforming their systems to stem the tide of unnecessary returns. We should also be witnessing the tech companies seeing their client lists growing exponentially.
However, as with everything in fashion, the picture is mystifyingly varied, and there are a wide range of approaches in play. Finding out how each apparel 'e-tailer' addresses the subject of fit is the easiest thing in the world. Simply click on a given fashion website and see. Extraordinarily, there is a significant proportion of websites that still employ technology whose principles haven't changed substantially since the middle of the last century – having dragged those old size charts on to their websites. A few have high-end fit tools created by the best minds in the field, and some seem to have produced their own in-house systems. Because the genius of the apparel industry tends to be in fashion, rather than IT, many, if not most of the latter, are lacklustre, crude and basic. So what is going on?
It's easy to see why company officers have to screen those who have access to them. If a director of a major retailer read every email trying to interest her in a new service, she would never have any time to do anything else. If she allowed cold-callers from all those promising her profitable new innovations, she would be driven mad within a day. And if she agreed to meet with everyone who was trying to talk her into an offer she couldn't refuse, she would instantaneously fill her calendar with enough meetings for the remainder of her career. Top company directors get remorselessly pestered, and they have to build a carapace around their world, so it's easy to understand why they are not easily accessible to the men and women in shiny suits trying to sell sparkly new technological ideas to them.
When I talk to companies who create IT fit tools, the most pressing subject on their mind is recruiting new clients – particularly among the bigger brands. It seems that even the best of them are finding that they cannot break through the plate-glass windows that protect the big fashion decision-makers from unwanted contact. The chatter is that those businesses that don't have fit tools have failed to get them because they don't really know how effective they are. Trapped inside their glass towers, they indulge in a counsel of despair: apparently returns (like death and taxes) are just a 'fact of e-commerce life', and nothing can be done to avoid them. Put simply, there is disconnect between many big fashion brands and the IT industry. Those trying to sell fit tools are having trouble getting a foot in the door.
This situation is a miserable one: on one hand we have fashion retail, where many large companies are suffering from a horrendous returns problem, and on the other we have a tech industry that has already achieved substantial advances, but which needs enough clients to make every further solution financially viable. It's a chicken and egg situation: the fit tools will ultimately prove to be the instigator of transformation in the fashion industry, yet they need to be taken-up in greater numbers in order to facilitate progress. The money people who are backing the IT start-ups in this field are getting impatient.
Where fashion companies are privately owned any reluctance of the board to bring in outside tech expertise could be argued to be no-one else's business than their own. However, for a publicly quoted fashion brand to neglect to equip its website with a cutting-edge fit tool that is going to substantially improve the bottom line, is a dereliction of duty. To see a major brand with a sizing box in their online store is frankly an embarrassment.
Shareholders could be forgiven if they look on out-dated sizing systems on websites as unacceptable, and evidence of managerial complacency: especially where they are mirrored with a profit-draining returns problem.
Fashion industry best practice should dictate an informed, pro-active and responsible attitude to returns, centred on cutting-edge IT solutions.
Some readers will be impatient with my thesis, asking when all the other benefits from a better sizing system are going to be mentioned. It's true; we can see a slew of advantages for our diverse population – ranging from better social justice to improved levels of happiness. However, I have written about those rewards before, and will do so again. In this post I am focusing on one thing: money.
All fashion e-commerce decision-makers should be looking to acquire the very best fit tools available as a matter of urgency. This should become the new industry-wide norm. Shareholders should be clamouring for it, and business analysts should be investigating where and why it is not happening. It will not be costly: rather, the whole point of them is that they will save a lot of money. Directors who do not have the expertise, time or energy to undertake the search for an appropriate IT fit solution for their business can, for now, outsource the search to independent consultants. In the future, they will be expected to own the brief for themselves.
There really is nothing to lose and much to gain.
