Creative Intelligence: The Future of Advertising Optimization?

In this exclusive interview, Florent Yon, Media Manager at Converteo, and Fabrice Courdesses, CEO of VideoRunRun, share their insights on Creative Intelligence and its critical role in optimizing video ad campaigns.

Creative Analysis: The Underutilized Lever of Advertising Performance

While creative accounts for nearly 70% of advertising performance, it remains far less developed than audience targeting or media activation. How can Creative Intelligence unlock its full potential?

Customization and Continuous Optimization: The Keys to Success

Every platform demands tailored content. Creative testing and iterative improvement should be integrated at the early stages of campaign development.

AI and GenAI: Powerful, But Not a Silver Bullet

Artificial intelligence enables large-scale personalization and optimization, but human creativity remains indispensable for delivering authentic, emotional impacts.

Why is creative analysis still the last under-leveraged pillar of media performance, alongside audience targeting and media activation?

Fabrice Courdesses, CEO of VideoRunRun:

The industry still operates within a siloed Media vs. Creative approach. Many hesitate to challenge the creative, treating it as untouchable. This is particularly true in France, where prestige awards like the Cannes Lions reinforce the notion of creative sanctity.

Additionally, the legacy of TV advertising has conditioned brands to push non-skippable ads, relying on repetition and brand lift. Today, creative analysis is often quantitative—focusing on “what works and how much”—but lacks qualitative depth to uncover the “why and how.”

In performance marketing (e.g., SEA or Display), optimization is straightforward—a simple button color change can double key performance indicators instantly. Video advertising, however, is more complex, involving multiple elements (sound, visuals, sequencing) that require deep-tech solutions like Computer Vision, Machine Learning, and Data Science to decode campaign success or failure.

Florent Yon, Manager at Converteo:

There’s a paradox in advertising: while creative has the greatest impact on performance, its analysis lags behind audience segmentation and media activation.

This is due to the technical complexity of analyzing video creatives and the proliferation of formats, making measurement more challenging.

According to Kantar*, 78% of advertisers struggle to consistently measure the impact of creative across platforms. The lack of standardized methodologies and the rapid evolution of digital advertising further complicate the process.

What advice do you have for advertisers?

Fabrice Courdesses:

The biggest mistake is assuming a single video will perform well across all platforms.

Each platform has its own DNA, rules, and audience expectations. TikTok users, for example, consume content in a radically different way than those on YouTube or Instagram. What works on one platform might flop on another.

Video content must be designed upfront with platform-specific adaptation in mind.

Moreover, creative testing should be part of the process from the start—integrating analysis from the early process enables continuous improvement and higher performance. That’s how you build an effective creative strategy.

When should brands leverage creative analysis tools?

Fabrice Courdesses:

We see three key use cases for Creative Intelligence:

1. Boost performance in Walled Gardens, where users can skip or click. Simply switching a sequence can X2 a KPI.
2. Enhance qualitative Attention—not just forced exposure—in programmatic OpenWeb, where formats are often non-skippable/non-clickable. Attention in OpenWeb is more about recall than sentiment. Seeing the same ad four times during a streaming session may boost recall but not necessarily brand perception.
3. Build long-term creative intelligence, by developing actionable “Data-Driven Creative Guidelines” tailored by platform and market. These guidelines improve creative briefs and optimize post-production, which directly impacts the success of digital ad campaigns.

How does Creative Analysis fit into the broader video advertising strategy?

Florent Yon:

Our methodology is anchored in a structured Learning Agenda that orchestrates creative tests methodically, enabling us to generate guidelines backed by data. Each campaign becomes an opportunity to extract insights that optimize future strategies.

To refine our recommendations, we prioritize measuring ad recall, engagement, and interaction quality across different platforms and audiences.

What’s your methodology for analyzing and optimizing video creatives?

Fabrice Courdesses:

Our approach is technical and data-driven.

Using Computer Vision and AI, we analyze every element in a video—text, speech, visuals, emotions, sequencing, etc. We overlay this with an advertising framework that categorizes key elements such as:

• Narrative structure (hook, arguments, outro)
• Attention drivers (people-centric content)
• Interest factors (product-centric content)
• Action triggers (CTAs)

This creates a rich dataset that powers our predictive Machine Learning models, aligned with branding or performance KPIs.

We then segment analyses based on practical use cases, allowing advertisers and agencies to take targeted actions—by country, influencer type, audience segment, funnel stage, etc.

Last but not least, a Creative Strategist interprets the data to deliver actionable insights within the brand’s unique creative and marketing framework..

How does your tech optimize video creatives across platforms (YouTube & other video ad platforms)?

Fabrice Courdesses:

Our technology is built to fit each platform guidelines, from YouTube’s ABCD framework to Meta’s best practices and TikTok’s unique engagement patterns. Beyond these guidelines, we also integrate historical campaign data across all platforms to refine predictive models further.

We approach optimization in three key phases:

• 1- Before the campaign (Predictive Analysis): Anticipating performance through creative pre-tests before going live, securing better efficiency and maximizing ROAS.
• 2- During the campaign: Providing real-time creative analytics to iterate and adjust during the campaign.
• 3- After the campaign: Extracting learnings based on data, to enhance future creative strategies and agency briefs.

What Key Recommendations Should Advertisers Follow to better integrate Creative Analysis into their decision-making process?

Florent Yon:

We recommend focusing on three fundamental pillars:

• Platform-specific creative adaptation
• A unified measurement framework for cross-channel creative performance
• Integrating creative analysis from the initial campaign design phase

This holistic approach significantly enhances the impact of ad investments.

Best practices for implementing a continuous creative optimization process?

Fabrice Courdesses:

Creative optimization is like training a sports team—play, analyze, learn, and come back stronger for the next game.

Our golden rules:

• Have a cross-functional lead to break down silos between Creative, Media, and Data teams.
• Use YouTube Ads as a testing ground—it’s the perfect lab covering all formats, devices, and objectives.
• Never launch just one creative—variations can 5X performance. It’s time to apply A/B testing principles from SEA/Display to video ads.
• Consider creative within its distribution context—as the saying goes, “Creative is king, but distribution is queen, and she wears the pants.”
• Build a continuously evolving Creative Playbook, tailored to your brand and audience, campaign after campaign.

What’s your take on using GenAI for video ad creation and optimization?

Fabrice Courdesses:

GenAI is creating a new category of video ads with its own early adopters, awards, and success stories—Coca-Cola’s Christmas campaign being a prime example.

There are two main types of video ads:

• People-based videos, focused on emotion (upper-funnel branding
• Product-based videos, designed for performance (lower-funnel conversions)

Right now, GenAI is excelling at product-based content but still struggles to capture the authenticity required for human-driven storytelling.

Ultimately, KPI performance is what matters. A GenAI-generated video is irrelevant if it’s massively skipped. The ad industry loves shiny new objects, but innovation doesn’t guarantee ROAS—at least, not yet.

That said, it’s a tool we integrate into our process, without sacrificing short-term actionability.

Florent Yon:

The numbers speak for themselves: according to Gartner’s “State of Marketing Technology 2024” report, AI usage in ad content creation has surged by 220% since 2023. However, Deloitte Digital (2023) found that 67% of consumers still prefer human-created content for emotionally driven brand communications.

GenAI is great for post-production efficiency and large-scale content personalization, but full automation is a trap.

Human creativity remains irreplaceable—AI is a powerful tool, but it doesn’t replace a great creative idea.

*Kantar « State of Digital Advertising » (2023)