Social media resources currently contain vast amount of unstructured data, open for processing with marketing analytics tools. Due to existing cognitive systems, we can uncover and handle interdependencies within unstructured data, turning them in structured ones. Cognitive computer systems are rapidly evolving and have a big potential to change the way information is used in business applications. Evolution of the cognitive information systems is still ongoing, yet they are already used in business and marketing. The goal of our article is to define various ways to apply cognitive systems for unstructured data analysis and management for further use in marketing analytics. We will use IBM Analytics Tools for the example of cognitive computing. We apply these tools to analyse social media as one of the major sources of data on potential customers. Social media is among the fastest growing communication platforms. At the same time, it is the venue for most swift and immediate reactions by customers to various marketing activities. Analysis of such type of data therefore provides interesting and important information on how people perceive different commercial products. Via IBM Watson we were able to analyse unstructured data found on social media. The advantage of using cognitive system is that system itself collects the relevant data, which we wanted to analyse, based on preset criteria. Analysis of data from the set of social media provided us with information on frequency of references to and individual perceptions of certain brands. Furthermore, from social media we also learned about demographic and geographical spread of awareness about brands and products. For research we analysed the perception of price of a new Samsung product (Samsung Galaxy S7) among students (age group 18-25) during two months from its launch (from 03.01.2016 to 04.30.2016).

Although higher education institutions (HEIs) are expected to be the leaders in knowledge generation and dissemination, it is often not clear whether they are knowledge-aware, that is, have a knowledge focus. In this article, the communication with stakeholders through HEI websites is examined to determine to what extent these institutions communicate about their knowledge initiatives and projects. This is done through an investigative study involving all HEIs and their faculties in Slovakia. Using content analysis, the study examines whether the publicly available resources on HEIs’ websites contain knowledge-related keywords, indicating the existence of a knowledge-focus. The results reveal that the websites of some HEIs contain hundreds of these resources, whereas others have none. Statistical evidence confirms that the intensity of communication about knowledge terms increases with the age and size of the HEI and is also dependent on the type of HEI (public, private state, foreign). Other dependencies between the examined factors have also been revealed, for example, HEIs that rank higher in Webometrics indicators are more intensive in their knowledge communications.