Identifying High-Performing HCPs: Sales Per Minute and Conversion Rate Analysis Based on Interactions
Requirement
Introduction: To analyzes interaction duration, follow-ups, and meetings to identify efficient HCPs based on high sales per minute and conversion rates with optimal interaction efforts.
Requirements:
Read the table “purgo_playground.hcp_efficient_analysis“.
Add Revenue Conversion Flag calculate: Revenue_Converted_Flag, is added with values are set to 1 if the interaction resulted in revenue conversion (Revenue_Converted = "Yes"). 0 otherwise (Revenue_Converted = "No"). Group the data by HCP’s (HCP_ID)with Count of interactions for each HCP, Sum of the duration of all interactions for each HCP, Average time spent per interaction for each HCP, Total sum of follow-ups conducted by each HCP, Total sum of Sales generated by each HCP. Number of successful revenue-generating interactions for each HCP, sum of Revenue_Converted_Flag divided by count of Interaction_Type with multiply by 100 as percentage count, sum of Sales_Amount divided by sum of Duration_Minutes .
Final Output: Show the results of HCP’s wise high performance wise Sales per minute.
Write the Pyspark code without syntax error.
Unity catalog: purgo_playground.hcp_efficient_analysis