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“The days of relying on size charts and body measurements for predicting sizes are over. Easysize’s in-depth knowledge of user’s style and fit preferences is something that sets them apart.”

Ilan Benhaim
Co-founder & Director of Strategy and Innovation

Case study

vente-privee

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How flash sales pioneer vente-privee used Easysize to help shoppers find the right size

Overview

vente-privee is a French e-commerce company that pioneered the model of online flash sales. Founded in 2001, the company today has more than €3.3bn and is one of only three unicorns (private companies valued at more than $1bn) in France. Online sales are exclusive to its 70 million members worldwide. Sales are for a limited time only (3 to 5 days) and are organised in close collaboration with over 7000 major international brands in all product categories: ready-to-wear, homewares, wine, toys, sports, high-tech, etc.

Challenge

vente-privee’s members have an access to exclusive deals from thousands of international fashion brands. Sizes often vary between brands leaving shoppers with a challenge to find the right one, and do it while a sale is still active. This all leads to confusion among shoppers – some of them end up buying the wrong size, some will buy several sizes of the same item to try it at home.

Goal

vente-privee had a goal to decrease the number of size-related returns and boost user confidence by providing the right size.

“Easysize is able to help millions of customers at scale and in a way that is authentic and informed by rich data.”

Ilan Benhaim
Co-founder & Director of Strategy and Innovation, vente-privee

Initiatives

Easysize was first launched on vente-privee.com in November 2017 on the French versions of the website. Easysize’s approach to solving the sizing issue is focused on analysing shoppers' previous purchase and return history – to better understand their individual style and fit preferences. Due to the nature of sales (flash-sales and campaigns that run for a limited time), it was crucial to provide the right recommendation for every SKU, every shopper and every campaign. Easysize was able to achieve this due to its data-driven technology, that doesn't use any size charts or measurements. Instead, it analyses purchase and returns from shops and hence can instantly scale its recommendations to all brands sold on the website. One of the biggest differentiators of Easysize from other sizing solutions is the seamless user experience. Easysize doesn't require any inputs from shoppers and auto-recommends the right size to all regular shoppers. It allows Easysize to engage with a significant number of orders and have a notable positive impact on vente-privee’s overall key metrics.

Results

Easysize size recommendation was used in 22% of all purchases. By auto-recommending the size to shoppers, vente-privee was able to lower its return rate by 14%. In addition, the sales conversion (from a page view), when the recommended size was shown, increased by 35%. Easysize helped prevent 4% of all returns at vente-privee.

Increase
sales conversion

Decrease in
return rate

Why this approach to solve the sizing issue was chosen

The majority of sizing solutions engage with shoppers only when shoppers click a dedicated button on a product page (usually “Find my size” or “What’s my size”). Shoppers are then asked to take a size quiz and add their measurements or brand references. Click-through-rate of “Find my size” button is usually in the range of 1-3%. It means that only a very small number of orders end up being created with the right size recommendation. In the contorary Easysize directly engages with almost a quarter of all orders (in this test this number was 22%) by auto-recommending the size, resulting in a significant impact on the overall return rate. It was done in a way (auto-recommended sizes) that didn’t require any actions from shoppers – shoppers simply saw the auto-recommended right size on the product page. This allowed vente-privee help those shoppers who needed it the most and engage with nearly a quarter of all orders.

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