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Hiding in Plain Sight

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In her latest piece for WhichPLM, Emma Hayes, womenswear customer fit expert and Founder of At Last, shares her expertise on customer denial when it comes to apparel fit – in particular, when it comes to plus-size womenswear. She argues that developers of fit technology should be studying the psychology of potential users as closely as they are looking at the grading of garments.

To what degree does customer sizing denial effect eCommerce fashion returns?

Throughout history, across cultures, women’s figures have been compared to the ideal body shape prevailing at any given time. Women have often taken this very seriously, and been known to resort to body modification, such as dieting, exercise, corseting – even cosmetic surgery – to conform to this standard. Those whose bodies diverged, learned to disguise their “faults”, or risked being forced to accept their lowered status as imperfect specimens.

Arguably, this situation became even more extreme with the advent of the internet, where a mob mentality about women’s body shape has emerged. The celebrity, Lady Gaga, for example (a woman with a near perfect figure), when performing at the 2017 Super Bowl, was attacked by an army of online “haters”, who accused her of having a “pooch”, because her stomach was not perceived to be perfectly toned. The superstar resorted to an Instagram defence: “I’m proud of my body and you should be proud of yours too.”

Fashion consumers are particularly sensitive to celebrity culture and absorb countless such negative messages whilst browsing.

Added to this media pressure, a woman’s romantic partner, her doctor, or even members of her own family may critique her physique, resulting in a lack of self-esteem. Thus, many women are in denial about their size, hide the parts of their bodies that might cause offence, and some cannot even look at their own “faults” in the mirror in private without shame.

With a woman’s size and shape engendering such fraught emotions, it is little wonder that the fashion industry is wrestling with fit issues.

Consumers’ attitudes towards their own bodies have created pressures that have skewed sizing since the introduction of manufactured garments back in the 1950s. Theoretically, the achievement of a good fit should not have caused any problems at a time when most apparel could be tried on in the fitting-room of a bricks-and-mortar store.   Yet, even then, the negative emotions surrounding sizing caused problems, with a significant percentage of women rejecting apparel with a number on its label that they didn’t relate to. The subsequent loss of sales resulted in the phenomenon of “vanity sizing” (in which certain manufacturers re-designated garments with increased measurements and decreased sizing numbers). And this was not an insignificant problem: the degree of apparel sizing inflation that occurred during the period from the 1950s onwards meant that a size 16 in 1958 would have been the equivalent of a size 8 in 2011.

These sizing and grading adaptations have been piecemeal, generating a non-standardisation of size throughout brands. Indeed, the sizing muddle that exists in the fashion industry today is arguably an expression of how consumers’ body shapes and measurements can never be seen solely in objective terms. There is always going to be an element of psychology involved with womenswear sizing.

Whereas the fashion industry has a history of apathy towards accurate measurements, this casual approach towards fit is something that doesn’t suit the eCommerce era. The opaque sizing legacy we see today is a significant component of the retail return problem which is ruinously expensive to companies (both financially and in terms of customer loyalty), and to the planet (globally, they are a source of huge ecological damage). If garment return was a crime scene, the smoking gun would be sizing: the issue of apparel fit must now be taken extremely seriously.

AI (artificial intelligence) is being developed to provide a solution, once and for all, to accurately fitting eCommerce consumers at the point of sale. Some of the online “fit tools” come in the form of a questionnaire, where fashion customers are asked to input various measurements, but the direction presently being taken by leading tech developers will rely heavily on digital scanning or similar innovations. This might mean using dedicated devices (say, in-store, at shopping centres or even gyms), or, more accessibly, with apps on a consumer’s own phone or other device. The object would be to make a 3D representation of her physique, either from a selection of photographs, or a direct scan of her body. Many assume that this process will always be met with complete cooperation and accuracy by the participant. However, as the history of apparel sizing will attest, this issue is not likely to be as simple as it first appears.

My speciality happens to be plus size female customers: an ever-growing cohort of women who suffer from the greatest number of fit problems and who thus generate the largest percentage of returns per dollar spent. Due to their diverse body shapes and widely extended range of sizes, these women offer a particular challenge to retailers. But the problem does not begin and end with their bodies; their minds also offer considerable obstacles to obtaining the correct fit.

