This project is about exploring shopper behavior and build a shopping cart recommender using Instacart data.
In this project, I want to explore customer shopping behavior by analyzing their pervious purchases and build a shopping cart recommender that could give them a tailored shopping experience to drive engagement.
I want to perform a Shopper Behavior Analysis by analyzing shoppers purchase history and see if I could find patterns such as what kind of items customers like to purchase in different time of day/week, how often do people reorder the same product they purchased before and etc. And build a recommender system using customer's reordered purchases and cosine similarity.
For complete write-up of this project, please go to my post on medium.
- Perform Data Cleaning, merging different tables together and do Exploratory Data Analysis (EDA).
- Analyze customer behavior, generate insights and build data visualizations for storytelling.
- Define a metric for model evaluation.
- Lastly, create a shopping cart recommender system to recommend items to customers based on their purchase history.
notebooks- My code for exploratory data analysis, data visualizations, recommender system and metirc calucation are in this folder.presentation- This is the deck that I used to present in Metis. For references, please refer to the reference page in my deck.