Ademola Ibitayo
A tech company's product was analysed to discover insights on the product subscriptions, usage and customer experience to develop strategies to improve customer experience and boost revenue. The analysis involves the application of different SQL methods to answer business questions.
- Summarized Customer Data for Leadership by Combining Aggregate Functions with CTEs
- Calculated descriptive statistics for monthly revenue by product using CTE
- Exploring variable distribution with CTE
- Analysed Payment Funnel to identify the furthest point in the payment process for customers using CTEs
- Recoded and Bucketed Values using CASE
- Created Binary Columns with CASE
- Pivoted rows into aggregated columns with CASE
- Recoded and Bucketed Values using CASE
- Created Binary Columns with CASE
- Pivoted rows into aggregated columns with CASE
- Pulled employee/manager data based on hierarchical relationships with a SELF JOIN
- Compared month-over-month (MoM) Revenue across to identify months when revenue was up using SELF JOIN.
- Extracted the data for the most recent sale per sales rep using Window Function- ROW_NUMBER()
- Tracked Sales Quota Progress over Time by Running Totals using SUM()
- Tracked User Payment Funnel Times by timestamp difference using LEAD()
View the full project on GitHub - https://github.com/AdemolaI/Analysis-of-Tech-Product-Usage-and-Customer-Experience-with-SQL