Philadelphia, PA, May 29, 2020 (GLOBE NEWSWIRE) -- VSBLTY Groupe Technologies Corp. (CSE: VSBY) (Frankfurt: 5VS) (OTC:VSBGF) (“VSBLTY”), a leading retail software technology company, in partnership with IMG, a global leader in sports events and media, conducted an audience study at the 106th Rose Bowl Game in Pasadena, Calif. on January 1, 2020. The research captured operational and marketing data that will help operators of entertainment and sports venues make informed decisions on staffing levels and guest experiences.
Jay Hutton, VSBLTY Co-founder and CEO, said, “Traffic count and other venue data collected, when combined with machine learning, can help improve operational efficiencies and venue logistics. Facts about fans, their habits and actions—in addition to demographic and psychographic information—will help plan audience activities as well as serve as a tool to validate the value of on-site advertising impressions to sponsors.”
To collect key audience information through signage analytics, high tech video cameras combined with video display signage were strategically placed in front of the stadium where more than 90,000 Oregon and Wisconsin fans attended pre- and post-bowl activities.
VSBLTY technology provides enhanced customer engagement and audience measurement using machine learning and computer vision. Its industry-leading VisionCaptor™ and DataCaptor™ software combine motion graphics and interactive brand messaging with cutting-edge computer vision measurement and insights. VSBLTY’s AI-driven software, Vector™, provides advanced facial recognition that is crucial to enhancing today’s security requirements when recognizing weapons or suspicious persons in a crowd.
Along the pathway to the stadium four cameras were deployed at different locations among “Fan Fest” activities that included two FESCO units displaying archived player videos and advertising messaging. The VSBLTY technology counted individual fans, documented both age and sex, recorded what they watched on video screens and for how long, collected 30,000 impressions, as well as the percentage of views per impression. The test also showed who watched what commercial messages, for how long, and what kind of information attracted and held interest.
Knowledge of the male-female attendance ratio will enable sports and entertainment venue operators to better plan the ratio of male-oriented content to female-oriented messaging. That same ratio information will help advertising sponsors decide what kind of messaging will work best at specific events.
The Rose Bowl Game test showed that pairing advertising and player/legacy videos would likely drive up commercial messaging impressions. Video advertisers at sports, entertainment and transportation venues can learn in real time who, by sex and age, is watching their messages and for how long—much like the information provided by traditional media rating services.
The study showed that dwell times for both commercial and sports content decreased over the course of the day and that suggests that changing pre- and post-game content should be considered. Improved viewership could be achieved by segmenting messages by length. Short messages should be near venue entrances while longer content should be placed were people are more likely to dwell.
Younger fans watched two times more videos than those over age 40 and did so for longer periods. Women’s interest in the video messaging far exceeded that of men, who recorded some 50 percent less dwell time.
The strategic use of digital signage paired with machine learning and artificial intelligence to understand how audiences act and react is proving to be one of the most important and effective audience analytics tools for sports and entertainment venues.
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About VSBLTY (www.vsblty.net)
Headquartered in Philadelphia, VSBLTY (CSE: VSBY) (Frankfurt: 5VS) (OTC: VSBGF) (“VSBLTY”) is the world leader in Proactive Digital Display™, which transforms retail and public spaces as well as place-based media networks with SaaS-based audience measurement and security software that uses artificial intelligence and machine learning.