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The main aim of this project is to built a predictive model using G Store data to predict the TOTAL REVENUE per customer that helps in better use of marketing budget.

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RajK01/Google-Customer-Revenue-Prediction

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✨ Google Analytics Customer Revenue Prediction ✨

📍 Business problem -

In every business it was proven about 80–20 rule, this rule tells us 80% of our revenue will be generated by only 20% of our potential customers. So our goal is to predict the revenue that is going to be generated by those potential customers in the near feature. So that marketing teams will invest appropriate money on promotional strategies to attract potential customers.

📍 About Data -

We are given with the users past data and transactions (when they logged into G-store), so by using this data I predicted the future revenue will be created by those customers. (Data is availavle in kaggle)

📍 Aim -

Aim is to build a predictive model using G-store data to predict the total revenue per customer that helps in better use of marketing budget.

📍 About features/columns/independent variables -

  • fullVisitorId, TransectionRevenue.

📍 Performance metric for the problem -

RMSE is defined as:

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