DoorDash Sales Analysis Using Excel

Published By: Madeeha Umar

In this fast moving world, everyone has a lot to do but always have shortage of time. The other day while we were busy in moving to a new house we forgot that our groceries are finished. It's lunch time, we are hungry but has no time to prepare... ??Hey let's order it online!! Is there any better idea other than this!!!

I realized that day how strong is the impact of technology we have in our lives and it has made it so easy. I know it's a bit more expensive with the added delivery charges but it's convenient for many reasons.

I see my friends always ordering online on different food delivery apps like DoorDash. It just made me curious to dive deep into analysis of the company. I analyzed that how many people are ordering from DoorDash and what are they ordering? How old they are and how much is their income? Does it have a correlation?? Does size of family and number of kids has any impact on their spending behaviour??

We all love food and always craving for our favorite food throughout the day. It makes DoorDash the biggest food delivery company in USA. Meanwhile during a recent research with a market share of 65 percent, DoorDash dominated the food delivery service companies.

Looking at transaction data through March 2023, Bloomberg Second Measure finds that DoorDash earned 65 percent of U.S. meal delivery sales. Between its debut through March 2023, the delivery company’s market share roughly doubled.

Here is the link to this research.

Let's start with the data:

Recently I got a data set from Kaggle. You can find it here. This dataset used for Excel project is using a slightly modified data set taken from a Brazilian version of DoorDash? a food company called iFood? for marketing analysis and it is slightly modified for educational purposes.

The data set?consists of 2206 customers of DoorDash company with data on:

• Customer profiles
• Product preferences
• Campaign successes/failures
• Channel performance
• Size of family

Key Findings:

With the help of this dataset imported to Excel for analysis I found out:

1. $1.24 Million were spent on DoorDash food delivery company in the year of 2018.
2. 67% of the spend variance can be explained by income levels.
3. Their growth remained pretty constant throughout the year at 183.75% new customers per month with November and December being the lowest and January being the highest.

Business Questions

To better assess the growth of DoorDash company and to find patterns of customers behaviors, I wanted to focus on getting answers of these business questions:

• What is the average amount of money spent by each customer?
• What is the total amount spent by customers?
• Does the age of customer affect the money spent?
• How is the oldest customer and age range of customers using DoorDash?
• Who is the most recently acquired customer?

Analysis

• First using Excel, I inserted a new column name "Customer ID". I sorted and filtered data to see the details of Campaign 6.
• Processing through Data Aggregation I used these functions SUM, MIN, MAX and AVERAGE. I was able to find information about these business questions like number of total customers, total spent and age of oldest customers with some other information.

• Then I used different formulas like IF, SUMIF and COUNTIF in order to find out the percentage of customer's total income vs what they spent on DoorDash.
• In order to know that if there is any specific age group that spend more on ordering food, I inserted a new column name "Age Group" and it differentiates customers in 4 age groups ranging from 24-35, 36-50, 51-65, and 66+.
• After analyzing the data I was able to create a scatter plot that describes a person's income that how they spent on DoorDash. In this scatter plot we can see as the income increases so as the total spent increases. I included the R-squared value in this relationship. This value is 0.6774 that represents and almost 70% of variance of total spent can be explained by their income. Even we can find few outliers in this scatter plot like we can see that 1 person is spending a lot more money on food delivery as compared to his income. May be this information in this dataset is wrongly collected or may be he is a student and he is spending more as still not making money yet. The other outlier we can see that one person is spending way less than what his income is. May be it's because of their food preference or they're more health conscious and emphasize more on home-cooked meals. There could be enough reasons to avoid food deliveries.

• Next I added a Histogram of the Amount total spent by customers.

• In aggregating the data deeper in Excel, I created a Pivot Table that broke down the customers by age and family size. It showed the patterns between their spending amount, their age and if they have kids or not. We can see that customers with same age groups without children spent lot more money on food deliveries as compared to those who have kids as parenting is not always easy. We could possibly see that people with 2 kids tend to spend less money on food deliveries and opted for home cooked food.

• After getting the data needed. I created a tool using?VLOOKUP. The tool would enable users to type any Customer ID and it returns the amount that customer spent.

• The final Bar graph completely shows the number of new customers that were obtained throughout the year. It shows that January was the month with highest number of new customers acquired. In months of November and December number of customers are decreased to the lowest. Overall average of 183.75% new customers acquired per month in a year that is great and consistent.

Insights & Recommendations:

To recap that what we've analyzed and learned through this dataset that people love to order food online from the comfort of their homes, offices and hotels. In 2018 there were total of $1.24 Million spent on food deliver company DoorDash. To summarize we can see that 67% of spent variance can be explained by income level. The more is the earning, the more is the spending on food delivery. We saw DoorDash has a constant number of new customers throughout the year, it was less in months of November and December but it was higher in the month of January.

We analyzed that overall the age group of 51-65 had spent more money. This leads me to realize that while DoorDash may be more popular within the age group of 36-50, the older group (51-65) has more higher income ranges and resources to use on food delivery services. DoorDash can introduce some special offers or packages for seniors that will eventually bring more benefits for DoorDash to acquire new customers.

Conclusion:

Thank you for reading my article and finding my insights. If you have any feedback or questions regarding this article, feel free to comment below. You can reach out to me at [email protected]. You can connect with me on LinkedIn and can find more articles written by me in my?Portfolio. I would love to have your suggestions.