La Redoute lets consumers snap and buy items directly from print catalog
The company partnered with LTU technologies to use the company’s image recognition software. The Pix&Find application lets users view a description of an item from the catalog and then add it to their shopping bag.
“We implemented the solution to create a bridge between the different channels – the mobile phone and the catalogue,” said Emilie Dedes, ecommerce and mcommerce project manager at La Redoute, Paris.
“The first La Redoute iPhone application, which came out in March 2010, made it possible to order products using catalog reference codes,” she said. “Entering reference codes or, in general, any kind of text entry, proved to be rather tedious on a telephone.
“The objective was to find a playful, rapid, and innovative way to order from the catalogue – or from any printed media – eliminating textual entry.”
LTU technologies delivers image recognition software and solutions to retailers and marketers that help them gain customer information.
The La Redoute application merges the offline print catalog and the online shopping experience using image recognition.
Users can take a photo of an item in the catalog using the application.
Then, the photo is analyzed by LTU’s technology and the user will get more information about the product.
“Thanks to visual recognition, Pix&Find represents a new way to use the iPhone and its camera for accessing information,” Ms. Dedes said. “The recognition stays effective despite variable conditions when the photo is snapped.
“No keyboard entry is necessary, which simplifies the clients search for products and simplifies ordering,” she said. “It represents an alternative to 2D bar code, which are too intrusive and not always appropriate for the medium.”
According to the company, they chose image recognition as opposed to QR codes to make it easier for more consumers to access product information, as well as buy directly from the application.
“La Redoute plans to continue its advancement in mobile and equally in image recognition,” Ms. Dedes said.