The black hole at the heart of plus-size fashion
I learned at school that the all-powerful law of 'supply and demand' meant that where there was consumer desire for something, a market would emerge to satisfy it. Yet, on the surface at least, this law seems to mean nothing in the business in which I have spent most of my professional life... plus-size fashion. To this day, over a half of all women in the US are clothed in dress size 14 or over, yet this sector accounts for less than a fifth of women's apparel sold yearly, and the UK fares no better.Why should this be? Social media is pretty clear that it's all about prejudice. The fashion industry 'hates' bigger people, and refuses to produce exciting enough clothing for them to want to buy. However, nothing happens without a reason – and that particular one simply doesn't hold water.
I'm not going to deal with sizeism. I'm here to talk from a business point of view, and it's clear that, where a product is likely to make money, commerce is only too willing to supply that product. Corporate directors – in any industry – do not choose to lose billions of dollars simply to indulge their own peccadilloes, even supposing they had any.
Let's go back to the pre-internet era, where the problem was already manifested. Back in the days where the consumer visited a bricks-and-mortar store and purchased her fashion after having checked the fit in a changing room, things were already far from peachy in the plus-size market. The level of customer satisfaction, the maturity of the market and the fulfilment of financial potential in this sector have always been extremely poor.
The poison in the bloodstream of the plus-size industry was a fit problem. All women – of every size, from the tiniest to the very largest – enjoy one of a number of diverse body shapes, such as 'hourglass', 'busty', 'pear-shaped', etc. This is because women have a number of differing areas of the body on which they store fat. As we grow larger, women add their excess body mass mainly on to these discrete areas, rather than evenly all over (or just around the middle, like most men). This means that women's differing body shapes become more exaggerated the further up the size range they go. Women of the same overall dress size can have a 20cm or more difference in any number of their measurements, meaning that two women of exactly the same dress size may simply find it impossible to fit into the same clothes. Plus-size women are, therefore, very difficult and complex to fit.
This complexity has created a cascade of negative effects that have always affected this market. Brands tried to create fits that they believed were likely to suit most people (just as they do in the 'straight' size ranges), by crunching the statistics into one 'average' grading. Even in 'mainstream' sizes it doesn't work brilliantly, but in the plus market, it fails because the resulting fit (the 'well-proportioned' body shape) counts for only about 10% of the population.
When plus-size designs requiring 'specific fits' (like tailored workwear suiting, for example) were produced using this formula, they therefore only fitted a small proportion of customers, creating very disappointing sell-throughs. The industry's response of providing 'non-specific' fits – a baggy, stretchy, shapeless offer – meant that although the clothing could actually fit on to their customers, it disappointed and infuriated them, causing them to refuse – as anyone would – to spend big on goods they found uninspiring.
Because the spend was poor, the industry assumed that the plus-size consumer was 'cheap', and reacted with a cut-price offer. The fabric and workmanship became low-cost, which minimised choice in the sector. Instead of having a range of price-points to match the 'straight' brands on the high street, plus-size apparel was relegated to one offer... that of the lowest price.
When brands tried to introduce fashion-forward looks, the fit for this type of apparel, again, needed to be specific, and, worse, the style had to be matched up to the correct body shape in order to look flattering, regardless of fit. When the bewildered consumers weren't physically able to buy into this enhanced design level, the industry concluded that larger women 'simply weren't fashionable'. This again affected the offer, with the choice of styles available to this cohort being limited largely to the predictable, repetitive, banal and mediocre.
At every point, new, good quality, stylish, exciting, fashionable looks for the plus-size market hit a brick wall... and it was always the same wall: fit. Unlike the sages of social media, I don't blame the industry for a failure in trying. In the pre-information age, they were at a loss as to know why nothing was working. Women went into the changing room with clothes, and came out without buying. On the high street, the plus-size fashion business was stalled and disproportionately small.
Roll forward into the Internet age, and broadly we are still in the same situation. Brands continually make attempts to widen this sector with diverse looks, price points, fits, quality and utility, but again these get sucked into a black hole. This time we can actually see that the consumer is interested in what's on offer, as plus-size fashion is being bought in ever-increasing quantities and social media is alive to the excitement caused with the new directional fashion-forward looks. However, the sector is suffering from truly horrendous levels of product returns – almost three out of every four plus-size items of apparel are presently being sent back. One thing has changed, however. In the information age, the answer as to why this is happening is now coming through loud and clear: overwhelmingly, these items are being returned due to poor fit.
