Assessing Impact of Competitor Market Entry

Analyzes the impact of a competitor entering an adjacent market.

---

Note: Data is Randomly Generated

For demonstration purposes, the data are randomized and all naming is fictitious.

# Load packages and functions
source('docs//00-Reused-Code/Read-Library-and-Functions.R')

set.seed(1024) # All data is randomized! Seed set for reproducibility

this_dir <- 'docs//01-Visual-Storytelling//02-Post-Mortem//'

# Date of the Competitor Entry:
date_competition_enters = Sys.Date() - 120
selected_stores = c('Flagship Store' )

# Read in a reference file for drive times destinations
dt_ref <- fread(paste0(this_dir, 'data//drivetime_ref.csv'))

# Get the R files containing the functions with plots --------------------------
purrr::walk(list.files(paste0(this_dir, 'functions//'), pattern = "\\.R$", full.names = TRUE), source)

Within the deliverable, this analysis shows that core KPIs soften across stores, suppliers, in-store sections, and subscribers.

1 Enterprise Operating Income per Store per Day Declines After Competitor Entry

Daily performance lagged the 6–12 month trend after entry.

See full function here.

## Individual Store Trends
plots_store_analysis <- store_analysis(
  selected_stores = c('Flagship Store', 'Other Stores'),
  comparison_date = date_competition_enters
)

# plots_store_analysis$plots$overview
plots_store_analysis$plots$operating_income_per_store_per_day

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2 Within the Flagship Store, Section Performance has Uniformly Decreased

High-traffic sections lost share post-entry.

See full function here.

# Specific Zone vs. Nearby Zones vs. Broader Floor
plots_section_of_store_analysis <- section_of_store_analysis(
  comparison_date = date_competition_enters
)

plots_section_of_store_analysis$plots$overview

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3 Supplier Performance has Dropped Proportionally

Key suppliers lost volume in line with subscriber erosion; supplier mix remained steady.

See full function here.

plots_supplier_analysis <- supplier_analysis(
  selected_stores = selected_stores,
  comparison_date = date_competition_enters
)

plots_supplier_analysis$plots$overview

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4 Subscribers Trend Lowers since New Competitor Entry

New subscriptions slowed and churn accelerated; cumulative subscribers underperformed the 12-month baseline.

See full function here.

## Patron subscribers
subscribers <- subscriber_demographic_analysis(
  comparison_date = date_competition_enters
)

subscribers$plots$overview

4.0.1 Subscriber Breakdown by Drivetime

subscribers$plots$demographics

4.0.2 Subscriber Comparison

• Since expanding, daily subscribers have been less than on average than in the past 12-months.
• The cumulative actual subscribers since expanding drifts far below the historical baseline. “Baseline” refers to the 12-month average subscribers.

subscribers$plots$cumulativeVariance

subscribers$plots$detail

4.1 Shrinking New Subscribers

Prospect pools thinned around the Flagship after entry; conversion windows narrowed and acquisition costs rose.

4.1.1 Reference of Current Drivetimes to Flagship Store

library(knitr)
knitr::kable(dt_ref)

Destination	Hours
Fayetteville	0.50
Springdale	0.75
Tulsa	1.50
Fort Smith	1.75

4.1.2 Shrinking New Subscribers in Key Markets

See full function here.

# Average Drivetime Analysis
plots_subscriber_drivetime_analysis <- subscriber_drivetime_analysis(
  comparison_date1 = date_competition_enters,
)

plots_subscriber_drivetime_analysis$plots$overview

plots_subscriber_drivetime_analysis$plots$drive_distributions_market

4.2 Appendix: Subscriber-Base Distributed Evenly Across United States

See full function here.

subscriber_geography_analysis()