How to increase the weight when it comes to outlier detection
Please look at my answer at Identfying spikes in data
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A general method could be to calculate a (moving) average and standard deviation.
Outliers are points that differ more than 3 times the standard deviation.

In your case, B will probably have a standard deviation of 3%, because 10% is considered an outlier. For A, C, D, E, the standard deviation may be 7%, because 20% is not considered an outlier.

Relative importance does not make something an outlier. A large deviation does.