Pre-ecommerce, it wouldn't have really mattered if we had found out that we needed to provide a wider range of gradings for this sector: stores could hardly have carried all that extra inventory, nor trained enough staff to target these diverse products and consumers correctly. But that was then, and this is now.
With the latest methods, we will have the ability to study our customers in huge numbers, clustering the data into body types and creating gradings that match each group of statistics. Larger brands will easily have enough capacity to create collections that are suitable for each shape – both in fit and style. These different collections will all overlap in design with basic items, diverging only where the looks become best suited to one specific body shape.
When selling, we will be able to take note of an individual's measurements so as to assign them a 'fit ID' – their body shape, height, measurements and fit preference – and supply them with the garment that will fit them. This must be done automatically. Customers will quite naturally browse the collections specifically created for them.
Smaller brands will create looks for their particular 'muse': as an exaggeration of what they already do, but with greatly enhanced two-way fit knowledge and communication. These brands, removed from the largely unsuccessful and damaging attempts to be 'everything to everybody' will have greatly enhanced profitability and opportunity for expansion.
To paraphrase George Santayana, "Those who cannot learn from the past are condemned to repeat it". We have the ability to learn from what has previously damaged the plus-size fashion industry, and the technology and capability to create a new response to this incredibly exciting, growing and lucrative market.
So what's the real problem distorting the supply/demand process in the plus-size apparel industry? What is causing the horrendous returns problem that afflicts this sector? Is there some mysterious black hole at the centre of this market? And, most importantly, is it something that can be solved? Do we now have an opportunity to create a new plus-size industry that is far more fit for purpose?
Let's go back to the pre-internet era, where the problem was already manifested. Back in the days where the consumer visited a bricks-and-mortar store and purchased her fashion after having checked the fit in a changing room, things were already far from peachy in the plus-size market. The level of customer satisfaction, the maturity of the market and the fulfilment of financial potential in this sector have always been extremely poor.
The poison in the bloodstream of the plus-size industry was a fit problem. All women – of every size, from the tiniest to the very largest – enjoy one of a number of diverse body shapes, such as 'hourglass', 'busty', 'pear-shaped', etc. This is because women have a number of differing areas of the body on which they store fat. As we grow larger, women add their excess body mass mainly on to these discrete areas, rather than evenly all over (or just around the middle, like most men). This means that women's differing body shapes become more exaggerated the further up the size range they go. Women of the same overall dress size can have a 20cm or more difference in any number of their measurements, meaning that two women of exactly the same dress size may simply find it impossible to fit into the same clothes. Plus-size women are, therefore, very difficult and complex to fit.
This complexity has created a cascade of negative effects that have always affected this market. Brands tried to create fits that they believed were likely to suit most people (just as they do in the 'straight' size ranges), by crunching the statistics into one 'average' grading. Even in 'mainstream' sizes it doesn't work brilliantly, but in the plus market, it fails because the resulting fit (the 'well-proportioned' body shape) counts for only about 10% of the population.
When plus-size designs requiring 'specific fits' (like tailored workwear suiting, for example) were produced using this formula, they therefore only fitted a small proportion of customers, creating very disappointing sell-throughs. The industry's response of providing 'non-specific' fits – a baggy, stretchy, shapeless offer – meant that although the clothing could actually fit on to their customers, it disappointed and infuriated them, causing them to refuse – as anyone would – to spend big on goods they found uninspiring.
Because the spend was poor, the industry assumed that the plus-size consumer was 'cheap', and reacted with a cut-price offer. The fabric and workmanship became low-cost, which minimised choice in the sector. Instead of having a range of price-points to match the 'straight' brands on the high street, plus-size apparel was relegated to one offer... that of the lowest price.
When brands tried to introduce fashion-forward looks, the fit for this type of apparel, again, needed to be specific, and, worse, the style had to be matched up to the correct body shape in order to look flattering, regardless of fit. When the bewildered consumers weren't physically able to buy into this enhanced design level, the industry concluded that larger women 'simply weren't fashionable'. This again affected the offer, with the choice of styles available to this cohort being limited largely to the predictable, repetitive, banal and mediocre.
