The Situation
FALKE only had classic product images for individual items: models on a white background—functional, but not suitable for social media. They lacked the dynamism, storytelling, and scalable creatives needed for paid social.
Without existing campaign material, the traditional route would have required an expensive, time-consuming shoot. At the same time, the demand for creative output and speed is constantly rising.
This created a clear conflict of goals: achieving high, campaign-level visual quality while maintaining maximum production efficiency. This is exactly where the strategy came in.
Implementation
Instead of a traditional production, an AI-first approach was chosen. The existing product image was reinterpreted using generative AI—reconstructing the model, expanding the setting, and turning a static asset into a campaign motif.
Building on this, video assets were created directly from the generated visuals. These achieved campaign-level quality and were virtually indistinguishable from non-AI content.
The assets were finalized in post-production and optimized for social media. This created a scalable system: from a static image to high-performing video content without a traditional shoot.
The key was not just the use of AI, but the clear process logic: from an existing asset to AI transformation, resulting in high-performance video content.
Outcomes
The impact was immediately measurable. 25% of revenue in Q1 2026 was generated via AI-created assets. At the same time, creative diversity was significantly increased, as new assets were no longer restricted by production limits.
Combining AI content, UGC, and classic assets created a much more robust creative setup. Content could be tested, iterated, and scaled faster than ever before.
The biggest lever, however, was efficiency: traditional shoots costing around €30,000 were replaced by a flexible, significantly faster AI process. For the first time, "baseline content" became truly scalable—without any loss in quality.
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