DoorDash Analytics

This article is for educational purposes only. The dataset has been modified for this purpose.

The other day I was without a car at my new apartment. Haven't been grocery shopping yet so no food in the fridge or cupboards. I was starving from moving and exhausted. DoorDash delivery to the rescue. Bring on the yummy Raising Cane's chicken fingers. It got me wondering how many people are using DoorDash. I wondered about their ages, income and what months are people ordering from DoorDash the most.

With the help of a dataset I found online, I was able to learn more about sales and demographics of iFood a company which has the same business model as DoorDash.

So with the help of Excel I imported the 2,000 row data set and learned

• $1.1 Million was spent on DoorDash in 2016

• 67% of the difference in spending is due to income levels

• Growth throughout the year was mostly constant at 183 new customers with November and December being the low & January and March being the high

• From the dataset for 2014-2016

  • Number of customers: 2021

  • Oldest customer: 80 years old

  • Average spent: $563.79

  • Total spent: $1,139,418

  
  

Let's Start with the Data

This dataset was given as a data analyst use case for an interview.

Here is the link to find it: Marketing Analytics (kaggle.com). The dataset is actually from iFood but very similar company to DoorDash. Below a copy of the excel file where I did my analysis can be found.

DoorDash_Case_Study.xlsx

Download XLSX • 828KB

Here are the important columns:

• Income, MntTotal (Amount Spent), Age (Age of Customer), Customer_Days (#Days of being a customer)

Here is what a row represents: Metadata about a customer

When the data occured: 2014-2016

Why do some people spend more?

The visual below shows that in general the greater the income the more money spent. It seems to be a close to linear relationship. I was able to plot a line that shows an R(squared) value of 0.67. Meaning, the scatterplot shows approximately 67% of the variance of total spent can be explained by income. Which means that with almost 67% accuracy I can predict how much will be spent on delivery based on income.

To recap, I learned that people love DoorDash and companies similar to it. They love it so much that $1.1 Million was spent in 2016.

Thanks for reading this. If you have questions feel free to leave a comment below, reach out to me at pcrosswait@patticrosswait.com or connect with me on LinkedIn Patti Crosswait.