MobileFuse Unveils Proprietary Machine Learning Platform, Advances Traffic Shaping Capabilities, Reduces Carbon Emissions and Costs Further
MobileFuse, one of the largest in-app, CTV, and DOOH advertising platforms, unveiled Braid, its proprietary machine learning platform. The platform will initially focus on optimizing traffic shaping, providing increases to programmatic efficiency and a reduction of unnecessary bloat.
The platform offers unique benefits to both publishers and advertisers alike. For advertisers and demand side partners, Braid learns the specific criteria each bidder requires or focuses on. From there, it delivers exactly what bidders need to meet campaign goals. This creates new operational efficiencies and cuts down on unnecessary data and processing as advertisers only receive opportunities that match their needs. Most traffic shaping solutions take an aggregate look at what ad buyers are interested in, and then sell inventory that aligns to that analysis. Braid is unique in that it looks at each individual buyer, and decides what to send to that platform specifically. This solution demonstrates MobileFuse’s commitment to providing innovative tools for brands and advertisers at scale, especially as they look to optimize results.
“Now is the time to implement machine learning in this capacity – especially with rapid changes happening around privacy, cookies and device IDs. As each new regulatory change influences which devices and creatives bring the largest impact, the Braid platform ensures we can match each buyer’s needs with the best match,” said Ken Harlan, Founder and CEO of MobileFuse. “Additionally, these new capabilities further reduce our carbon emissions. As our solutions provide more curated opportunities to bidders, that reduces unnecessary server pings across the board and ultimately drops our carbon emissions even further.”
MobileFuse’s proprietary machine learning platform represents a defining moment for its tech stack. It is built in a way that enables the company to quickly add new capabilities and features, and uncover data-driven insights that lead to constant optimizations. Altogether, this ensures more effective campaigns for the company’s advertiser clients, and better revenue for publishers.