Conjoint is a compensatory multiattribute model - it assumes that weakness on one attribute can be compensated for by strength in another. It assumes that the utility or value for a product can be expressed as a sum of utilities for its features or attributes.

Next, we can ask customer to rank or rate, the profiles. The table below present rankings for a hypothetical customer, the profiles are coded as dummy variables

data choc;
input Chocolate $ Center $ Nuts $& Rating;
datalines;
Dark Chewy Nuts    7
Dark Chewy No Nuts 6
Dark Soft Nuts     6
Dark Soft No Nuts  4
Milk Chewy Nuts    9
Milk Chewy No Nuts 8
Milk Soft Nuts     9
Milk Soft No Nuts  7

PROC TRANSREG is used to perform a metric conjoint analysis.
ods exclude notes mvanova anova;
proc transreg utilities separators=", " short;
title2 "Metric Conjoint Analysis";
model identity(rating) = class(chocolate center nuts / zero=sum);
run;

The specification class(chocolate center nuts / zero=sum)
designates the attributes as class variables with the restriction
that the part-worth utilities sum tozero within each attribute.