How blurred-machine/sales-and-marketing-analytics works
This repository is a collection of nine sales and marketing analytics notebooks, covering customer metrics and behavior, sales prediction, and marketing response and experimentation. An analyst selects and runs a notebook to explore its named topic. The README documents the capabilities, but no notebook source excerpts were available, so data inputs, implementation steps, and connections between notebooks are not inferred.
Main entry points: Revenue and User Retention Calculation.ipynb Metrics & Retention · Customer Segmentation.ipynb Customer Segmentation · customer_lifetime_value_prediction.ipynb Lifetime Value · churn_prediction.ipynb Churn Prediction
Components 10
Customer Analytics
- Metrics & Retention
1- Know Your Metrics/Revenue and User Retention Calculation.ipynb - Customer Segmentation
2- Customer Segmentation/Customer Segmentation.ipynb - Lifetime Value
3- Customer Lifetime Value Prediction/customer_lifetime_value_prediction.ipynb - Churn Prediction
4- Churn Prediction/churn_prediction.ipynb - Next Purchase Day
5- Predicting Next Purchase Day/Predicting Next Purchase Day.ipynb
Sales Forecasting
- Sales Prediction
6- Predicting Sales/Sales Prediction.ipynb
Marketing Analytics
- Market Response Models
7- Market Response Models/Market Response Models.ipynb - Uplift Modeling
8- Uplift Modeling/Uplift Modeling.ipynb - A/B Testing
9- AB Testing Design and Execution/AB Testing Design and Execution.ipynb
Other components
- Analyst
Connections 9
- Analyst → Metrics & Retention: runs
- Analyst → Customer Segmentation: runs
- Analyst → Lifetime Value: runs
- Analyst → Churn Prediction: runs
- Analyst → Next Purchase Day: runs
- Analyst → Sales Prediction: runs
- Analyst → Market Response Models: runs
- Analyst → Uplift Modeling: runs
- Analyst → A/B Testing: runs