There is a growing literature on the design and use of stated choice experiments. Analysts have developed sophisticated ways of analysing such data, using a form of discrete choice model to identify the marginal (dis)utility associated with observed attributes linked to an alternative, as well as accounting for preference and scale heterogeneity. There is also a growing literature studying the attribute processing rules that respondents use as a way of simplifying the task of choosing. Using the latent class framework, we define classes based on rules that recognise the non-attendance to one or more attributes. These processing rules are postulated to be used in real markets as a form of cognitive rationalisation. The empirical study involves a choice amongst rural environmental landscape improvements in the Republic of Ireland. We estimate models and calculate a marginal willingness to pay (WTP) for four landscape improvements, and contrast it with the results from a model specification in which all attributes are assumed to be attended to with parameter preservation. We find that the marginal WTP is, on average, significantly higher when full attribute preservation specification is adopted, raising questions about the appropriateness of current practice that assume a fully compensatory attribute choice rule.