Ehandelsanalyse

Ehandelsanalyse, or e-commerce analysis, is the systematic process of collecting, processing, and interpreting data from online retail channels to understand customer behavior, assess performance, and support decision making across marketing, product, and operations. The aim is to improve user experience, increase conversions, and optimize profitability.

Core metrics include traffic, conversion rate, average order value, revenue, gross merchandise value (GMV), cart abandonment rate, customer acquisition cost, and customer lifetime value. Analytical methods cover funnel analysis, cohort analysis, attribution modelling, segmentation, and experimentation through A/B tests.

Data sources span website and app analytics, payment and order data, customer relationship management, email and advertising platforms, product and inventory systems, and marketplace data. Analysts often combine structured data with session and clickstream data, then apply statistical or machine learning models to forecast demand or optimize offers.

Applications include optimizing site design and checkout flow, pricing and promotions, merchandising, cross-sell and up-sell strategies, personalised recommendations, and inventory planning. Ehandelsanalyse supports budgeting, channel planning, and performance benchmarking against competitors or market trends.

Challenges include data quality and integration, privacy and compliance (notably GDPR), data fragmentation across channels, and attribution complexity. Ethical considerations and transparency in reporting are important. The field relies on cross-functional collaboration among marketing, product, IT, and logistics teams.