AdTheorent’s Solutions Leverage Machine Learning Technology and Cross-Channel Management Capabilities to Provide Real-Time Ad Optimization with Improved Return on Investment for Customers

Based on its recent analysis of the digital advertising industry, Frost & Sullivan recognizes AdTheorent with the 2018 North American Growth Excellence Leadership Award for its suite of products that offer customers effective predictive advertising, robust cross-channel campaign management capabilities, and pragmatic advertising capabilities while addressing consumer privacy and data security needs.

“AdTheorent is the leading provider of data-driven predictive solutions for digital advertising. The company’s Machine Learning-Powered Predictive Advertising Platform, combined with its cross-environment mapping solution and predictive creative capabilities, outperform other alternatives in the market and help brands connect with their optimal audiences at scale,” said Vikrant Gandhi, Industry Director at Frost & Sullivan.

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AdTheorent leverages its Machine Learning Technology Platform and the Cross-Environment Map measurement capabilities to deliver data-driven, scalable, and transparent cross-channel advertising campaigns. The Machine Learning Technology Platform learns faster and across more data than any other solution in the market, and identifies optimal audiences across various digital channels. AdTheorent’s Cross-Environment Map matches user IDs across all environments and matches them to a single user, allowing advertisers to attribute activity across all environments, all delivered in a de-identified manner which adheres to best practices for user privacy and personal anonymity. Through these solutions, AdTheorent offers managed, results-driven digital advertising that consistently delivers higher value than stand-alone programmatic solutions.

AdTheorent’s digital advertising solutions help customers achieve improved returns on their investments in digital advertising by incorporating innovative features, such as relationship targeting, an advanced predictive creative mechanism, and 360-degree custom video content, into its products. The company follows a performance-based pricing structure, working closely with customers to customize pricing around their unique requirements, which allows products to be both cost-effective and scalable. Examples include a Cost Per Incremental Visit (CPIV) pricing model, as well as other performance-based pricing such as a charge per vehicle registration, service signup, or pharmaceutical prescription sale. AdTheorent further improves the product ownership experience by gathering extensive feedback and reporting to improve product performance. In addition, the company pursues partnerships with leading industry solution providers to expand and improve its targeting and measurement data capabilities.

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“Frost & Sullivan independent analysis indicates that annual revenue growth of AdTheorent has consistently exceeded 75%, and the company consistently beats target customer acquisition goals by 75% as well. These results are a clear demonstration of AdTheorent’s successful growth strategy,” added Vikrant.

Each year, Frost & Sullivan bestows this award upon the company that demonstrates excellence in growth and customer value. It recognizes the superiority of the product/service as well as the overall customer, purchase, ownership, and service experience offered, which has resulted in the recipient company seeing above-market growth and greater share of wallet. The award lauds the growth, diversification, and sustainability strategies of the company.

Frost & Sullivan Best Practices awards recognize companies in a variety of regional and global markets for demonstrating outstanding achievement and superior performance in areas such as leadership, technological innovation, customer service, and strategic product development. Industry analysts compare market participants and measure performance through in-depth interviews, analysis, and extensive secondary research to identify best practices in the industry.

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