AI Copilots for Data-Driven Brand Management

Brands are key success factors for companies. However, their analysis and evaluation are often carried out manually and rely on subjective opinions or intuition. This introduces bias and increases risk, as these evaluations are critical for guiding substantial brand investments.

We introduce The Regular Brand (TRB), an AI-powered data platform co-developed by KMS TEAM and bakdata. TRB enables objective analysis and evaluation of even complex brand systems in real-time. TRB automatically integrates and analyses large-scale, heterogeneous data from various online sources. With AI technologies such as embedding and large language models, we generate actionable insights from both text and visual content. Our AI architecture features optimized model selection and configuration, enabling high-performance analytics on large data sets while keeping operational costs low.

With the ZEISS brand as a case study, we demonstrate TRB’s capabilities and discuss opportunities and challenges of data-driven brand management:

Our analyses reveal competitive advantages and insights for brand positioning across industries. By analysing brand concepts such as archetypal frameworks (e.g., Hero, Explorer, Sage) and continuously monitoring trends and benchmarks, we contribute to informed actions in brand management.

Opportunities include a structured, data-driven approach to analyzing complex brand systems - adaptable across industries, providing a reliable foundation for strategic investments and precise brand management.

Key challenges include ensuring high-quality, up-to-date data, defining the right data scope, and weighting sources. Is website content enough or should we also consider social media, online shops, and other channels? We also address AI explainability, the limits of automation, and how large organizations can adopt and govern data and AI tools successfully.