10. A method for computationally performing an online choice model, the method comprising: receiving a plurality of attributes from a user wherein each attribute has an associated plurality of attribute levels; generating a survey experimental design and an associated set of treatments, comprising the steps of: determining the signature of the attribute space from the received plurality of attributes and associated attribute levels; selecting one or more experimental designs from a library of experimental designs; for each selected experimental design; performing one or more transformations until the signature of the transformed experimental design matches the signature of the attribute space to obtain one or more matching transformed experimental designs; wherein each transformation preserves the information properties of the untransformed experimental design; selecting a survey experimental design from the one or more matching transformed experimental designs; obtaining a set of treatments from the selected survey experimental design; assembling an online survey, comprising the steps of: creating a plurality of survey templates pages; creating a plurality of treatment representations based on the set of treatments associated with the survey experimental design; assembling the plurality of survey templates pages and plurality of treatment representations to form an online survey; conducting an online survey, the online survey comprising allocating each treatment to one or more respondents; providing a plurality of combinations of treatments to the one or more respondents; receiving the responses of the one or more respondents; generating a model based upon the received responses to obtain a plurality of model parameter estimates and errors from which a utility estimate can be obtained for each attribute level; and providing a model explorer user interface for allowing the user to enter one or more attribute levels and obtain a model prediction of the expected utility; wherein the one or more transformations comprise one or more of the following group of transformations: factorial splitting of a factor F into two sub factors A, B where A×B=F and A or B match at least one unmatched factor in the signature; factorial expansion of a factor F into a new factor A×F where A×F matches at least one unmatched factor in the signature; factor truncation of a factor F into a new factor F−A where F−A matches at least one unmatched factor in the signature; full factorization by generation of a new factor F where F matches at least one unmatched factor in the signature; and deleting a factor F when all the other factors in the signature are matched.
10. A method for computationally performing an online choice model, the method comprising: receiving a plurality of attributes from a user wherein each attribute has an associated plurality of attribute levels; generating a survey experimental design and an associated set of treatments, comprising the steps of: determining the signature of the attribute space from the received plurality of attributes and associated attribute levels; selecting one or more experimental designs from a library of experimental designs; for each selected experimental design; performing one or more transformations until the signature of the transformed experimental design matches the signature of the attribute space to obtain one or more matching transformed experimental designs; wherein each transformation preserves the information properties of the untransformed experimental design; selecting a survey experimental design from the one or more matching transformed experimental designs; obtaining a set of treatments from the selected survey experimental design; assembling an online survey, comprising the steps of: creating a plurality of survey templates pages; creating a plurality of treatment representations based on the set of treatments associated with the survey experimental design; assembling the plurality of survey templates pages and plurality of treatment representations to form an online survey; conducting an online survey, the online survey comprising allocating each treatment to one or more respondents; providing a plurality of combinations of treatments to the one or more respondents; receiving the responses of the one or more respondents; generating a model based upon the received responses to obtain a plurality of model parameter estimates and errors from which a utility estimate can be obtained for each attribute level; and providing a model explorer user interface for allowing the user to enter one or more attribute levels and obtain a model prediction of the expected utility; wherein the one or more transformations comprise one or more of the following group of transformations: factorial splitting of a factor F into two sub factors A, B where A×B=F and A or B match at least one unmatched factor in the signature; factorial expansion of a factor F into a new factor A×F where A×F matches at least one unmatched factor in the signature; factor truncation of a factor F into a new factor F−A where F−A matches at least one unmatched factor in the signature; full factorization by generation of a new factor F where F matches at least one unmatched factor in the signature; and deleting a factor F when all the other factors in the signature are matched. 18. The method as claimed in claim 10 , wherein the step of receiving a plurality of attributes from a user further comprises: providing a user interface for receiving content and layout parameters relating to the online choice model survey from a user; generating a plurality of survey template pages based on the content and layout parameters received from the user; wherein at least one of the plurality of survey template pages comprises at least one treatment display zone, each treatment display zone comprising one or more associated layout parameters; sending the set of treatments and the one or more layout parameters associated with each treatment zone to a content generator for generating a visual representation of a treatment; and receiving a plurality of treatment representations from the content generator; wherein in use, an online choice model survey is provided to a survey respondent comprising one or more web pages based upon the one or more survey template pages in which each of the treatment display zones displays one of the received visual representations of a treatment.