Integração do Google Analytics com heurísticas de usabilidade para avaliação da usabilidade de sites de ecommerce

Abstract

This project explores the integration of Google Analytics (GA) with usability heuristics for evaluating the usability of e-commerce websites. The research addresses the limitation of quantitative data obtained solely through Web Analytics, highlighting the need for a mixed methodology that combines quantitative data extraction with qualitative data from heuristic evaluations to infer usability and accessibility problems. The methodology employed involved building an e-commerce prototype, collecting quantitative user behavior data using Google Analytics 4 (GA4), and identifying pages with potential usability problems. Subsequently, heuristic evaluations were conducted on these specific pages, utilizing the ECUXH (E-Commerce User eXperience Heuristics) set, which is designed for the e-commerce domain and considered more effective than generic heuristics. The results show that GA4 can quickly indicate general problematic areas, such as the purchase process and internal search. In contrast, heuristic evaluations complement this analysis by providing specific and in-depth details about the nature and exact causes of the identified problems. The advantages of this combined approach include rapid identification of problematic areas, continuous monitoring, data accuracy from page tagging, and financial insights not offered by heuristic evaluations. However, there are also disadvantages, such as time-consuming analysis and interpretation of web metrics, GA’s lack of specific detail on its own, and the dependence on comprehensive GA4 event configuration for complete data collection. It is concluded that GA is an effective and economical first step for identifying usability problems, but complementary techniques like heuristic evaluation are indispensable for a complete and detailed understanding, allowing for faster and more economical problem identification.