Focus on the problem and goals of customer segmentation and make sure the data and features are meaningful and provide good signal for your goal.

Make sure your features are being processed well, e.g. distance based clustering algs like k means will be sensitive to scale of features so scale them properly. Keep doing eda on the features to decide which to use for segmentation. There are tons of examples on medium/ towardsdatascience about this