Easysize is evolving from being a sizing solution to an AI-driven return prediction platform. We comprehensively analyse customer behaviour…
Easysize is evolving from being a sizing solution to an AI-driven return prediction platform. We comprehensively analyse customer behaviour and automatically identify which carts are likely to be returned.
Easysize started nearly four years ago with an ambitious goal to decrease returns in fashion e-commerce and solve the so called sizing issue (e.g. challenges with picking the right clothing and shoe size), that has been puzzling the minds of industry experts for decades.
Over the last couple of years we have been fortunate to work closely with and learn from some of the largest fashion online-retailers and iconic fashion brands across the world. These collaborations helped us realize the need to expand our product to address e-commerce returns not related to sizing. Today, I am excited to announce the launch of this new improved product.
Returns in fashion e-commerce of the future
Returns have always been a controversial topic in fashion e-commerce.
On one hand, nearly 20–25% of fashion bought online is returned and globally the industry spends around $63B / year on handling returns. These costs not only include shipping, delivery, packaging, but also loss/damage to inventory, revenue loss due to need to discount returned merchandise, increase in customer acquisition and retention costs, inventory costs, and so on.
On the other hand, returns are an important part of the shopping experience. For the majority of shoppers having a free and seamless return experience is a game changer. According to the latest research by PostNord, 64% of online shoppers in Europe say that an easy return process is one of the key factors while shopping online.
This dichotomy puts a huge pressure on e-commerce operators. How does one minimize the costs of returns, when a permissive return policy is an essential part of customers’ choice and their shopping experience?
Easysize has a solution. We believe, that there are 2 key components in a successful strategy aiming to decrease returns:
1. Understand why shoppers return — not what they write in the return forms, but their true motivation.
2. Prevent returns before they happen — e.g. before a shopper purchases an item or the item is shipped.
Understanding the true nature of returns
Some returns are absolutely necessary — let’s say a wrong item was shipped, or an item was damaged — shoppers must be able return these orders without any extra hassle. But not all returns are the same.
The majority (70–75%) of returns in fashion e-commerce happens because a shopper made a mistake while purchasing, while in some cases, the shopper placed an order with the explicit intent to return (some or all) of the order. These behavioural returns are redundant and can be prevented.
Here are some common scenarios:
- Wrong size: Sizes differ dramatically between brands, making it hard for shoppers to choose the right size when buying online.
- Cancellations: Mostly happen with cash-on-delivery purchases.
- Buy-to-rent: A shopper buys an item to wear it for a special occasion, saves the tags, sends it back, and claims a full refund.
- Resellers: A shopper buys dozens or hundreds of items at a discount, then resells some of them and returns the rest.
- Instagrammers: A shopper buys fashion items for the sole purpose of taking photos for social media and then returns them after that.
- And many other examples, when shoppers abuse return policies or simply make mistakes.
At Easysize we built an algorithm that analyses shopping and return patterns of customers in order to predict the right size; this was out first product with which we have served our customers since 2014. We have since expanded this product to also identify the return risks of individual shoppers, items, and brands. Together, our analysis now provide us with all the necessary clues to identify and predict unnecessary behavioural returns.
Most importantly, our data, our algorithm, and our product is not limited to a single shop. Our data comes from shops across the globe. By monitoring shopper behaviours, and item performance across different shops, we’re able to have a deeper and a better understanding of return risk of each cart that is being created.
Providing real-time actionable insights
Our algorithm carefully evaluates each item added to the cart in real-time and estimates a probability of a return. If an item or a cart is flagged as a high risk, we notify the online-shop and advice a potential reason for a return.
We don’t divide shoppers into “bad” and “good”. Instead we evaluate a combination of a shopper’s historic pattern with a specific product and brand added to each cart. We then flag items and carts that may be returned. We do that because a human behaviour is complex. You might be a great customer, when buying t-shirts, but a risky one, when buying jeans (because you like getting a few items to try them at home). We also believe that user behaviour changes all the time, so does the risk of returns.
It’s key that the online shop can take an immediate action and prevent unnecessary returns from happening — before it’s too late, the order is placed, items are packed and shipped, and money and resources were spent handling the return.
With our new product, your shop has the freedom to implement custom rules and address different types of returns in a way, that is the most appropriate for your shoppers.
For example, the correct size can be shown on a product page or a checkout, if a customer is likely to make a mistake.
Alternatively, your shop can offer free express delivery to shoppers and carts that have low return score, driving customer loyalty through unexpected delight. Shops can also take preventive measures towards carts that are likely to abuse return policies by applying different delivery or payment options etc.
We tell shops what and why will be returned in real-time and let them act on this.
The big picture
Fashion is an industry that has a long-standing problem with sustainability. Excessive returns contribute largely to this problem — from the obvious carbon emission associated with logistics to overstocking (in order to keep enough inventory).
Our mission is not simply to help a single business or a shop be more profitable and sustainable. We aim to reshape the entire fashion e-commerce industry by preventing waste and help educate customers to embrace more responsible consumption.
We help online shops to reduce over-consumption and over-stocking items that will not sell or will be returned. We reduce the waste of manufacturing, storing, shipping, and at times destroying the merchandise. We’re committed to making e-commerce more economically and environmentally sustainable. At the end of the day, we believe that this is exactly what the world needs; less waste, more happiness.
– Gulnaz Khusainova, Founder and CEO at Easysize.
Curious to see how our new product works? Check our updated website at easysize.me or drop us a line (firstname.lastname@example.org).