Image: Hafsa Ennajari & Akinlolu Ojo from Concordia University’s Applied AI Institute along with Pascal Maeder, Urbanoid’s CEO. (photo J.Wenk)

As context-based ad targeting makes its play to solve for a cookie-free future, and first-party data increasingly becomes a privacy-centric focus for advertisers, Montreal’s Urbanoid has launched an AI solution designed to optimize ad bidding and placement without the need for cookies or like-minded tracking.

Code named CTX, the tool simplifies the process for ad platforms to incorporate AI and location-based contextual data to make more effective targeting decisions, while maintaining privacy standards.

Created in collaboration with Concordia University’s Applied AI Institute, CTX is currently a white-label AI software solution that improves the performance of ad campaigns by tracking over 100 contextual variables in real time – ultimately showing advertisers the best location and best time to run an ad for a particular product. 

“Imagine you have someone walking down the street at Bloor and Yonge in Toronto,” explains Pascal Maeder, Urbanoid’s CEO. “It’s 11:45 a.m., and you want to know whether to serve them an ad for a coffee, an umbrella, or a burger.” Through various data points including (but not limited to) weather, mobile phone density, and transit data, Maeder says CTX analyzes it all in real-time, and provides a rating or score. 

“It’s 11:45 a.m…. and it’s sunny,” so the early morning coffee and umbrella ad opportunities are given a low grade/rating on the scale. “But a burger would score very well, because it’s almost noon, and there’s a special for a burger and a drink 50 metres away.”

Advertisers ask their DSP to query the CTX system, and it then provides a score and ranks the ads in question, providing insight into whether an ad will be relevant at a certain time and location, across web, mobile and DOOH inventory.

CTX is still in beta testing mode, white-labelled with select DSPs, and a commercial, CTX-branded version will launch next year, Mr. Maeder says.

The CTX pending patent (categorized under System and Method for Contextualized Selection of Objects in Mixed Reality) was co-invented by Hafsa Ennajari and Akinlolu Ojo, both PhD students specializing in Machine Learning and attached to Concordia’s Applied AI Institute, as well as by Leonid Reinoso, Urbanoid’s CTO.