Využití procesů Competitive Intelligence ve startupu zaměřeném na digitální marketing

This thesis addresses the design and validation of a model Competitive Intelligence (CI) process in a startup environment, with a focus on digital marketing. The main objective was to create a practically applicable framework that would enable startups to make strategic decisions based on valid data obtained primarily from publicly available sources (OSINT), while respecting their financial constraints. The design process was based on the intelligence cycle methodology, which enabled a structured approach ranging from the definition of key intelligence topics and questions to the collection, analysis, and interpretation of data. Based on a review of professional literature and the identification of Key Intelligence Topics (KITs) and Key Intelligence Questions (KIQs), the main requirements for the process of collecting and evaluating information about the competitive environment were defined. Based on these, a case study was developed in which the proposed techniques were practically tested in a real-world context. A significant part of the work also involved assessing the ethical and legal limits of data collection; through structured interviews with legal experts, the boundaries between legitimate competitor monitoring and potential violations of copyright or the GDPR were defined. After conducting the analyses and incorporating the findings, the results showed that the proposed process meets the needs of startups and has the potential to contribute to improving the quality of management’s strategic decision-making. The output of the thesis is a comprehensive manual and a set of recommendations for the effective and legal implementation of CI processes.