X
Sign Up for Updates
Sign up for our mailing list to keep up with what we're up to and be the first to know about new Marketing X AI events.
Sign up for our mailing list to keep up with what we're up to and be the first to know about new Marketing X AI events.
A breakthrough AI-powered tool, CollXbs, has transformed the way marketers approach brand collaborations. By generating visually compelling and conceptually intriguing brand collaborations, the tool not only showcases AI's creative potential but also offers unique insights into brand strength and identity. The innovation has sparked a conversation in the industry, paving the way for a future where AI plays an even more integral role in marketing.
CollXbs, launched in 2022, is a groundbreaking tool leveraging AI to generate unique brand collaborations. By taking input from marketers about desired brands and items, it provides a new perspective on brand interaction and image generation. The tool is open for all, fostering a new level of creativity and understanding of AI within the marketing and creative community.
In today's dynamic era of branding, the interplay between creativity and technology opens the door to unexplored avenues. Leading the way is Noah Brier with BrXnd—an organization committed to driving marketing innovation through AI. His first offering is a unique AI-powered brand collaboration tool named CollXbs.
Rob Walker wrote in Fast Company, "Anyone can now use the collab-engine to generate a dizzying array of hypothetical dual-branded items." But CollXbs is more than a tool that generates marketing copy and imagery—it provides profound insights into brands' strengths and weaknesses, all learned by AI.
The intuitive design of CollXbs is such that users input two brands and choose a product. The result is an AI-generated brand collaboration. The process relies on several models fine-tuned by Brier. It starts with feeding the brands and the item to a model trained on hundreds of actual collab announcements, generating realistic-sounding marketing text. This text then informs an aesthetic description for the item through another fine-tuned model. This description is converted into an image prompt, which is finally fed to Dall-E, a model capable of creating unique images from text descriptions. Brier adds specific directions for better results, like "8k. ultra realistic. commercial photoshoot" for sneaker prompts.
Through the analysis of thousands of AI-generated collabs, Brier discovered critical insights. First and foremost, good brands make better images. He posits that practices making brands great, like consistency and distinctiveness, align well with the way machine learning models pick up on patterns. Small but powerful brands, such as Aimé Leon Dore and Ghostly, also have a great appearance. This proves that the strength of a brand is not only based on its size.
Brier further notes that the tool serves as a measure of relative brand strength. For example, in a Hermès collaboration, the iconic brand often overpowers the other, unless the collaborator possesses a strong aesthetic. This demonstrates the model's ability to discern strong brand identities. He even noticed that the model recognizes the distinct art direction aesthetic of brands like Supreme.
Interestingly, the model also reflects common brand perceptions. When users request a sneaker, it often places a Nike swoosh on it, regardless of the brands chosen, symbolizing Nike's ubiquitous presence in the sneaker market. While at first, this seems like a mistake—a “hallucination” in AI terms—it’s actually an accurate representation of market perception, which associates Nike with sneakers.
Through tools like CollXbs, BrXnd fosters a dialogue between brands and AI, pushing both industries forward, and proving that AI can play a significant role in understanding and representing brands. His ongoing commitment to exploring the potential of AI in marketing sets the stage for future innovations, positioning BrXnd at the forefront of this convergence.
