Analyse customer segmentation, sentiment on product review, and built a product recommender system

Given 5 dataset: geolocation, products, product name translations, customers, general. I explored these dataset and perform some analysis:

1. Location Heatmap: To determined which location has the highest transaction, most store, and most customer.
2. Delivery Estimation: To determined whether the estimation is early, late, or precise.
3. Promotion Timing: To determined the best time to promote products.
4. Customer Behaviour: To classify each customer to specific segment to treat customer differently based on their segmentation.
5. Popular Product: To determined which product have already popular so the company do not need to promote them anymore but to promote other unpopular product.
6. Sentiment Analysis: To determined whether the product reviews show bad or good compliment.

After several analysis, I created a product recommender system to give recommendation to customer after they purchased a product. This recommendation product will have high similarity with the previous purchased product.