A crowdfunding site wants to run a marketing campaign for the next quarter of the year. The marketing manager wants to target those segments that have donated the most in the past year.
- What are the top three categories in terms of total donations?
- What device type has historically provided the most contributions?
- What age bracket should the campaign target?
- The average donation was
$39.4dollars with the lowest and highest donations being
- Gaming, marketing and fashion category have contributed most in the past year with total donations amounting to
- More donations were made from ios platforms with a high percentage of
- Half of the donations made in the past year came from teenagers and adolescents within the age group
- Since the majority of donors fall in the age group 18-24 and are mostly known for the age group to be mostly online. The marketing manager should target this age group and also users on the ios platforms.
- Though gaming, marketing and fashion have the highest amount of donations, the difference is not that much with other categories and I will advise the marketing manager to target all categories.
category– “Sports”, “Fashion”, “Technology”, etc.
device– the type of device used.
gender– gender of the user.
age range– one of five age brackets.
amount– how much the user donated in Euros.
library(tidyverse) data <- read_csv("C:/Users/Adejumo/Downloads/crowdfunding.csv") skimr::skim(data)
|Number of rows||20658|
|Number of columns||5|
|Column type frequency:|
Variable type: character
Variable type: numeric
The amount of donation is normally distributed with mean of
$39.4, the minimum and maximum donation respectively are
Top categories in terms of total donations
data %>% group_by(category) %>% summarize(total_price = sum(amount)) %>% ggplot(aes(x = reorder(category, total_price), y = total_price, fill = category)) + geom_col() + geom_text(aes(label = scales::comma(total_price)), hjust = 1) + coord_flip() + xlab("Category") + ylab("Total Price")
The top three categories in terms of total donations is games, environment and fashion.
Device type with the most contributions
data %>% group_by(device) %>% summarize(count = n()) %>% mutate(percent = prop.table(count)) %>% ggplot(aes(x = device, y = percent, fill = device, label = scales::percent(percent))) + geom_col(position = 'dodge') + geom_text(position = position_dodge(width = .9), vjust = -0.5, size = 3) + scale_y_continuous(labels = scales::percent) + xlab("Device type") + ylab("Percentage of donors")
Most donations have come from those using ios platforms which constitutes 65% of donors.
What age bracket should the campaign target?
data %>% group_by(age) %>% summarize(count = n()) %>% mutate(percent = prop.table(count)) %>% ggplot(aes(x = reorder(age, percent), y = percent, fill = age, label = scales::percent(percent))) + geom_col(position = 'dodge') + geom_text(position = position_dodge(width = .9), vjust = -0.5, size = 3) + scale_y_continuous(labels = scales::percent) + coord_flip() + xlab("Age groups") + ylab("Percentage of donors")
The age group 18-24 which are teenagers and adolescents have the highest percentage of donors.
Distibution of donations
data %>% ggplot(aes(x = amount)) + geom_density()
Most donations made lie between 25-50 dollars.