I would like to include the number of sales representatives and sales assistens in my sales process as a factor that influences revenue. How can I do that? # Number of Sales Assistants (Appointment) and Number of Sales Representatives (Conversion)number_of_sales_assistants <- 10 # Sales assistantsnumber_of_sales_representatives<- 5 # Sales representatives#Sales process based on binomial distribution#Basic sales process#Leadsleads <- rbinom (1, target_group, lead_rate)total_lead_cost <- leads * lead_cost#Appointmentsappointments <- rbinom(1, leads, appointment_rate_assistant)total_appointment_cost <- appointments* appointment_cost#Conversionsconversions <- rbinom (1, appointments, conversion_rate_representative)total_conversion_cost <- conversions conversion_cost*# Revenuerevenue <- conversions * average_order_value_new# Coststotal_costs <- total_lead_cost + total_appointment_cost + total_conversion_cost# Profitprofit <- revenue total costs

Answered: I would like to include the number of…

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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I would like to include the number of sales representatives and sales assistens in my sales process as a factor that influences revenue. How can I do that?

# Number of Sales Assistants (Appointment) and Number of Sales Representatives (Conversion)
number_of_sales_assistants <- 10 # Sales assistants
number_of_sales_representatives
<- 5 # Sales representatives
#Sales process based on binomial distribution
#Basic sales process
#Leads
leads <- rbinom (1, target_group, lead_rate)
total_lead_cost <- leads * lead_cost
#Appointments
appointments <- rbinom(1, leads, appointment_rate_assistant)
total_appointment_cost <- appointments* appointment_cost
#Conversions
conversions <- rbinom (1, appointments, conversion_rate_representative)
total_conversion_cost <- conversions conversion_cost
*
# Revenue
revenue <- conversions * average_order_value_new
# Costs
total_costs <- total_lead_cost + total_appointment_cost + total_conversion_cost
# Profit
profit <- revenue total costs

Expert Solution

Step 1: Introduction

This answer proposes an approach to model the sales process in a way that includes the number of sales representatives and sales assistants as crucial variables. By doing so, we can build a more accurate and comprehensive model to predict and analyze sales outcomes.

Algorithm

The algorithm is built on the R language and involves several stages:

Initialization: Set the number of sales assistants and representatives, along with other sales metrics like lead rate, appointment rate, and conversion rate.
Lead Generation: Calculate the total number of leads generated based on the lead rate and the maximum number of leads each sales assistant can handle.
Appointment Scheduling: Determine the total number of appointments scheduled by taking into account the appointment rate and the maximum number of appointments each assistant can handle.
Conversions: Calculate the total number of sales converted by considering the conversion rate and the maximum number of conversions each sales representative can handle.
Revenue, Cost, and Profit Calculation: Revenue is calculated as the product of conversions and average order value. Costs include costs for leads, appointments, and conversions. Profit is then derived by subtracting the total cost from the total revenue.

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