Cross-Sell Up-Sell Recommender System

A recommender system that enables cross-sell and upsell of products (either new products or already bought products) that will enable higher revenue generation. The data captures material that is sent to the wholesalers over a span of time.

Link for the presentation - https://drive.google.com/file/d/1o8j2kPF_6vMz_LpxZn8uiZ_DAk83tkgU/view?usp=sharing

Here is a video of the working of the platform. Click on it to get directed to the Google Drive link:

Objectives

• Finding how similar other wholesalers are to W1.
• Finding wholesalers who buy similar products.
• Finding wholesalers who buy similar products.
• Application of a feedback mechanism so that sales team can easily implement their knowledge of incompatible products/customer.
• To find which products are popular.
• To recommend the product which will enable higher revenue generation.

The dataset

The dataset has been provided by AB InBev as a part of their hackathon Maverick 2.0: Hack-a-thon where the participants in the Cross-Sell Up-Sell track were to build a Recommender System based on the data given Consumers/Wholesalers and their history of purchase.

Installation and setup

• Before starting the installation process, please ensure that you have conda/virtualenv installed.

1. Open terminal and clone the reposotory:

  git clone https://github.com/milonimittal/Cross_Sell-Up_Sell.git

2. Change into project directory:

  cd Cross_Sell-Up_Sell

3. Create python environment:

  conda create --name recsys python=3.8.5

4. Activate environment:

   conda activate recsys

5. Install dependencies:

   pip install -r requirements.txt

6. Running the code:

   python main_flask.py

Contributing

Feel free to contribute features / point out errors. Fork this repository and make a pull request.