Competitive Analysis with Data Science for Marketing Strategists

Course overview

This training provides you with practical knowledge in the field of competitive analysis using Data Science. You will learn to categorize typical tasks confidently, apply suitable methods and tools, and present results in a comprehensible manner. The focus is on practical applications from the areas of Data Science, Strategic Marketing Management, and Online Marketing, which will support you in your role as a marketing strategist or in comparable professional tasks. Data Sources and Collection Methods in the Competitive Context Basics of web scraping to collect publicly available competitive data Use of SEO, Ads, and social media tools for market observation Structuring and storing competitive datasets Exploratory Analysis and Pattern Recognition Descriptive statistics to describe competitive structures Clustering approaches to identify market segments Visualization of competitive landscapes and positioning fields Price, Assortment, and Communication Analysis Systematic comparison of price levels and offer structures Analysis of competitors' advertising and content strategies Identification of market gaps and differentiation potentials Deriving Strategic Recommendations for Action Transforming analysis results into strategic options Presentation and communication of competitive insights Establishing a continuous competitive monitoring system This training helps you to handle typical tasks in the field of competitive analysis with Data Science more securely and efficiently. You will combine professional knowledge with practical methods and tools from the areas of Data Science, Strategic Marketing Management, and Online Marketing. This way, you strengthen your confidence in your role as a marketing strategist and can directly apply the content in your professional everyday life.

Upcoming dates

• 2026-09-13T22:00:00.000Z · 2027-01-03T23:00:00.000Z · Erfurt · Blended Learning
• 2026-09-13T22:00:00.000Z · 2027-01-03T23:00:00.000Z · Berlin · Blended Learning
• 2026-09-13T22:00:00.000Z · 2027-01-03T23:00:00.000Z · Freiburg im Breisgau · Blended Learning
• 2026-09-13T22:00:00.000Z · 2027-01-03T23:00:00.000Z · Ludwigsburg, Württemberg · Blended Learning
• 2026-09-13T22:00:00.000Z · 2027-01-03T23:00:00.000Z · Köln · Blended Learning