METHODOLOGY FOR MULTI-CRITERIA EVALUATION OF DIGITAL RETAIL PLATFORMS: INTEGRATION OF MCDA, WEB ANALYTICS, AND UX DATA

The article presents a methodology for multi-criteria evaluation of digital retail platforms based on the integration of Multi-Criteria Decision Analysis (MCDA), web analytics, and UX data. The proposed hybrid model combines AHP and TOPSIS methods, enabling the formalization of expert preferences and the construction of an integral ranking of alternatives. The methodology incorporates heterogeneous data sources, including quantitative web metrics, qualitative UX assessments, and mystery shopping results. Principles of data normalization, criteria weighting, and the algorithm for calculating the integral score are described. The methodology was tested on datasets from online stores and offline retailers, confirming its stability, interpretability, and applicability for assessing digital maturity and user experience quality. The results can be used for UX auditing, interface evaluation, digital product management, and strategic e-commerce analysis.

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