How E-Commerce Killed Forever 21
Examining the death of the fast-fashion retailer, and the tech-focused factors which lead to its demise.
Named after its target audience, Forever 21 emerged in the 1980s as a fast-fashion brand catered towards (you guessed it!) twenty-something year old women, selling trendy clothing at low prices. The retailer was a huge success for about three decades, hitting its peak in 2015 with co-founders Jin Sook and Do Won Chang seeing a combined net worth of $5.9 billion. Earlier today, however, Forever 21 filed bankruptcy — specifically for Chapter 11 bankruptcy protection — planning to close nearly half of its stores worldwide, and use this downfall as an opportunity to rebrand & re-emerge in the new world of e-commerce.
So, what happened in the four years between Forever 21’s peak and its bankruptcy filing?
Forever 21 is one of many retailers who have recently shut down storefronts or gone bankrupt specifically due to their inability to properly adapt to e-commerce. Just last month Barney’s New York set an example of how being unable to keep up with such technological advancements can lead retailers towards fateful horizons. Specifically, Forever 21 heavily invested in conventional malls and neglected consumer shifts to online shopping, seeing solely 16% of its sales happen online. However, not only has e-commerce revolutionized the typical way to shop, shifting from in-person connections to purely online experiences, but it has also redefined how data is and must be used by retailers in order to survive.
Currently seen as quite the controversial business model, fast-fashion is defined as when retailers quickly produce clothing mirroring latest trends at inexpensive costs to consumers. Forever 21 embodied this model upon its founding, boasting that none of its items would sell for a price above $50. Nowadays, however, consumer trends are shifting; customers actually prefer to pay more for an item of clothing that is of better quality, and might actually be deterred from companies that identify as “fast-fashion”.
Although fast-fashion offers affordable, low-priced clothing to consumers, the madness behind this method is quite astounding. Fast-fashion is notorious for causing “environmental havoc”, as 85% of textiles produced each year end up in landfills. Its necessary quick product turnaround means that mass items of clothing are produced in a short period of time, only for trends to change and turn these items to waste.
Millennials, or 21–34 year olds, are also the generation which cares most about purchasing from sustainability-friendly brands, with 85% of the sub-population claiming it is “extremely or very important” to them that “companies implement programs to improve the environment”. This is a 13% increase from baby boomers, who were likely its target audience upon Forever 21’s founding.
How are these dire implications of fast-fashion related to e-commerce, and why did Forever 21’s lack of e-commerce adaption help its demise?
The Rise of E-Commerce
E-commerce is defined as the buying and selling of goods on the internet, as well as the tracking of data that goes along with such transactions. Nowadays, e-commerce is much more powerful than setting up a pretty website on Shopify — what’s going on behind the scenes of a website is far more important to the user experience and to ensuring retail success.
Applications of machine learning in e-commerce, for example, are a significant way in which data from user browsing and transactions can propel an online retailer’s profit. Much like how when you walk into a physical store, a sales representative can read your body language, follow what you’re browsing, and make targeted product recommendations, machine learning can allow retailers to make these same targeted sales entirely online.
One fashion-tech startup which has been dominating the e-commerce product recommendation sphere is Revolve, managing to improve its product sell-through by 20% after implementing more advanced ML & data tools to better target its users’ demands.
A product’s success, additionally, is predominantly influenced by its price, and machine learning can help retailers with that too. By teaching computers to compare competitor prices, adapt to new data patterns, and detect emerging trends, retailers can implement price optimization strategies and thus develop a supply chain most beneficial for their businesses. Not to mention that machines can run these analytics at rates much faster than of which any human is capable.
Machine learning and data tracking can also help retailers identify more precisely what consumers actually want, instead of blowing money on advertising and expending manual labor to figure it out themselves. I’ve written about this previously, using Chanel as an example of how retailers often misunderstand what they think their customers want versus what their customers are actually looking for. In fast-fashion specifically, when technological advancements allow for more accurate garment production based on identifying what people are actually going to buy, producing enormous quantities of clothing only for the majority to end up in landfill is no longer acceptable.
As of 2018, the United States brought in $4.5 billion from e-commerce alone, and the division is becoming increasingly more competitive. If you’re unable to shift along with your consumers, use data to augment profits & eliminate waste, and better cater to the wants of your customers, then succeeding in e-commerce is not for you. R.I.P., Forever 21.
Fashion and tech are more closely linked than ever, and nowadays retailers can either embrace this necessary synchronicity or charge, aimlessly and blindly, towards their own demise.
Reach out if you want to talk more about fashion & tech — I’d love to hear from you!