How Shein revolutionised retail for the 21st century

In October 2020, Chinese retailer Shein became the largest online-only fashion company in the world.

Although the business is based in China, the majority of Shein’s markets are abroad, and the retailer ships to more than 220 countries or territories worldwide.

In the first half of 2021 Shein was the second most downloaded shopping app globally and the business’s revenue has grown more than 100% every year for the past eight years. 

It is now valued at around $47 billion.

Clearly Shein should be a household name, but, if you are over 30, chances are your knowledge of the company is limited. This is all to do with Shein’s hyper-targeted business model, which focuses its advertising on the holy grail of retail buyer personas – Gen-Z women aged 15 – 30.

In an over-saturated market, limiting your target audience so drastically shouldn’t work – and yet Shein have proven that it can, to an impressive extent. 

In this article we will explore how a company launched by a Chinese SEO executive has used artificial intelligence and data analytics to become the TikTok generation’s number one fashion brand.

Shein if you want to go faster

The last time the fashion industry enjoyed such a revolution was the 90’s, when Amancio Ortega founded Inditex, the fashion conglomerate that made him the 10th richest person in the world.

You may not have heard of Inditex, but you will have heard of Zara, the jewel in the crown of Inditex and the pioneer of ‘fast fashion’.

At Zara, the focus is on manufacturing up-to-the-minute fashion items internally – using the reactions of customers to inform the latest designs and create a production line that is always moving.

Zara researches latest fashion trends around the world and designs affordable items based on these insights with a rapid turnaround time. The brand claims to be able to get pieces from the drawing board to the shop floor in just three weeks.

For customers, the ability to keep up with the latest fashion trends at a price point that is manageable for all budgets is appealing. So much so that direct competitors such as Mango, Uniqlo and H&M were eventually forced to change their own manufacturing model to keep up. 

Thanks to time and technological advancement, fast fashion has gotten faster – and simpler. Online stores such as ASOS and Boohoo offer the same roster of regularly-updated fashion products delivered to customers’ doors in less than 24 hours. 

But these businesses still rely on personal relationships with their customers, and a certain combination of research and instinct in order to choose the right product lines for their target audiences.

Artificial Intuition

Today we are living in an internet age where all businesses have access to a vast supply of one of the retail world’s most precious resources –  data.

Retailers do, of course, already use cookies and algorithms to note trends and individual customer behaviours. 

The natural next step was to create an online-only system that could monitor global fashion trends in real time, measuring it against inventory numbers and in-app user behaviour to create an automatic supply process that happens so fast it’s almost intuitive.

This is exactly is what Shein did, turning ‘fast fashion’ into ‘real-time fashion’ – a term coined by US tech and business bloggers Packy McCormick and Matthew Brennan.

How does it work?

Shein’s AI gets its product ideas from the search and social media behaviours of its target consumers. 

These ideas pass directly to Shein’s internal designers, an 800-strong team who work continuously to produce clothing items based on the ideas as they come through. The finished designs are passed over to suppliers automatically through Shein’s central enterprise resource planning (ERP) system, ready to be manufactured and sold in limited numbers.

If the items are popular, the order volume for manufacturing increases, automatically and in real time, through the ERP.

This real-time model cuts the time from concept to finished product from three weeks to as little as three days.

While the idea of fast fashion is nothing new, this intuitive form of targeting and marketing definitely is. 

In fact, in April 2021, data analytics firm Apptopia stated that

“Shein is so far ahead of its direct competitors that it’s difficult to even compare them.”

Origins

Shein was founded in 2008 by Xǔ Yǎngtiān 许仰天 (Chris Xu), an SEO specialist working in the exports industry.

With a good understanding of how best to help domestic companies to sell products to overseas customers, and an extensive knowledge of search engine optimisation, Xu decided to open his own export venture, originally specialising in wedding gowns.

