The question is no longer whether marketers have enough data. The question is whether they can predict outcomes before investing budget, launching campaigns, or producing the next round of creative assets.

Every day, marketing teams, creative directors, media buyers, brand managers, ecommerce leaders, and agency partners make decisions that determine campaign success or failure. Yet most organizations still rely on insights that arrive after money has already been spent.
That is why Brunner is excited to announce the acquisition of AdSkate, an AI-powered creative intelligence, synthetic audience, and predictive analytics platform designed to help organizations understand not only what works, but what is likely to work before a campaign launches.

A Pittsburgh Story of Innovation

This partnership reflects what Pittsburgh does best: transforming breakthrough ideas into real-world impact.

For decades, Brunner has helped brands grow through integrated marketing that connects strategy, creative, media, and analytics. AdSkate was built within a technology ecosystem fueled by institutions such as Carnegie Mellon University, widely regarded as a global leader in artificial intelligence, and Penn State University, whose research and engineering programs have helped shape generations of innovators.

By combining Brunner’s marketing leadership with advanced predictive intelligence developed within this innovation ecosystem, we’re building a new model for marketing performance, one that unites human expertise with data science and AI to help brands move faster, make smarter decisions, and create sustainable growth.

From Analytics to Predictive Marketing Intelligence

For decades, marketers have relied on dashboards, reports, surveys, and post-campaign analysis to understand performance. While valuable, these approaches are inherently retrospective. They explain the past.

AdSkate helps brands move into the future.

Using proprietary AI models and synthetic audience technology, marketers can test creative assets against custom-built audiences before campaigns launch. Digital ads, video assets, social content, landing pages, ecommerce experiences, email creative, and messaging frameworks can be evaluated early in the planning process.

Instead of waiting for performance data to arrive after launch, organizations can gain predictive insights about audience response, message resonance, engagement drivers, and creative effectiveness before significant media investments are made.

This allows marketers to move beyond asking “What worked?” and begin asking “What is most likely to work?”

Powered by Synthetic Audiences

One of the most transformative capabilities within the AdSkate platform is synthetic audience modeling. Built using advanced AI techniques, synthetic audiences allow marketers to evaluate creative concepts, messages, visual executions, and campaign strategies against highly customized audience populations.

These audiences create a new layer of decision intelligence that complements traditional research methods. Brands can explore likely audience reactions, identify potential points of friction, uncover opportunities for optimization, and gain directional insight before launching campaigns into market.
The result is faster learning, reduced risk, more informed creative decisions, and greater confidence in marketing investments.

Building Better Creative Through AI

Traditional creative testing often identifies a winning ad. AdSkate takes optimization significantly further.

Through continuous performance analysis, AI can identify the specific visual, emotional, messaging, structural, and audience-related attributes contributing to success across multiple creative assets.
Rather than selecting a single winning creative execution, marketers can isolate the highest-performing components from numerous ads and use those insights to inform the next generation of creative development.

This creates the opportunity to build champion creative informed by the strongest-performing attributes discovered across campaigns, audiences, channels, and formats.

As campaigns continue to generate performance data, the system continuously learns, identifies emerging patterns, and provides recommendations that help improve future creative effectiveness.