{"id":37830,"date":"2026-01-16T14:29:53","date_gmt":"2026-01-16T13:29:53","guid":{"rendered":"https:\/\/hs-nordhausen.greydsuite.de\/?post_type=zusatzmaterial&p=37830"},"modified":"2026-01-19T12:59:14","modified_gmt":"2026-01-19T11:59:14","slug":"2-2-category-management-with-ki","status":"publish","type":"zusatzmaterial","link":"https:\/\/hs-nordhausen.greydsuite.de\/en\/zusatzmaterial\/2-2-category-management-mit-ki\/","title":{"rendered":"2-2: Category management with AI"},"content":{"rendered":"

Marketing textbook, Keywords<\/span><\/p>\n\n\n\n

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Business requirements for market-oriented action \u2192 Marketing organisation \u2192 Organisational structure (section 2.3.1)<\/p>\n<\/div>\n\n\n

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Category management will not be replaced by AI in the future, but this key technology of digitalisation opens up new possibilities: Automated processes will take over time-consuming tasks and free up time for strategic considerations. According to a study by Kantar, manufacturers and retailers are planning to invest more in AI over the next few years in order to better understand customer data, recognise trends at an early stage and plan and implement strategies more quickly. The study shows that AI delivers high added value, particularly in terms of demand planning, competitive analysis and pricing strategy. In addition, relevant market developments can be identified more reliably, product ranges and promotions can be planned better and the customer journey with its numerous touchpoints can be analysed more precisely.<\/p>\n\n\n\n

Data forms the necessary basis for every learning system. Based on a wide range of data, AI enables decision-makers to make better decisions and optimally utilise sales potential. In addition to data quantity, data quality also plays a decisive role: AI systems are based on pattern recognition and learning algorithms that are trained to recognise certain patterns in the available data and derive insights from them. If data is incomplete or incorrect, the AI works inaccurately or incorrectly.<\/p>\n\n\n\n

Specific examples of the use of AI in category management:<\/p>\n\n\n\n