At every point, new, good quality, stylish, exciting, fashionable looks for the plus-size market hit a brick wall... and it was always the same wall: fit. Unlike the sages of social media, I don't blame the industry for a failure in trying. In the pre-information age, they were at a loss as to know why nothing was working. Women went into the changing room with clothes, and came out without buying. On the high street, the plus-size fashion business was stalled and disproportionately small.
Plus-size women, already at a great disadvantage in society, were forced to wear cheap, shapeless, sexless, frumpy garments, reinforcing stereotypes and damaging self-esteem, careers and relationships. Fashion matters, and these women were being underserved.
Roll forward into the Internet age, and broadly we are still in the same situation. Brands continually make attempts to widen this sector with diverse looks, price points, fits, quality and utility, but again these get sucked into a black hole. This time we can actually see that the consumer is interested in what's on offer, as plus-size fashion is being bought in ever-increasing quantities and social media is alive to the excitement caused with the new directional fashion-forward looks. However, the sector is suffering from truly horrendous levels of product returns – almost three out of every four plus-size items of apparel are presently being sent back. One thing has changed, however. In the information age, the answer as to why this is happening is now coming through loud and clear: overwhelmingly, these items are being returned due to poor fit.
Pre-ecommerce, it wouldn't have really mattered if we had found out that we needed to provide a wider range of gradings for this sector: stores could hardly have carried all that extra inventory, nor trained enough staff to target these diverse products and consumers correctly. But that was then, and this is now.
Where the legacy is poor, it is our responsibility – and opportunity – to build a completely new system, throwing out the bugs as we go along.
With the latest methods, we will have the ability to study our customers in huge numbers, clustering the data into body types and creating gradings that match each group of statistics. Larger brands will easily have enough capacity to create collections that are suitable for each shape – both in fit and style. These different collections will all overlap in design with basic items, diverging only where the looks become best suited to one specific body shape.
When selling, we will be able to take note of an individual's measurements so as to assign them a 'fit ID' – their body shape, height, measurements and fit preference – and supply them with the garment that will fit them. This must be done automatically. Customers will quite naturally browse the collections specifically created for them.
Smaller brands will create looks for their particular 'muse': as an exaggeration of what they already do, but with greatly enhanced two-way fit knowledge and communication. These brands, removed from the largely unsuccessful and damaging attempts to be 'everything to everybody' will have greatly enhanced profitability and opportunity for expansion.
To paraphrase George Santayana, "Those who cannot learn from the past are condemned to repeat it". We have the ability to learn from what has previously damaged the plus-size fashion industry, and the technology and capability to create a new response to this incredibly exciting, growing and lucrative market.
There is absolutely no reason why plus-size womenswear cannot be every bit as exciting, fashion-forward, inspiring – and lucrative – as 'mainstream' fashion.
Fashion's 'mind-blowing' fact
The good news for fashion e-commerce is that customers are choosing to purchase apparel online in ever-growing quantities; the bad news is that some 40% of that is being returned.It's now common knowledge that these product returns create a matrix of detrimental effects on every element of the fashion industry. The loss of sales, customer dissatisfaction, forfeiture of loyalty, damage to stock, administrative/distribution/picking and re-stocking expenses, along with and ecological harm, create a powerful engine for change.
We know that around 70% of customers report 'poor fit' as their reason for returning apparel, and the industry is slowly edging towards developing the kind of intelligent solutions that are needed to drill down to the root causes of this fit problem. The beginning of this process is to take a long, hard look at our customers.
How, exactly, do we get to see our customers?
The solution still favoured by many brands is to simply ask consumers to choose the clothing size they wish to purchase, without any real inquiry as to their measurements. This is a legacy from bricks-and-mortar stores, where this system worked adequately – only then it was supported by the ability of the consumer to test personally the fit of each item in the changing room. Online, however, size self-reporting has proved too blunt a tool to provide acceptable results.
