Easysize for flash-sales

The right size for every campaign and shopper

Your shoppers have a limited time to make a purchase decision – only while a campaign is active. If they’re not sure about the size, they most likely will not purchase at all or purchase several sizes, which adds more burden on the inventory and increases returns. Easysize is here to help!

Tailored for flash-sales

We sufficiently work with your data: time limited campaigns, ever-changing inventory, spontaneous user behaviour driven by offers.

Rich data

Using data across 15,000 brands and 7million SKUs, our algorithm knows, when brands change their sizing and how sizes correspond between brands.

Flexible integration

With modern RESTful APIs, a JavaScript snippet, and mobile SDKs, getting up and running couldn’t be easier.

Easysize for flash-sales

Recommend the right size for higher conversions and lower returns

Easysize seamlessly integrates onto a product page to pre-select the right size or provide useful size tips. Everything happens automatically when the page is loaded – no customer inputs required.

Repeated shoppers First-time shoppers
Shoppers with an existing history of orders and returns receive an auto-recommendation of the right size for every product. The size is calculated based on their individual style and fit preferences.
New shoppers can follow useful size tips (customised for each product) to make better decisions. It helps boost user confidence and doesn’t require any extra inputs.
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, vente-privee

Our impact

What can you expect?

  • +30% in sales conversion
  • -15% in returns
  • Improved user confidence with every purchase

VP logo

vente-privee is a French e-commerce company that pioneered the model of online flash sales. Learn more how we help them to target size related returns.

Read case study