This project is based on a ride-sharing application data that has the purpose to respond to 5 business questions and provide further insights based on the data:
- What steps of the funnel should we research and improve? Are there any specific drop-off points preventing users from completing their first ride?
- Metrocar currently supports 3 different platforms: ios, android, and web. To recommend where to focus our marketing budget for the upcoming year, what insights can we make based on the platform?
- What age groups perform best at each stage of our funnel? Which age group(s) likely contain our target customers?
- Surge pricing is the practice of increasing the price of goods or services when there is the greatest demand for them. If we want to adopt a price-surging strategy, what does the distribution of ride requests look like throughout the day?
- What part of our funnel has the lowest conversion rate? What can we do to improve this part of the funnel?
- Finish the presentation video, review the report.
- Adjust global filter definitions and organize graphics based on dataset to avoid repetitions.
- Introduce and reformat all of the Python to use Dash Library for a better user experience.
- Instead of multiple SQL files, combine most of them in a global CTE and filter out the final result for some of them based on the needed data.