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StackAdapt: Leading the Way in Programmatic Advertising

Author image Published by [email protected]
Published Date 26.04.2023

Here at StackAdapt, we’ve earned the reputation as the premier self-serve advertising platform, specializing in multi-channel solutions that include native, display, video, connected TV, audio, in-game, and digital out-of-home ads. 

The company is designed around the three core pillars of programmatic—planning, executing, and analyzing—which results in a state-of-the-art programmatic platform where some of the most progressive work in machine learning meets cutting-edge user experience. Ad buyers can plan, execute, and manage data-driven digital advertising campaigns across all devices, inventory, and publisher partners using the StackAdapt platform.

Our team includes leading experts who understand the business of agencies and advertising. They offer stellar implementation, onboarding, and always-on customer service to help marketers insulate themselves and their clients from risk. The team believes that campaign success comes through establishing partnerships and providing end-to-end campaign strategy and management that is easy and effective.

In early 2020, StackAdapt had 187 employees across two countries. Since then, we’ve expanded rapidly to over 1,000 employees across 12 countries with revenues north of nine figures in just nine years of operation (StackAdapt was founded in 2014). Despite a challenging environment, including the rise of CTV and retail media networks, the deprecation of cookies, and the COVID-19 pandemic, StackAdapt has continued to surge forward to become a leader in the ad tech market.

For example, we’ve differentiated ourselves from other programmatic platforms by exclusively building a programmatic platform using machine learning and AI from the beginning. This approach puts StackAdapt at a distinct advantage over other programmatic platforms that are adapting to new AI tech at the moment. StackAdapt’s system is also not only more effective but also entirely privacy-compliant, which is increasingly important as identifiers such as cookies decline in importance.

Although StackAdapt has heavily focused on new partnerships and multi-channel solutions over the last year, with the advertising conversation currently focused on contextual advertising, we decided to have a large part of our award submission speak towards our latest contextual solution.

Our Page Context AI is a powerful tool that enables marketers to reach a target audience in a more personalized and effective way. By analyzing the content of web pages, StackAdapt’s AI provides real-time insights into what topics and themes are being discussed, allowing marketers to serve ads that are relevant to the content on the page and more likely to resonate with the viewer. We utilized case studies that prioritized Page Context AI, such as our work with omnichannel-first agency Matrixx Shopper Marketing to demonstrate its efficiency and effectiveness. 

In recognition of our innovative contextual approach and exceptional case study results, StackAdapt has been named a 2023 finalist in the Global Business Tech Awards. Entering into this award was not just about garnering recognition for StackAdapt, but to celebrate the hard work and dedication of everyone who has contributed to our success.

“The award nomination means everything to our StackAdapt family,” said Vitaly Pecherskiy, Chief Operating Officer at StackAdapt. “It is recognition for all the hard work we have put in over the years, and an opportunity to celebrate the successes and the milestones we have achieved together. More importantly, it is a testament to the value we bring to our clients and the trust they have placed in us.”

Overall, StackAdapt’s success is evidence to our commitment to innovation, customer service, and staying ahead of industry trends. With a focus on integrating AI, offering contextual advertising, and providing end-to-end campaign strategy and management, StackAdapt is poised to become an even stronger leader in the ad tech market over the next year.

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