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Fashion’s Primacy of Preference

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In her latest piece for WhichPLM, Emma Hayes, womenswear customer fit expert and Founder of At Last, shares the issues our industry has with accepting consumer preference, and how technology can help going forward.

Fashion is preference. Were it not for preference, everyone would wear exactly the same clothes, in the same way, all the time, and no one would care very much about how clothes fitted, how fashionable they were, or how stylish. The subject of apparel preference is of huge breadth, including, as it does, consumers’ partialities concerning style, fit, and even ecological concerns: arguably, everything that comes under the umbrella term of “taste”. Without preference there would be no such thing as “fashion”: there would only be clothing.

Taste in apparel is something that is affected by countless aspects, such as body type, culture and age, and there will always be a mysterious (even subconscious) element to it. Preference amongst consumers is the engine that drives the world of fashion forward season by season: a kind of alchemy that makes the typical consumer’s fashion palate shift on a regular basis. Some time ago, for example, the fashion-forward customer couldn’t get enough of full-length, super-skinny jeans. Now, wider, shorter-length denim is a “thing”, and soon the prevailing look might be something else altogether. Preference evolves like this, continuously churning throughout the population.

I have a professional interest in womenswear garment fit, which encompasses the issue of fit preference. Putting aside other fashion inclinations, fit preference concerns how a woman expects her clothes to hang, drape, cling, tailor – or otherwise interact with the shape of her body. An individual’s fit preference is fairly stable over her lifetime and is one element in a matrix of concerns that is presently costing the ecommerce fashion industry billions of dollars a year worldwide in garment returns.

Here’s a thought experiment, illustrating to what the term “fit preference” refers. For a given period, a woman (the “wearer”) is to be dressed in clothes selected by another female, the “shopper” (who is the same age, height, body shape and weight as she is). The fashion taste and colouring of the two women are perfectly aligned. The shopper is tasked with choosing items that fit her own body exactly the way she likes, and there is no interaction between the wearer and the shopper.

Initially, hearing about this situation, some would suggest: “If the two women are the same size and body shape as each other, the shopper’s choice of clothes will automatically fit the wearer perfectly.” Or, perhaps, they would say: “I can’t even guess what this experiment is about: there’s literally nothing of note here”.

During the course of the hypothetical study, it turns out that the clothes don’t fit the wearer in the way to which she is accustomed. The waistlines, for example, feel looser than she normally wears, which is because they are expected to “settle” low onto her hip, rather than snugly on the waist. The necklines appear quite low, meaning that the wearer feels that they are somewhat more “revealing” of cleavage than she would prefer. Generally, the shopper’s choice of clothing is different from the wearer’s “normal” fit: everything feeling “slouchier” than the wearer would have selected for herself. The woman reports that she “feels different from normal” and “uncomfortable” when she is dressed this way.

Analysing the result of the trial, is it surprising that this could happen between two such physically similar people? Could the wearer be expected to find dressing this way acceptable once she has had the opportunity to get used to it? Or would it be logical to surmise that the wearer would not willingly tolerate this type of fit for long?

Fashion professionals who work face to face with consumers will not be surprised by evidence of fit variance between individuals. Indeed, one of the most useful methods employed by the canny stylist happens prior to selecting any apparel to show her client: it is to observe the customer’s fit preference, as judged by what she is already wearing. Detecting a consumer’s established fit pattern saves considerable time, but does not make any impact on which items are ultimately purchased. The consumer, when physically present, will soon make her preferences clear, when she tries the items on. Ecommerce fashion does not have this luxury: everything is bought without testing the fit first, and inappropriate garments are usually returned for a refund: an expensive and wasteful process.

This is far from a theoretical situation. Outlandish as it sounds, the idea of the fit of a garment being automatically settled upon by an entity other than the wearer is fast becoming a possibility: soon, consumers may have the fit of their apparel selected, not by another person, but by a “bot”.

The fashion industry is facing a major problem with ecommerce garment returns. Worldwide, the National Retail Federation says ecommerce returns overall average between 20% and 30%, which, in a 1.5 trillion-dollar industry, of which 47% of sales were made online in 2020, equals a hugely expensive problem. A large proportion of these returns are reported as being due to fit problems. Unsurprisingly, the race is on to find a solution for assessing the perfect garment fit for consumers who are buying “sight unseen”.