In 2012, Xu expanded his product range to include all types of women’s clothing, although the site (then known as SheInside.com) was still, at this point, only an online platform. The site worked by uploading images of products, waiting for enough orders to come in and then ordering them wholesale.

By 2014, the newly-rebranded Shein was now designing its own clothing, with a team of designers working in-house to design and prototype outfits, and a network of factories and workshops on-hand to produce the clothing at an affordable end-price point.

When Shein moved its headquarters to clothes manufacturing hub Panyu in 2015, all of its suppliers moved with it.

 

A new type of supply chain

Shein has made waves in the fashion and clothing manufacturing sectors in more ways than one.

The brand has actively worked against the expected standards of China’s clothing manufacture industry, rethinking the way supply chains work in the 21st century.

The core principle of Shein’s supply chain management approach is paying suppliers quickly, and on time. 

Global industry billing practice is usually 90 days – especially for those dealing with big businesses – and it is common for payments to be delayed even past this point. 

Shein offers suppliers payment terms of 30-45 days, and consistently meets its pledge to pay them on time.

The brand has been vertically integrating their supply chain steadily, taking on various responsibilities that are traditionally handled by factories (prototyping, designing), reducing cost and risk for their manufacturers.

Additionally, Shein offers loans to suppliers to help them to get their own businesses in order, and thus able to handle larger volumes of orders.

In return, the company insists that their suppliers use Shein’s supply chain management (SCM) software instead of their own – meaning that all 300+ of their factories are connected via one cloud software system, allowing the brand to keep track of the status of every order they have.

Consumer-driven manufacturing

But Shein’s supply chain isn’t the only automated part of their business.

Shein’s business model essentially links supplier to consumer in a way that negates the need for human intervention.

There is a good reason for Shein’s insistence on suppliers using their software. Through this software the company is able to get real-time information about factory capacity and inventory, but also monitor customer searches and buying patterns. 

This means that Shein can update their manufacturing capacity utilisation rate to reflect the popularity of individual items.

Put simply, the SCM is able to live-update what needs to be produced, and how much, based on what consumers are currently clicking on and buying.

When a new item goes live on the website an algorithm goes to work instantly, noting clicks and sales and increasing or decreasing the production quota as necessary. This same algorithm automatically orders any materials needed, and begins recommending the item to more users with similar profiles.

This works in much the same was as TikTok’s algorithm, which monitors video engagement with limited groups of users and then expands their viewership out as users continue to engage.

TikTok is immensely popular with users under 25 because the algorithm provides a flawless user experience, creating a feedback loop that ensures users see only the videos that are the most relevant to them every time they sign in.

For Shein, the consumer-to-manufacturer (C2M) model ensures that the brand is able to be all things to all consumers. 

Rather than having its own specific style, which requires consumers with those interests to find the site, the products that users see reflect current fashion trends in their age group, and even location, in real time.

Because of this, Shein is able to add between 700 and 1,000 new clothing items to their shop every day. 

Diagram, schematic

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Shein’s Real-Time Retail Flywheel, Analysis: Matthew Brennan

Marketing to Gen-Z

Where the algorithm works to cover the back end of Shein’s business model, data is also key to the customer experience that makes Shein so successful – and the two elements feed into each other seamlessly. 

Shein’s app works to create an addictive user experience, which ensures consumers are regularly checking and browsing the app, feeding more data in and helping the algorithm to learn their interests more effectively.

One of the surprising ways in which Shein has been able to effect change in Western consumers is in pushing customers onto its app, where data can be collected more easily, and the buying journey more carefully regulated. 

In China, native mobile apps are far more common than in the US, UK and Europe. Many Chinese businesses struggle to bring customers from the Western world onto apps, as these consumers are more comfortable using websites. 

However, Shein has astutely chosen their target audience to match this need – the devoted mobile-users of Gen-Z. 

More than any other demographic, Gen-Z are comfortable with, and used to using, mobile apps. This means that they are more than happy to download and use the app for a simpler shopping experience.

