When we began, All For Mimi had major visibility gaps across AI and search ecosystems. Despite millions of social impressions, the brand’s digital footprint was fragmented: product pages weren’t indexed properly, metadata was inconsistent, and generative engines (like ChatGPT and Gemini) either ignored or misidentified the brand entirely.
Our task was to connect the dots—aligning All For Mimi’s creative storytelling with the technical precision needed to make it discoverable by both people and machines. We built a structured entity system using Schema.org, optimised content for generative queries, and launched a targeted PR and backlink campaign to anchor the brand’s authority within fashion and culture. The result was a system that didn’t just boost visibility, but redefined how the brand is interpreted by intelligent engines and audiences alike.Development was centered around speed and scalability. We built the website using Next.js, ensuring it was lightweight and highly optimized.
For Berland, this project marked a defining example of the new era of digital communications—where cultural relevance and algorithmic precision coexist.
All For Mimi went from viral momentum to verified credibility, setting a benchmark for how next-generation brands can future-proof their presence across both AI and human ecosystems. The project demonstrated what happens when storytelling meets structured data: discovery becomes inevitable.