Project Link

About this project

The Online Food Ordering Analysis was created to understand the characteristics and behaviour of customers using an online food ordering service. The analysis explores customer demographics, socioeconomic characteristics, feedback, family size, customer types, and ordering outcomes to identify patterns within the dataset.

Business Questions

• • Who are the customers using the online food ordering service?
• • How are customers distributed across income, age, education, occupation, and family size?
• • How do customers rate their experience?
• • Does customer feedback differ by gender?
• • How do ordering outcomes vary across customer types?

Key Insights

• • Positive feedback was higher than negative feedback, with 317 positive responses compared with 71 negative responses.
• • Positive and negative feedback proportions were relatively similar across male and female customers.
• • Ordering outcomes varied across New, Regular, and Frequent customers.
• • Customer type showed different distributions across marital status groups.
• • Customer distribution varied across different family sizes.

Recommendations

• • Monitor negative feedback and investigate the issues behind negative customer experiences.
• • Analyse Frequent and Regular customers to better understand customer retention.
• • Use customer characteristics for more targeted customer segmentation.
• • Track customer feedback regularly to identify changes in customer experience.
• • Further investigate factors influencing ordering outcomes across customer types.

Tools Used