Arguably, the “physical” aspects of web retail fashion fit are in the process of being solved. Women’s bodies, for all their diversity, are visible and assessable from the outside. This is not to underestimate the difficulties inherent in designing the tech necessary to body-scan a consumer to record the size and shape of her figure, for example. Complications abound with this technology, but, arguably, these can be resolved with practical solutions. However, the issue of preference is more subtle and mysterious, involving, as it does, the content of the consumer’s head. When two women have the same type of physique, their body scan will look similar, but this does not mean that they have the same taste in fit.

The difficulties in establishing the fit preference of a consumer are legion. A woman’s inclination includes how she approaches dressing different parts of her body, and her figure as a whole. It encompasses differing choices in both alternative items of apparel and in varying activities whilst wearing those items. To establish a comprehensive “fit preference body map” of a given consumer, a considerable degree of observation and research into that individual would be required over enough time to understand the various types of apparel that she wears. It’s one thing (albeit not so easy in itself) to ask a consumer to undergo a body scan at the point of sale. It’s quite another to build up a detailed picture of her fit preference, starting from scratch each time she is making a purchase!

The fit preference of a given consumer is therefore something that will take time, subtlety, and considerable expertise to establish. And once completed, this valuable information will, by necessity, be passed on to other fashion retailers, through confidential and secure information-sharing technology. Consumers, the fashion industry, and legislators, will have to be prepared to make the difficult decisions necessary to facilitate this.

There is no escaping fit preference. As it is spectrum, with the “least fussy” consumers at one extreme (people who would wear just about any fit that doesn’t offend public decency), to “hyper-controlling” individuals (those who will not, under any circumstances, consider buying a garment unless its degree of ease is exactly to their taste) at the other, everyone has a place on this scale.   These variations become markedly exaggerated in the plus size female cohort. Many in the fashion industry appear to believe that when technology decides on a median fit, eventually consumers will “get used” to it, and the issue of fit preference will simply go away over time.

However, those who understand what it is like to wear an occupational uniform (where the fit is usually a generic one, taking into account only the size and height of the wearer) may question this theory. All the evidence (albeit anecdotal) from this experience is clear: people can wear apparel for a considerable period (years, or, indeed, decades) without ever having got used to a fit that they have had imposed on them from outside. An individual’s fit preference often proves to be extremely resilient: few people enjoy having their own choice of fit overridden, and for some, it is a miserable experience. There will be many consumers that will not agree to actually pay for it.

It may be somewhat ill-advised, therefore, that there currently appears to be little interest in consumer preference amongst those developing body-scanning technology. Few retailers would expect to get away with imposing their taste in fashion styles on a consumer, so why should they think they can successfully do so with fit? The theory appears to be that, even where the consumer is not entirely satisfied with a generic fit, she will not be unhappy enough to return the garment. At best, this notion could be said to be lacking in ambition; at worst, it shows wishful thinking, used to excuse a disregard for customer service – a gamble that leaves the retailer vulnerable to commercial disadvantage.

Fit preference has been part of the human make up for hundreds (likely thousands) of years. It is one of the aspects that enables a person to express individuality through their look: it offers emotional support for bodily insecurities and bolsters feelings of attractiveness. It underlines the morals of the wearer or, conversely, reveals a sense of freedom from societal values. There is no evidence that distinct taste in fit will go away anytime soon. Or, indeed, that it would be a good thing if it did.

It’s much more likely that, when rolling out point-of-sale fit tools for online fashion, any experiment in imposing a generic fit on consumers will provide somewhat disappointing commercial outcomes. No doubt, with any advance in sizing technology, there will be fewer returns than the present situation (where fashion ecommerce fit advice is scarce and of poor quality: causing the abysmal rate of returns that is currently occurring), but, in a world where it is important to avoid all unnecessary waste, it’s highly likely that there will still be too many garments sent back due to fit issues. A place for fit preference will therefore ultimately need to be found in the technology presently being developed, so that all consumers will get what they want: a look that they can feel comfortable with, and one which they feel respects and expresses their taste as an individual.

And this is also the surest way for ecommerce fashion to get what it wants more than anything else: fewer garment returns.

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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.