User experience (UX) analysis is essential for designers and companies when optimizing products or services as it can help designers to uncover valuable information, such as the hedonic and pragmatic qualities of a UX. While previous research has described the conventional methods of UX analysis, such as surveys or subjective determination, this paper proposes a data-driven methodology to automatically integrate hedonic and pragmatic qualities for UX from online customer reviews. The proposed methodology comprises the following steps. First, we combined a corpus-based approach, a dictionary-based approach and word embedding to generate a lexicon of hedonic and pragmatic qualities. Second, we filtered out the sentences that contained no hedonic or pragmatic information and classified the remaining review sentences. Third, we extracted and clustered the UX elements (such as product feature, context information and context clustering). Finally, we scored each UX element based on hedonic or pragmatic qualities and compared it against previous UX modeling. This study integrates hedonic and pragmatic qualities to enrich UX modeling in the field of UX. For a product designer, the UX analysis results may highlight a requirement to optimize product design. It may also represent a potential market opportunity in a UX state where most of the current products are perceived UX results by customers. This research also examines the invaluable relationship between UX and online customer reviews to support the prospective planning of customer strategy and design activities.