In view of the micro-scrutiny, and (as Lady Gaga might put it), “hate” being projected towards physical imperfections, it is little wonder that some women develop secretive behaviours surrounding their bodies, and this is particularly exaggerated in the larger sized cohort. We live in a society that particularly abominates obesity, so, from bad experiences, many larger people resent being analysed and observed. Knowing that the very shape of their body can give offence, some plus size women habitually resort to camouflage or concealment, even from themselves.

When developing technology, it’s natural to make logic-based deductions about the attitudes and behaviour of those who will use it. It might be thought sensible, for instance, to assume that the public will fully cooperate with a process that will benefit them with clothing that fits properly, just as it’s easy for fashion professionals to suppose that everyone possesses a weighing machine and/or tape measure. On the face of it, it appears logical that consumers would accurately report the resulting personal data. Similarly, customers will surely be happy to have their body scanned, or, at the very least, supply sufficiently revelatory photographs, if for a good enough reason? And once the correct size has been calculated, would she not be very happy to follow that advice? But one could look at each of these assumptions and dismantle them all.

Consumers are faced with a plethora of clothing options, and they may not feel any urgency in obtaining the correct fit for any one garment. Indeed, if the purchase process appears too onerous (or makes them feel uncomfortable), they will decide to shop elsewhere. Some people (if they dislike revealing their own measurements) may not even possess the equipment to obtain them. Some may input inaccurate figures due to feelings of negativity or denial.

Scanning interacts with consumers differently, triggering a unique set of issues, but encountering negativity from the same source. For example, for the shape of the body to be obtained, much imaging tech requires the subject to wear tight-fitting apparel: something which can trigger negative emotions, especially in plus size women. Many people who have body insecurities will feel as uncomfortable about the existence of an image of them in tight-fitting underwear, as the average person might feel about pictures of themselves in the nude. When presented with the resulting 3D avatar, some subjects can feel embarrassment and alienation. Not emotions that enhance a shopping experience.

Whatever tool has been used to establish a sizing recommendation, the retailer will then be faced with the same problem that has bedevilled the fit issue for the best part of a century: will the customer accept her size?

Fit technology (although, arguably still in the early stages of being developed), is already effective at preventing many sizing-related returns and is rapidly improving. But as yet, it has only been adopted by a self-selected cohort of consumers who have shown a particular willingness to embrace it. For these tools to be reach optimum effectiveness, a high level of participation will be necessary, so it will also have to be acceptable to a wide range of people, some of them far more sensitive than others. Negative emotion about size and shape is not an issue that will necessarily diminish as the public get more accustomed to a new purchasing regime, any more than the pressures that caused vanity sizing went away over a period of some seventy years.

Whilst evolving any interactive consumer technology, developers should be studying the psychology of users as closely as they are looking at the grading of the garments. It should always be remembered that this is elective technology: customers can choose to avoid it if they wish. In an ideal world, the source of physical insecurity, body shaming, would be eliminated, and human beings would relate to the fit of their apparel in purely functional terms.

However, as this is unlikely to happen any time soon, new fit technology will benefit  enormously from developing an interface with the consumer that allows her to feel less judged and more secure in her privacy and comfort. The issue of what (and how much) is fed back to users is a vital one. The retail experience will enjoy greater participation from the public if it presents an easy-going, pleasant, entertaining, deliberately ambiguous, and non-quantitative feedback to its users.

This is likely to involve giving the consumer a place to hide, even from herself.

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Lydia Mageean Lydia Mageean has been part of the WhichPLM team for eight years now. She has a creative and media background, and is responsible for maintaining and updating our website content, liaising with advertisers, working on special projects like our PLM Project Pack, or our Annual Publications, and more.Joining mid-2013 as our Online Editor, she has since become WhichPLM’s Editor. In addition to taking on writing and interviewing responsibilities, Lydia has also become the primary point of contact for news, events, features and other aspects of our ever-growing online content library and tools.