This following document shows a basic example of the type of analysis that could be extracted from this group project. With Research Question 2, a key objective is analyzing Lincoln Financials’ social media over their key competitors. Therefore, I chose to use a stacked column chart to show and compare the social media data of the financial institutions. Sample data was compiled manually into Excel for the purposes of this initial project discussion; however, more efficient methods would be used to pull relevant data later.

Accumulated Instagram data of Lincoln Financial and Prudential (Extracted Website: Social Blade; Figures from Jan 2023-Sep 2024)

library(readr)

data <- read_csv("SampleIGDataForProject.csv")
## Rows: 42 Columns: 4
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): Month, Company
## dbl (2): FollowersGained, MediaPosted
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
# Structure dataset
str(data)
## spc_tbl_ [42 × 4] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
##  $ Month          : chr [1:42] "Jan-23" "Jan-23" "Feb-23" "Feb-23" ...
##  $ FollowersGained: num [1:42] 308 248 218 402 232 434 193 285 92 248 ...
##  $ MediaPosted    : num [1:42] 0 7 0 12 0 9 0 11 0 15 ...
##  $ Company        : chr [1:42] "Lincoln" "Prudential" "Lincoln" "Prudential" ...
##  - attr(*, "spec")=
##   .. cols(
##   ..   Month = col_character(),
##   ..   FollowersGained = col_double(),
##   ..   MediaPosted = col_double(),
##   ..   Company = col_character()
##   .. )
##  - attr(*, "problems")=<externalptr>
# Show first 6 rows of dataset
head(data)
## # A tibble: 6 × 4
##   Month  FollowersGained MediaPosted Company   
##   <chr>            <dbl>       <dbl> <chr>     
## 1 Jan-23             308           0 Lincoln   
## 2 Jan-23             248           7 Prudential
## 3 Feb-23             218           0 Lincoln   
## 4 Feb-23             402          12 Prudential
## 5 Mar-23             232           0 Lincoln   
## 6 Mar-23             434           9 Prudential

Sample Analysis

library(ggplot2)

# Lincoln vs. Prudential Followers Gained
 ggplot(data, aes(x = Month, y = FollowersGained, fill = Company)) +
      geom_col(position = "stack") +
      coord_flip() +
      labs(title = "Comparison of Total Monthly Followers Gained by Lincoln and Prudential", x = "Month", y = "Followers Gained")

# Lincoln vs. Prudential Media Posted During the Same period
ggplot(data, aes(x = Month, y = MediaPosted, fill = Company)) +
      geom_col(position = "stack",) +
      coord_flip() +
      labs(title = "Comparison of Total Monthly Media Posted by Lincoln and Prudential", x = "Month", y = "Media Posted")

These results show that Prudential outweighs Lincoln with monthly IG followers gained and IG media posted in this specific period. This conclusion must further be supported by testing the correlation and strength of these figures, while adding other social media platforms where previous data exists. The chart should also be reordered chronologically.

Credit: https://socialblade.com/instagram/user/prudential

https://socialblade.com/instagram/user/lincolnfinancial