Retail Segmentation Based Marketing Campaing In R And H2o

Abstract

1. Introduction

A retail chain "At the corner" sales different types of products. They would like to introduce a new product. They decided to go with an e-mail marketing campaign. To optimize campaign costs and customers' comfort they decided to carefully select customers that would be contacted in the campaign.

As an analytical driven company "At the corner" conducted a pilot campaign to gather data (stored in data/retail_train.csv file). The data was gathered for 10 000 customers with an information (column purchased) whether a customer opened an email and clicked in a promoting banner.

2. Objective

Showcase for using H2O and R for scoring for marketing campaign in retail

This project demonstrates how R, Machine Learning can be applied to a real-world Digital Marketing & SEO problem.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• See the project README for exact requirements
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/WLOGSolutions/retail-segmentation-based-marketing-campaing-in-r-and-h2o.git
cd retail-segmentation-based-marketing-campaing-in-r-and-h2o

1. Install dependencies for the project
2. Build custom package(s) segmentationmodels with internal functions implemented

rsuite proj depsinst

rsuite proj build

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Export reports to Google Sheets or PDF
• Schedule weekly automated reports
• Add competitor comparison

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. Which marketing or SEO problem does this tool solve?
2. Which data sources or APIs does it use (Search Console, Analytics, social platforms)?
3. Which metrics or KPIs does it report and how are they calculated?
4. How could the output help a business make decisions?
5. How would you schedule it to run automatically?

9. Source Code & License

This project is developed by WLOGSolutions and published on GitHub under the Apache License 2.0. Please follow the license terms and credit the original author when you use or modify this code.