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Telemarketing Sales Prediction

Home Page: https://vaima75.github.io/Oasis/

License: GNU Lesser General Public License v3.0

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oasis's Introduction

Tele-Marketing Sales Prediction: Classification Problem

This case-study was given by Desicison Point

Case-Study : Oasis Problem Statement

Company X relies upon telemarketing to sell products.

Your project lead wants to utilize the opportunity and prepare a business development case for predictive modeling assignment. The lead has asked you to explore different available techniques and prepare a few slides on the technique which can be implemented on the business. The lead has also requested you to prepare the objective of the model, list additional data requirement and briefly describe the model- include steps and possible impact on the business.

The column headers are self-explanatory, with the 'Sale' column indicating whether a sale was made or not when Agent X called the customer.

Data Description

Sno Variables Description
1 Call_ID Customer Call ID
2 Sale Did Sale Happend?
3 Agent_ID ID of Agent
4 Age Age of Customer
5 Product_ID ID of Product
6 Timezone Timezone where call was made
7 Phone_code Customer's Phone Code
8 First_Name Customer's First Name
9 Last_Name Customer's First Name
10 Area_Code Location Code of Customer
11 Gender Customer's Gender
12 Call_Count Calls made to customer by Agent X

Methodology

  • Data - Preprocessing

    • Feature Creation and Preparation
    • Outlier Treatment
    • Imputation Method
  • Model Preparation and Algorithms

    • Sampling Techniques
      • Over sampling
      • SMOTE
      • SMOTE Tomek
    • Modelling Algorithms
      • Random Forest
      • XGBOOST

Results

Mno Model Sampling Method Accuracy F1 Score Recall ROC-AUC PR-AUC
1 RF Upsample 0.892 0.105 0.071 0.522 0.180
2 RF SMOTE 0.901 0.071 0.040 0.514 0.175
3 RF SMOTE Tomek 0.901 0.069 0.041 0.513 0.174
4 XGBOOST Upsample 0.618 0.189 0.495 0.562 0.328
5 XGBOOST SMOTE 0.909 0.030 0.016 0.506 0.213
6 XGBOOST SMOTE Tomek 0.909 0.030 0.016 0.506 0.213

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