I am running a logit model trying to predict purchases on a dataset including change variables, i.e. I have a dataset of this kind:
webvisits.month1 webvisits.month2 webvisits.month3 Purchase contract1 34 21 22 0 contract2 11 2 2 1 contract3 9 22 17 1 contractn 5 44 42 0
The model is not performing well at all, would it be a good idea to try and normalize my variables? Would that affect the outcome? If this is the case, should I normalize them by month (considering the values by variable webvisits.month1, webvisits.month2 and so on) or rather by contract (e.g. considering the distribution contract1 [34,21,22,0], contract2 [11,2,2,1] and so on? Thanks, hope this makes sense.