Revolutionizing B2B Advertising with Real-Time Data
Real-time data advertising is rapidly transforming the way agencies create and optimize campaigns, especially in the B2B sector. Multiply, a media agency startup, is at the forefront of this shift. By leveraging proprietary AI technology and a data-driven approach, Multiply delivers self-learning ads that evolve in response to real-time customer insights.
Multiply’s Vision: Adaptive Ad Campaigns in Real Time
In March 2026, Multiply emerged from stealth mode to announce a $9.5 million seed funding round. Backed by investors such as Mayfield, Sorenson Capital, Max Mullen of Instacart, and industry leaders from HubSpot and Braze, the agency has set out to redefine how B2B companies approach real-time data advertising.
CEO and co-founder Matt Jayson emphasizes the importance of ads that adapt as quickly as their target audiences. With a lean team of 13, Multiply plans to allocate much of its new funding to hiring strategists who can enhance both the human and technical sides of their offering.
Integrating Real-Time Signals for Smarter Ads
Currently, Multiply focuses its efforts on LinkedIn and Google Ads, with expansion plans into Meta, Reddit, and even ChatGPT in the near future. The agency’s proprietary AI software constantly tracks live data signals—such as brand sentiment, customer interactions, and ad performance metrics—to generate new ad versions tailored for B2B audiences.
Despite their AI-driven approach, Multiply insists on maintaining a human touch. According to Jayson, B2B clients often hesitate to hand over full control to artificial intelligence due to concerns around cost and brand safety. To address this, every AI-generated ad goes through human review before reaching clients, ensuring strategy and creativity remain closely aligned with client goals.
Blending Human Expertise with AI for B2B Success
B2B marketing presents unique challenges, as much of the valuable data exists within sales teams’ conversations rather than in public datasets. Multiply’s solution involves direct integration with sales call recording platforms and CRM systems. By analyzing sales calls, customer testimonials, and even LinkedIn data, the AI can identify key phrases and sentiments—insights that inform new ad iterations.
For example, if a particular benefit or product feature is frequently praised by customers, Multiply’s AI highlights that in new ad versions. The agency’s approach to real-time data advertising means each campaign is not static; instead, it evolves as new data becomes available, allowing for continual refinement and improvement.
Self-Learning Ads: Continuous Optimization and Feedback
The concept of “self-learning ads” is central to Multiply’s philosophy. The platform continuously tests different audiences, creatives, and messages, using performance feedback to drive future ad development. Each audience segment—from salespeople to CFOs—receives tailored messaging, maximizing relevance and engagement.
Multiply’s “insatiable ad agents” never settle for current results. As soon as a version starts underperforming, the AI suggests or generates new variants, always aiming to boost click-through rates and conversions. This dynamic feedback loop is the hallmark of effective real-time data advertising and is set to become a best practice in the B2B space.
The Future of B2B Advertising: Human-AI Collaboration
Multiply’s journey highlights the importance of combining advanced technology with strategic human oversight. As more agencies and brands embrace real-time data advertising, the industry will likely see a shift toward more dynamic, responsive campaigns that mirror the ever-changing preferences of professional audiences.
By prioritizing transparency and client involvement, Multiply addresses common AI adoption barriers while offering the benefits of automated optimization. The result is a new standard for B2B marketing—one where ads are always learning, adapting, and improving in step with the people they’re meant to reach.
This article is inspired by content from Original Source. It has been rephrased for originality. Images are credited to the original source.