Podcast Summary: The Agile Brand with Greg Kihlström® – Episode #703: How AI and Deep Learning is Affecting Advertising with Jason Gillespie, RTB House

Release Date: July 11, 2025

Introduction

In Episode #703 of The Agile Brand with Greg Kihlström®, host Greg Kihlström engages in an insightful conversation with Jason Gillespie, the Vice President and Global Head of Analytics and Product Marketing at RTB House. The episode delves into the transformative impact of artificial intelligence (AI) and deep learning on the advertising landscape, exploring how these technologies enhance advertising effectiveness, personalization, and the future of marketing in a world grappling with the deprecation of third-party cookies.

Guest Introduction

Jason Gillespie brings a wealth of experience from RTB House, where he oversees analytics and product marketing across global markets, including the United States, Europe, and RTB House’s home base in Poland. His role involves aligning market needs with product offerings through comprehensive data analysis and ensuring the seamless integration of AI-driven solutions in marketing strategies.

AI, Machine Learning, and Deep Learning: Definitions and Differences

The conversation begins with a foundational understanding of AI, machine learning (ML), and deep learning (DL). Jason Gillespie explains:

“AI is the least specific and most generic term for computers that are doing something like humans would do...” (04:44)

He differentiates the three concepts using concentric circles:

• Artificial Intelligence (AI): The broadest category encompassing any computer system performing tasks that typically require human intelligence.
• Machine Learning (ML): A subset of AI focused on identifying statistical relationships within data to make predictions, such as predicting credit card payment behaviors.
• Deep Learning (DL): A more specialized form of ML that mimics human cognitive processes, handling vast and unstructured data streams akin to how humans perceive and process information through multiple senses.

Deep Learning in Online Advertising

Jason elaborates on why deep learning is particularly potent in the context of online advertising:

“Deep learning can natively ingest very different behaviors and start to sort them out with enough users over time...” (07:47)

Key advantages of deep learning in advertising include:

• Handling Variability: Ability to manage fluctuating user behaviors and traffic patterns, whether it’s a surge or a drop in website visits.
• Predictive Accuracy: Enhanced capacity to predict incremental transactions, not just attributed conversions, providing a more holistic understanding of advertising impact.
• Incrementality: DL excels in determining the true incremental value of ads by analyzing what happens when ads are and aren’t shown to users, a challenge for traditional ML models.

Enhancing Engagement Across Channels

The dialogue progresses to how deep learning fosters more effective multi-channel engagement through:

• Personalization and Relevance: AI-driven insights enable highly personalized ad experiences tailored to individual user behaviors and preferences.
• Optimal Timing: Unlike ML, which struggles with temporal dynamics, DL effectively incorporates timing into ad delivery, ensuring ads are shown when they are most likely to resonate with users.

Jason shares an example of RTB House’s proprietary technology, Intent GPT, which enhances contextual targeting by intelligently interpreting web content to place ads more strategically:

“AI reads every page and says, wait a minute, this is a gruesome story... Let's put your ad over here...” (19:38)

Role of Humans in AI-Driven Marketing

A significant portion of the discussion addresses the symbiotic relationship between AI and human expertise:

• Automation of Repetitive Tasks: AI can handle mundane tasks such as data entry and basic analytics, freeing up human resources for more strategic and creative endeavors.
• Human Oversight: Despite AI’s capabilities, human judgment remains crucial for overseeing AI outputs, ensuring relevance, creativity, and ethical considerations in marketing strategies.

Jason emphasizes the importance of human intervention in refining AI-generated creative content:

“There's always going to be the opportunity for some AI and then opportunity for a human touch...” (19:36)

The State of Cookies and Advertisers' Strategies

The conversation shifts to the evolving landscape of online tracking, particularly the uncertain future of third-party cookies. Jason Gillespie provides strategic advice for advertisers navigating this transition:

“You always want to be on first party data... first party advertising is doing more with your first party data...” (22:08)

Key takeaways include:

• First-Party Data Emphasis: Building robust first-party data strategies to ensure reliable and ethical data usage.
• Adaptability to Multi-Identity Ecosystems: Preparing for a fragmented identity environment where universal addressability is no longer guaranteed.
• Leveraging Partnerships: Collaborating with technology partners to manage diverse consumer identifiers and maintain effective targeting capabilities.

Conclusion

In conclusion, Jason Gillespie underscores the necessity of embracing deep learning to stay competitive in the dynamic advertising ecosystem. By leveraging AI’s advanced capabilities and maintaining robust human oversight, marketers can enhance campaign performance, drive incremental growth, and adapt to the rapidly changing digital landscape.

Notable Quotes

• Defining AI and Deep Learning:

  “Deep learning mimics the way a human learns... it handles missing values or weird values natively.” – Jason Gillespie (06:30)

• Incrementality in Advertising:

  “Deep learning excels at the true incremental transactions because it understands the holistic view...” – Jason Gillespie (07:23)

• Human-AI Collaboration:

  “AI can generate thousands of creative variations, but humans are needed to identify the truly impactful ones.” – Jason Gillespie (19:36)

• First-Party Data Strategy:

  “The less you rely on third-party data, the better you're going to do with your first-party advertising.” – Jason Gillespie (24:30)

Final Thoughts

This episode of The Agile Brand offers a comprehensive exploration of how AI and deep learning are revolutionizing advertising. Jason Gillespie’s expertise provides valuable insights into leveraging these technologies for enhanced effectiveness, personalized user experiences, and sustainable business growth in an increasingly complex digital environment.

For more information about Jason Gillespie and RTB House, listeners are encouraged to follow the links provided in the show notes.

Note: This summary intentionally omits introductory promotions, advertisements, and non-content segments to focus on the core discussions and insights shared during the episode.