Food is at your Doordash with one click! :Excel-Based Marketing Analysis

Food is at your Doordash with one click! :Excel-Based Marketing Analysis

INTRODUCTION,

One day, I was at my mom's place and feeling really hungry. I suggested cooking pasta, but she thought we should order pizza because there was a discount on DoorDash. It made me realize that even though my mom didn't grow up with the internet, she now uses it a lot, especially for online orders after the COVID situation.

This got me thinking about who uses these platforms the mosthow much money they make, and whether discounts and campaigns really make a difference in what people choose.

So, I did some research, focusing on DoorDash, a popular food delivery service in the United States. In this report, I'll look at the data to help us understand how these digital platforms are influencing our choices. Here's what I learned:


KEY TAKEAWAYS,

  • The dataset has information on 2021 customers ranging in age from 24 to 80.
  • The total spending on the platform amounted to $1.14 million.
  • People who have more income tend to spend more on platforms.
  • The 36–50-year-old age group is making the top contributors to the platform's overall spending.
  • Campaign number 6 was identified as the most successful.

due to high demand among the customers.

  • The best-selling product is wine.


ANALYSIS

When your income increases, you are more likely to spend on platforms such as a food delivery service. This is a scatter plot chart that describes the positive correlation between total spending and household income.

In the chart, the coefficient of determination (R²) is 0.67. This information can be used as an example in analysis with 67% accuracy.


 In this histogram, you can see how much money DoorDash customers are spending. The majority of customers tend to spend small amounts. Specifically, more than 1000 customers have spent an amount ranging from $4 to $418.50. Additional detail is that over 200 customers spend between $418.50-$1247.50.



Graphs are displaying a total spending of $41,072. It becomes evident that the age group with the highest expenditure is 36-50, closely followed by the 51-65 age bracket. Notably, when we look at the income distribution, these age groups have the highest incomes.


Six different campaigns have been attended by participants across different age groups. Campaign 6 stands out as the most popular, with 138 individuals joining from the 36-50 age group, suggesting a preference for discounts and campaigns within this demographic.

Interestingly, the enrollment from Campaign 5 to Campaign 6 more than doubled, indicating a notable increase in interest. It may be worthwhile to conduct further research to understand why this has increased. In contrast, Campaign 2 appears to be the least successful among the campaigns.


Wine stands out as the top-selling product across all consumer groups, followed closely by meat.

To maximize the advantage of the popularity of wine, it would be beneficial to look into customer purchasing patterns.

By strategically placing complementary items in close proximity to wine displays, we can encourage customers to explore additional products.

This approach may result in increased sales and a more engaging shopping experience. Understanding the items frequently purchased alongside wine allows for a targeted approach to product placement and promotion, enhancing overall sales performance. 


January and March were the most popular months for customers to enroll to platform, whereas November and December had the lowest number of new customers.

 

SUGGESTION AND CONCLUSİON

 In this analysis, we learned that people love DoorDash and the convenience it brings.

Key findings from the analysis reveal a positive correlation between income and spending on the platform. The data emphasizes that as income increases, so does expenditure on food delivery services. Moreover, the age group of 36-50 emerged as the top contributors to DoorDash's overall spending. This age group can be a target demographic for future marketing efforts. In contrast, the age group of 24-35, which tends to spend the least, can be effectively targeted by a team using popular digital platforms like Instagram and TikTok for advertising.

The success of Campaign 6 highlights the effectiveness of promotions, indicating a preference for discounts among middle-aged consumers. This information could have a significant impact on marketing strategies to attract and retain customers.

Furthermore, the popularity of wine as the top-selling product presents an opportunity for strategic product placement and promotion. Understanding customer purchasing patterns related to wine allows for targeted marketing and overall sales performance.

The company should consider adjusting its marketing calendar to align with customer sign-up trends.

In conclusion, adapting marketing approaches to align with customer demographics and preferences, especially considering income levels and age groups, can contribute to DoorDash's continued success in the competitive market.

 

Note :

The dataset I've used is provided as part of Avery Smith's Data Analytics Accelerator program. The original dataset came from Kaggle, from a company called iFood, which is Brazil's version of DoorDash. This data is used in the hiring process for data analysts. 


Thank you for taking the time to read my article!

I am constantly learning and improving my data skills, and I would love to hear your feedback, questions, and suggestions.

Let’s Connect on LinkedIn!

Saad Abdul Rauf

Cloud Data Architect at Small World FS | Transforming Organizations with Data-Driven Solutions

8mo

🤩 Amazing good job Ezgi Soylu 🫡

Kathy Mucher

Academic Data Analyst at Pearson Virtual Schools

9mo

Ezgi Soylu, great marketing insights! Well done! 👏

Aksha Hrudhai K

Pricing and Freight Analyst @Parts For Trucks || Microsoft EXCEL || Microsoft SQL Server || Tableau Desktop || Power BI || Python || Agile || Data Visualization ||

9mo

That's a great article Ezgi Soylu 👏. Great graphs and good conclusion at the end.

Stuart Walker

Fraud Prevention Analyst @ M&G PLC | Data Analyst | Python | SQL | Data Analytics | Excel | Tableau | Power BI | R

9mo

Good job Ezgi 👏💪👏

Lisa D'Cruz

Data Analyst || I effectively communicate data-driven insights 📊 Python | SQL | Excel | Data Visualization | Data Analytics

9mo

Nice report, Ezgi Soylu, with valuable suggestions for better future iFood marketing campaigns!

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