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Although it is habitual to measure human perceptions with quite accurate instruments, perceptions are characterized by uncertainty and fuzziness. Furthermore, variations in individual perceptions and personality mean that the same words can indicate very different perceptions. In this context, the fuzzy linguistic approach seems to be an appropriate framework for modeling information. In this paper we explore the problem of integrating semantically heterogeneous data (natural language included) from various websites with opinions about e-financial services. We develop an extension of the fuzzy model based on semantic translation (FMST) under the perspective of the service quality (SERVQUAL) stream of research. The model permits us to obtain a more precise representation of the opinions using each type of customers. By integrating all customers into different subsets, a financial entity can easily analyze the …