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It’s always cheaper to market to an existing customer than to new customers, and it’s easiest of all to market to a happy customer.

Why is customer loyalty so important? Well, first of all, there’s the economic incentive. That is to say, offering a little ‘thank you for your purchase’ as a follow-up to every order. In all the excitement, though, is anyone thinking seriously about customer retention?Įpic customer service only really gets into gear after a purchase has been made, and one of the easiest ways to keep folks coming back is by showing a little customer appreciation. Your warehouse is busy putting together orders, and your finance team has a smile from ear to ear. In this case we would like to measure the relationshipīetween the minutes a customer stays in the shop and how much money they spend.Good news! Your marketing team has had an amazing quarter, and orders have come flooding into your online store. That will help us find this relationship. The sklearn module has a method called r2_score() It measures the relationship between the x axis and the yĪxis, and the value ranges from 0 to 1, where 0 means no relationship, and 1

Of how well my data set is fitting the model. That is probablyīut what about the R-squared score? The R-squared score is a good indicator Spending 6 minutes in the shop would make a purchase worth 200. Example: the line indicates that a customer Regression, even though it would give us some weird results if we try to predict The result can back my suggestion of the data set fitting a polynomial Mymodel = numpy.poly1d(numpy.polyfit(train_x, train_y, 4)) Python Examples Python Examples Python Compiler Python Exercises Python Quiz Python Bootcamp Python Certificate
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