Cartier’s goal was to develop an app to help sales associates find any watch in its immense catalog quickly. The app would use an image to find detailed information about any watch the Maison had ever designed (starting with the past decade) and suggest similar-looking watches with possibly different characteristics, such as price.
But creating this app presented some unique challenges for the Cartier team. Visual product search uses artificial intelligence (AI) technology like machine learning algorithms to identify an item (like a Cartier wristwatch) in a picture and return related products. But visual search technology needs to be “trained” with a huge amount of data to recognize a product correctly — in this case, images of the thousands of watches in Cartier’s collections.
As a Maison that has always been driven by its exclusive design, Cartier had very few in-store product images available. The photos that did exist weren’t consistent, varying in backgrounds, lighting, quality and styling. This made it very challenging to create an app that could categorize images correctly.
On top of that, Cartier has very high standards for its client service. For the stores to successfully adopt the app, the visual product search app would need to identify products accurately 90% of the time and ideally return results within five seconds.