A Story of Two Campaigns

Picture this:

A global retail brand launches a holiday campaign. One campaign uses only Dynamic Creative Optimisation (DCO). The other blends DCO with Reinforcement Learning with Human Feedback (RLHF).

• In the DCO-only campaign, the ad server pushes out thousands of variations of taglines, product shots, and CTAs tuned by OpenRTB signals and audience cohorts. Click-through rates climb, fill rate improves, and the DSP reports good CPM optimisation.
  
  
  

• But then comes the backlash. One tagline, automatically generated for GCC markets, doesn’t align with local cultural norms. Another creative in the US misses the tone of the brand voice. Performance is good, but brand trust takes a hit.
  
  
  

Now, compare this with the RLHF+DCO campaign. Here, a creative AI first generates multiple scripts and headlines. The brand’s creative team ranks them. RLHF fine-tunes the model to learn the human taste. When DCO delivers variations across SSPs, DSPs, and the Ad Exchange, every output is not only optimised for performance but also aligned with human judgment.

That’s the difference between automation and generative optimisation with human feedback.

What is RLHF (Reinforcement Learning with Human Feedback)?

RLHF is the secret sauce behind systems like ChatGPT. Instead of letting AI decide purely based on data, humans guide it by ranking outputs.

• In advertising: This means humans teach AI what feels authentic.
  
  
  

• Example: A DSP generates multiple video scripts. A creative team picks the ones with the right humor and empathy. The model then learns to generate better future outputs.
  
  
  

RLHF injects brand safety, empathy, and cultural nuance into programmatic pipes.

What is DCO (Dynamic Creative Optimisation)?

DCO is the assembly line of programmatic creatives.

• It mixes and matches headlines, images, CTAs, and formats (HTML5, native, video, interstitial) based on audience data, device, or GEO.

• Instead of one-size-fits-all, brands run thousands of personalised creatives at scale.

Example:

• APAC: A user in Singapore sees festive banners in Mandarin.

• EU: A shopper in Berlin sees winter imagery and a price in euros.

• GCC: Ads adapt with culturally sensitive greetings.
  
  
  

DCO maximises fill rate, improves viewability, and ensures floor price management across the ad exchange.

RLHF + DCO: Generative Optimisation in Action

When RLHF and DCO converge, we move from simple automation to generative optimisation, where ads are not only dynamically generated but also human-aligned.

• Guardrails: RLHF ensures that ads generated by DCO never cross brand tone or cultural lines.

• Continuous feedback: Creative teams feed results back into the loop, alongside A/B test data and programmatic bid shading insights.

• Scalability: DCO handles the heavy lifting across SSPs, DSPs, and publishers, while RLHF preserves human values.
  
  
  

Use Case:
A streaming platform launches a new thriller series.

• DCO: Automatically adapts trailers, thumbnails, and taglines for cohorts (e.g., action fans vs. mystery fans).

• RLHF: Ensures humour in ads doesn’t feel offensive, and tone stays aligned with the brand voice.

• Outcome: Higher CPM optimisation, stronger viewability, and zero brand-safety incidents.

Why Advertisers Should Care

1. For DSPs:
   
   
   

   • RLHF ensures generated ads resonate with audience cohorts, not just click metrics.

   • DCO drives conversion lift by matching creatives with intent signals.
     
     
     

2. For SSPs:
   
   
   

   • DCO boosts inventory monetisation across ad exchanges.

   • RLHF maintains MRC standards for viewability and safety.
     
     
     

3. For Brands:
   
   
   

   • RLHF enables creative directors to “train” AI in their brand's voice.

   • DCO scales that voice across global GEOs with precision.
     
     
     

The Bigger Picture: Art Meets Science

Advertising has always existed at the intersection of art (storytelling) and science (performance).

• RLHF is the art. It captures tone, taste, and human judgment.

• DCO is the science. It delivers personalisation at scale with programmatic precision.

• Generative optimisation is the marriage. Machine-generated creatives shaped by human feedback, deployed through programmatic pipes across SSPs, DSPs, and exchanges.

Final Thought

The next era of advertising won’t be about machines replacing humans. It will be about machines learning from humans and humans scaling their creativity through machines.

With RLHF + DCO, every ad impression can be both human-shaped and AI-optimised. That’s not just automation. That’s generative optimisation for the advertising age.