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The methodologies used to measure key performance indicators are in a constant questioning, also quantitative data has using priority. Therefore, this research aims to generate fuzzy key performance to manage interactive customer experience. Whereas include companies measure their performance with fuzzy information, and improve the delivery information for making business decisions. First a model is proposed to manage customer interactive experience, based on the proposal of Schmitt (2003), measured with conventional indicators, using to a structural equation model analysis. Subsequently, to propose fuzzy key performance indicators, based on fuzzy subsets, model of Mamdani inference methodologies. The empirical study is applied to 960 customers of a low cost airline company in the Spanish air industry. The software used were AMOS, Matlab and KNIME. The approach proposed in this study can be a reference to linguistic analyzes based on information posted on any social media, either, Twitter, Facebook, blog, among others.   It is the first time empirically studied fuzzy indicators to manage interactive customer experience, marketing area. Whereas the data analyzed are based on the information delivered to a customer company in their natural language.

Fuzzy Key Performance Indicator, Customer Experience, Text Mining, Fuzzy Set, Mamdani model.