Feeding the fashion addiction

Thanks to the app, Shein is able to hold a distinct advantage over other fashion brands in three key ways:

  1. Cost (the affordability of their items),
  2. Range (the choice available to consumers), and
  3. Retention (how addictive the shopping experience is).

With thousands of new items appearing on its site every day, Shein is able to easily source and present brand new content to consumers on their social media profiles.

The affordability of its clothing makes the company an easy source of user-generated content such as ‘haul’ and ‘try-on’ videos.

In fact, Shein invests heavily in targeted social campaigns for exactly this reason. 

The brand has its own extensive affiliate network which includes influencers and customers (known as Key Opinion Consumers), who are offered discounts and free clothing items to create content.

More recently, Shein has begun collaborating with celebrities like Katy Perry, Khloé Kardashian, Lil Nas X and Bahraini celebrity Almahra, creating Key Opinion Leaders (KOLs) who create clothing lines, perform at event – essentially boosting the company’s relevance in specific markets.

In the app itself, Shein has incorporated gamification to make the browsing experience more compelling. Shoppers are rewarded with points for frequent logins and reviewing clothing items – the app even hosts playable minigames.

Customer acquisition

Clearly, Shein’s data-focused model works, as is demonstrated by its year-on-year revenue growth. 

Another area in which the company’s use of AI has seen exceptional results is in customer acquisition. For a business that is growing so quickly, Shein’s customer acquisition costs are almost negligible.

As acquisition in this case is not measured by purchases and, instead, users using the site and feeding the AI with data, even unregistered users are helping Shein to improve its service and build its brand.

The higher the demand the more data is gathered, allowing Shein to make shrewder decisions and offer lower prices (bulk orders are always more cost-effective). 

This feeds into the user experience, which improves exponentially and drives customers to keep returning to the site, giving Shein more money to spend on marketing.

This cycle can continue, becoming more efficient and more effective over time, creating a competitive advantage that is increasingly difficult for other retailers to match.

What can traditional retailers learn from Shein?

One of the driving forces behind Shein’s most recent success was the Covid-19 pandemic in 2020. 

Where other retailers struggled to pivot and alter important elements  of their business such as what they sell, how and to whom, Shein’s business model is designed around allowing the customers to choose what they want and how they want it. 

The secret to this success is more than intuition – it is technology.

We are living in an internet age where businesses that rely on traditional forms of production, marketing and selling will consistently come up against businesses who are leaning into technology and are thus always one step ahead.

AI offers today’s retailers an opportunity to personalise their business experience for their specific audience, understanding customers not only as they are today, but as they will be tomorrow. 

With algorithms putting the work in to create personal buying journeys for your target audience, your business is free to focus your resources on the top of the sales funnel – building visibility and making first contact.

AI tools can help retailers to improve the accuracy of their demand forecasting and optimize product placement on their sites and social media. 

An integrated system combines these insights with predictive analytics that can ensure your inventory holds more of the stock that is popular, and less of what is not, and keeps every link in your supply chain up-to-date with what is needed in real time, saving money and preventing excessive waste.

As the brand continues to dominate the world of fashion retail globally, it is clear that the traditional retail industry has to invest in new AI tools for analysis – otherwise they cannot hope to compete with Shein.

This is how we do it

Norna is a Swedish startup dedicated to disrupting the retail industry – giving traditional retailers a competitive edge against tech giants like Shein and Amazon.

Our team features a roster of skilled scientists, designers, product managers and engineers, who have banded together to create Norna Analytics – an advanced tool that helps you to understand your target market and manage your business in much the same way as Shein. 

Our tool monitors and analyses changes on the websites of all major fashion companies. It  provides real-time access to information about new products, price changes and discounts – and even insight into strategic decisions such as assortment composition and colour opportunities.

Find out more or contact co-founder Michael Collaros michael.collaros@norna.ai

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