Many online retailers have therefore been forced to seek out some physical information about their customers, asking them to input body measurements, weight, height, and, occasionally, bra size and/or body shape. However, even when returns data is added into the mix, most of these systems have not been supported by sophisticated enough tech, and they must take their share of the blame for the level of product returns that we see today.
Luckily, the cavalry, in the shape of clever tech people, are busily doing what they do best: developing technological solutions. At present there are scanning devices, smart apparel, measurements from photographs and mobile phone apps undergoing rapid development, so very soon we should start to be able to get a much clearer idea of the size and shape of our customers. It's clear that the tech will not cease development until a thorough, accurate, continuous, 'sub-conscious' system of gathering consumer body metrics is perfected. This omnipotent tech may take some time to arrive, but we had better not sit around waiting for it: we urgently need to develop interim techniques that will help us do as much of the heavy lifting as we can. Any system that is even marginally more effective than what we have now is going to diminish the numbers of returns, which is enough of a reason to adopt it. However, a more vital motive will prove to be the ability to begin participating in the industry transformation that will advance with every fresh piece of customer data gained.
Will fashion customers willingly give up personal information?
The answer to this is a resounding yes... and also a frustrating no. 78% of customers reported being willing to share body metrics in exchange for a better fit. Yet, like everything else to do with human beings, the answer is more complex than at first view.
Consumers can – and do – contaminate their own information every time they come into contact with it.
If body measurements are continuously being requested (or fed back), a number of detrimental effects will be seen. Some customers will balk at even knowing accurate personal statistics ("The last time I measured myself was when I was at my slimmest: I really don't want to know how my waist compares now"), some will disagree with feedback from automated measuring systems ("How much? There's something wrong with this set up!"), and others will be deterred from purchase ("When I find that I've put on weight, I find that I've been put off buying anything"). These, and many other emotional reactions to sizing, add up to a situation where input is often out-dated, inaccurate, or, even worse, the very act of obtaining the latest data deters or upsets the consumer to the extent that it has a detrimental effect on sales.
We will solve this conundrum only by providing an automatic apparel fitting service designed to keep conscious customer involvement to a minimum. As usual, we will have to get smart.
"It'll blow their minds"
When considering the effects of new advances, many people focus on the tech itself – in this case, assuming that once we have the body metrics of our fashion consumers, this information will be slotted into the sales process at the point of sale. In other words, the stock sits in the warehouse – the consumer at his or her screen, and the tech simply pairs up the matching size.
This, although true as far as it goes, understates the case a thousand fold, because, like all great technological advances, it is the way tech interacts with society that brings about the most significant disruption – often in the most unforeseeable ways. In this case, we will see the effects on the fashion industry of a tidal wave of information.
When talking to a friend (a fellow customer expert), I asked him how he thought the fashion industry would react once it gets hold, for the very first time, of all the body metrics of its consumers (and particularly those of the ever-growing plus-size section of the population). He instantly said "It'll blow their minds". I agree.
It is only once we have seen in detail the huge diversity between the body shapes, sizes, heights and weights of our population that we will begin to have a true picture of what we are up against. The fact is that we have never produced apparel that actually reflects the sizes and shapes of our population – far from it.
The true reason for a return may not be that an individual is being supplied with the wrong item of stock – with the right piece having remained at the depot. It is actually highly likely that the brand has not manufactured any items that will adequately fit this person – and many others – because their choice of gradings is inadequate. The information will tell the company that there is no 'right piece' for this individual – not even close. And this is going to be happening millions of times across the industry. The brands that find this out are going to have to think about what, if anything, they are going to do about the river of gold of potential business that they are presently losing out on.
If we are going to offer the correct apparel to our consumers, we will need to redesign every size, introduce every grading, redefine our offer and our entire tech – root and branch. We will have to learn to think completely differently about the way we fit people into apparel, and how we create clothing fit for people.
Those fashion brands that are swift to realise the enormity of the opportunity gained by this enhanced knowledge are going to be at such competitive advantage that they will sweep all before them. In turn, tech companies that win the race to develop the technology driving this disruption are going to become the behemoths of commerce.
As my friend concluded, "It's a great time to be alive".