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Real Emotion, Real Results (Letterfest)
Project type
Illustration ads
Project Title: "Real Emotion, Real Results": Data-Driven UGC for Letterfest Client: Letterfest (Personalised Portraits)
The Brief: To create a high-converting video campaign for Letterfest's "Daddy & Me" personalised illustrations. The objective was to move away from polished studio ads and utilize a User-Generated Content (UGC) aesthetic to build authenticity, trust, and relatability with the target audience (partners buying gifts for dads).
The Approach: I personally filmed and directed this campaign on location, capturing genuine interactions between models to simulate a real family breakfast and gift-giving moment. The visual strategy focused on "unpolished" authenticity—handheld camera movement and natural lighting—to blend seamlessly into social media feeds. However, the core strategy lay in the narrative testing. I didn't just create one ad; I built a framework for creative testing.
Key Challenges & Solutions:
Optimizing the "Scroll-Stop": A single script isn't enough to guarantee performance in modern feed algorithms. I developed varying angles of narration with distinct "hooks" to test what grabbed attention fastest. These ranged from humorous relatable confessions (e.g., "I'm not saying I cried, but...") to more sentimental, heartfelt openings.
AI-Driven Narrative Variations: To produce these variations efficiently, I used ElevenLabs to generate the voiceovers. This allowed me to rapidly test different tones—from a casual, conversational "dad voice" to a more emotional delivery—without the time and cost of re-recording a voice actor for every script tweak. This data-driven approach allowed us to identify exactly which narrative hook stopped the scroll.
Outcome: A suite of authentic, relatable video assets that feel like genuine customer testimonials rather than ads. By combining my own live-action filming with AI-generated audio variations, we successfully optimized the campaign for engagement, finding the perfect balance between emotional resonance and algorithmic performance.

