This repository contains my solution to the Quantium Data Analytics Virtual Experience Program on Forage.
Quantium is a leading data science and AI firm, founded in Australia in 2002. Quantium combines the best of human and artificial intelligence to power possibilities for individuals, organisations and society.
You are part of Quantium's retail analytics team and have been approached by your client, the Category Manager for Chips, who wants to better understand the types of customers who purchase Chips and their purchasing behaviour within the region.
Conduct analysis on your client's transaction dataset and identify customer purchasing behaviours to generate insights and provide commercial recommendations.
- Examine transaction data - look for inconsistencies, missing data across the data set, outliers, correctly identified category items, numeric data across all tables. If you determine any anomalies make the necessary changes in the dataset and save it. Having clean data will help when it comes to your analysis.
- Examine customer data - check for similar issues in the customer data, look for nulls and when you are happy merge the transaction and customer data together so it’s ready for the analysis ensuring you save your files along the way.
- Data analysis and customer segments - in your analysis make sure you define the metrics – look at total sales, drivers of sales, where the highest sales are coming from etc. Explore the data, create charts and graphs as well as noting any interesting trends and/or insights you find.
- Deep dive into customer segments – define your recommendation from your insights, determine which segments we should be targeting, if packet sizes are relative and form an overall conclusion based on your analysis.
Extend your analysis from Task 1 to help you identify benchmark stores that allow you to test the impact of the trial store layouts on customer sales.
- Select control stores – explore the data and define metrics for your control store selection – think about what would make them a control store. Look at the drivers and make sure you visualise these in a graph to better determine if they are suited. For this piece it may even be worth creating a function to help you.
- Assessment of the trial – this one should give you some interesting insights into each of the stores, check each trial store individually in comparison with the control store to get a clear view of its overall performance. We want to know if the trial stores were successful or not.
- Collate findings – summarise your findings for each store and provide an recommendation that we can share with Julia outlining the impact on sales during the trial period.
- Remember when working with a client visualisations are key to helping them understand the data. Be sure to save all your visualisations so we can use them later in our report. We are presenting to our client in 3 weeks so if you could submit your analysis by mid next week that will give us great amount of time to discuss findings and pull together the report.