Success Story

Predicting what scents make sense

03/11/2015

William Yin, CEO of Scent Trunk. Photo courtesy of Queen's University.

As online shopping becomes more and more popular, a Queen’s University company is using machine learning to make buying scented products easier for online shoppers.

Scent Trunk evolved out of the 2014 Queen’s Innovation Connector Summer Initiative, a 16-week paid summer internship program supported by the Queen’s Innovation Connector (QIC), which forms Kingston's Campus Linked Accelerator with Launch Lab. The company addresses the barrier to online retail of scented products, namely the inability to smell the product before purchase. Scent Trunk is developing a machine-learning algorithm that identifies what someone likes to smell and then sends them targeted scent samples.  

Scent Trunk, which is led by William Yin, Chief Executive Officer, Richard Smale, Chief Operating Officer, and Saqib Dareshani, Chief Technology Officer,  is using machine-learning technology to make the best predictions for consumer preferences. The better the prediction, the better the targeting, the higher the sales conversions and the lower the customer acquisition costs for the company’s brand partners. By analyzing customers’ preferences and responses over time, the company is able to find the colognes that best match each individual.

An exciting recent development for Scent Trunk has been new partnerships with several different brands. As Scent Trunk gains more credibility within the industry, higher-end brands have demonstrated a willingness to partner with Scent Trunk and offer their products through the service.

The company won the Toronto regional competition in the Global Student Entrepreneurship Awards and was scheduled to appear on Next Gen Den, the web-based spinoff of the popular CBC Television show Dragons’ Den  on March 9.

This story was provided by Queen's University.