Today fit expert Mark Charlton discusses the barriers to fit success if we continue down our industry’s current path. He shares his view of a world with lower product returns, higher inventory management, and satisfied, brand loyal consumers.
I have a passion for great fitting apparel, and for over 20 years I have been helping brands understand sizing constructs and globalize fit offerings.
Most of my articles thus far have addressed the complexities of creating, perfecting and executing fit across a diverse and ever changing consumer landscape.
In this article I would like to explore the key performance metrics (or lack thereof) for measuring fit success and consumer validation with regards to fit and sizing.
It would be remiss if I didn’t acknowledge COVID-19 and it’s impact on the apparel retail industry. My reflection, among many, is the rocket ship-type acceleration of e-commerce. E-commerce for many retailers and brands has been the life buoy keeping them afloat during the trying times of COVID and, for some, the differentiator from survival to thriving in this new forced normal. However e-commerce does have its challenges, with fit and sizing being one of the biggest, as well as the single biggest reason e-commerce apparel is returned.
Taking a slightly different approach to the problem, I have investigated the shift from push model to pull model that many manufacturers are transitioning toward in order to better manage inventory based on more accurate demand signals.
Applying this approach to apparel fit communication, the industry is very much in the push model of “here’s a product and here’s how it fits”…but fits who exactly? The model it’s photographed on: how does that translate to me? How does it translate to you? And to your individual consumer?
Like the stripes on a zebra every human is individual; we have our own unique shape, size, proportion and preference (how we choose to wear our garments – slim, loose, long, short, etc,). Oh, and by the way each of these factors are variable over time. Like it or not our shape and proportions change over time, as do our preferences based on our pace of trend adoption from early adopters to laggards (in front or behind the trend).
I see sufficient risk if the industry continues on this path, in this model.
E-commerce has increased operating costs as garments are shipped individually to consumers’ homes versus consolidated shipments to store. One could argue that e-commerce sites provide significantly lower operating costs than physical stores, however now consider that a large percentage of product that is shipped out to consumers is returned due to perceived poor fit and sizing. The impact of these returns are not only with further increased shipping costs but also a significantly delayed selling / fulfilment window for said product, as well as skewed inventory levels and procurement as a result of unpredictable returns. This in turn equates to either insufficient inventory or excess inventory – both problems significantly harming the retailer’s bottom line.
Perhaps the largest risk of all is brand credibility through the eyes of your consumer, aka consumer confidence. Every return equates to a dissatisfied consumer and a potential lost consumer.
Above I referenced perceived poor fit and sizing as the fit and the sizing goes through many stringent processes to ensure the fit is as the designer / merchant / brand intended. However, how successful are these processes if the consumer is either confused by the fit or size offering, or dissatisfied at the point of receipt?
As a brand or retailer what we cannot control is the shape and size of our consumers; what we can control is our product offering, our fit and sizing offering. Then be aware of how our product fits different shapes and sizes and how individual consumers can navigate the size construct to align with their fit preference.
An example I frequently use is: I am 5’10”, 200lb, ex-weightlifter, endomorphic body type (short and stocky), and I generally purchase a size ‘large’. However if I see a shirt I like but it’s a slim fit and I am looking for a looser fit, I opt for an XXL as this fits perfectly for my needs. I purchase the slim fit shirt in an XXL, wear it and am happy.
But the metrics or the take away that the retailer would see is “the slim fit shirt is resonating with the XXL consumer”. As opposed to the ‘Large’ consumer needing more of a loose fit.
We know that sales are an indicator for future product creation therefore basing future product lines and product mix on historical sales can be dangerous if you do not truly understand how your consumers are experiencing your product.
Hence the need to establish accurate, meaningful metrics of fit success. A true reflection of how your product is being experienced by your consumer.
Sales alone are not an accurate measure of fit success, a much more holistic approach is required. Sales along with returns will create a better picture but, in my opinion, in order to be truly accurate and meaningful sales and returns need to be filtered by size then be balanced and clustered by demographic, and a similar demographic clustering by body shape / proportion and preference. And let’s not forget that consumer feedback needs to be also accounted for and balanced.
Imagine a dashboard that charts product sales, returns and feedback that can then be broken down by consumer demographic and/or by body shape demographic, then fit preference. This would show how your product is being purchased, by whom, and how they experience your product.
This, I believe, would be much more meaningful in order to create products that consumers want in the fit and size that they need.
The next step is to create a more individual way to communicate fit and size to your consumers, I do see a few examples of brands and retailers showing products on different sized models. This is an encouraging baby step. The next step I believe is to unpack the preference communication. Take a standard slim fit tee: this is designed and developed to fit slim, but in reality one could choose to size down for super slim / skinny fit, size up for a more regular fit or size up 2 sizes for a loose fit.
With the progression in body scanning technology soon we will understand the body shape, size and proportion of our individual consumers along with individualized fit communication to unlock preference paired with individual purchase and return history. Then we can accurately dashboard, with meaningful metrics, fit and fit success.
The future will be better fitting clothes that meet your individual consumer’s expectations, lower product returns, better inventory management and most importantly satisfied consumers with higher brand confidence.