Get insights of Instacart Market Basket

January 22, 2018
By

(This article was first published on R – NYC Data Science Academy Blog, and kindly contributed to R-bloggers)

Introduction

Services that deliver the ingredients and recipes you need to make fresh, home-cooked meals, like Instacart have grown in popularity as people are turning away from low-cost, fast food in favor of healthier alternatives. However, those subscription services are still luxury for many so I decided to create a interactive dashboard to help the Instacart have some promotions with the consumers.

 

Research Question

What consumer behaviors can we find based on previous purchasing data?

What’s the best time to deliver effective promotions to targeted consumers?

 

Data

The data set is on kaggle’s competition and I used orders, order products, products to do the analysis.

 

Order Time

 

The first plot shows that there is a clear effect of day of the week. Most orders are on days 0 and 1. Unfortunately there is no info regarding which values represent which day, but one would assume that this is the weekend.The second plot shows most orders are between 8.00-18.00. The third plot shows that people seem to order more often after exactly 1 week.

We can prove previous plots by the heat map in bottom

In the heat map we can find that density over weekend is relatively high, from the previous graphs, we can come out with a promotion idea to increase customers loyalty. For example, we can send out coupons before weekend comes and to see if consumers to use coupon or not. If consumers use coupons, we can calculate the percentage of consumers who actually use coupon. This can tell us our promotion is effective or not.

 

Top Categories & Average Number of Items do People Buy

In this plot we can find that which products are sold most often (top10). It’s obviously that the winner is Bananas. I also find that more and more people prefer to buy organic food now.

Let’s have a look how many items are in the orders. We can see that people most often order 5 items online.

Right now, we can also make a promotion based on these insights. For example, if consumers buy five products at a time, we can add one free organic food or bananas to their order. By doing so, we can encourage consumers buying less than 5 items to add more items to their cart to get one free organic food. we can combine data analysis of consumer data with marketing to better deliver promotion to our target consumers.

 

Summary

Based on the word cloud we can find that popular products are organic products. People care about their health and it totally worth it with the higher price buying organic food. Instacart can put more efforts on organic products/food promotions to better meet consumers need.

If you have any question, please feel free to check my GitHub!

To leave a comment for the author, please follow the link and comment on their blog: R – NYC Data Science Academy Blog.

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