Analysing Instacart's data sets to extract insights and propose segmentation strategies. Performing data wrangling & subsetting, data consistency checks, combining & exporting data, deriving new variables, grouping data, and aggregating variables using Python. Employing Seaborn and Matplotlib libraries to produce visualisations to communicate insights to stakeholders.
Instacart is an online grocery store operating in the US and Canada. The company boasts strong sales figures, yet desires further understanding of their sales patterns. The stakeholders are primarily concerned with the diversity of customers within their database and their purchasing behaviours. They acknowledge the impracticality of targeting all customers using uniform methods and are contemplating a focused marketing approach. They aim to tailor marketing campaigns to distinct customer segments to evaluate their impact on product sales. The analysis will guide the formulation of this strategy, ensuring that Instacart effectively targets the appropriate customer profiles with relevant products.
- What are the busiest days of the week and hours of the day in terms of order volume?
- Are there specific times of the day when customers tend to spend more money?
- How can product pricing be simplified into more manageable price range groupings to streamline marketing and sales efforts?
- Which product categories exhibit higher popularity compared to others?
- How do customer segments differ in ordering behaviours based on factors like brand loyalty, loyalty status, regional differences, age, family status, demographics, and customer profiles?
The project files are organized into the following folders:
- 01 Project Management: includes the Project Brief.
- 02 Data: divided into two subfolders:
- Original Data: contains the original data frames.
- Prepared Data: holds cleaned and wrangled data frames, ready for analysis. (Data files not uploaded to GitHub due to size.)
- 03 Scripts: contains Jupyter notebooks with the analysis code.
- 04 Analysis: holds the visualisations used for developing and explaining insights.
- 05 Sent to Client: contains the final report presented in Excel.
Instacart is a real company that has made their data available online. However, the contents of the attached project brief have been fabricated by CareerFoundry for the purpose of this analysis.