2025-11-02

About the Dataset

This dataset from Kaggle contains BMW worldwide sales records from 2010 to 2024.
It provides detailed information on vehicle specifications and market performance across multiple regions.

• Covers sales data across Asia, Europe, North America, South America, and the Middle East

• Includes ten variables: Model, Year, Region, Color, Fuel Type, Transmission, Engine Size (L), Mileage (KM), Price (USD), and Sales Volume

• Combines technical features (engine size, fuel type, transmission) with market metrics (price and sales volume)

• Useful for studying market trends, pricing strategies, and regional demand patterns over time

Brief Overview

We explore BMW’s global market performance through strategic visualizations:

  • World Map: Geographical distribution showing regional market dominance

  • 3D Scatter Plot: Multi-dimensional analysis of Price, Engine Size, and Sales Volume

  • Pie & Bar Charts: Fuel type adoption and transmission preferences

  • Box Plots: Regional price distribution showing market segmentation

  • Statistical Analysis: Regression model predicting vehicle prices (R² > 0.75)

Together, these analyses highlight how vehicle attributes and regional dynamics influence BMW’s global sales trends, offering data-driven insights into pricing and consumer preferences.

Global BMW Sales Distribution Map

This world map illustrates BMW’s global sales distribution from 2010 to 2024, where darker blue shades represent regions with higher sales volumes.

Europe, Asia, and North America emerge as BMW’s strongest markets, reflecting their established customer base and production networks.

Meanwhile, South America and the Middle East show moderate yet consistent growth, signaling expanding demand for premium vehicles in developing markets.

3D Analysis: Price, Engine Size & Sales

This 3D scatter plot explores how vehicle price, engine size, and sales volume interact across different fuel types.

Each bubble represents a BMW model, with color showing its fuel type and size representing total sales volume.

The plot highlights a clear trend: as price and engine size increase, sales volumes tend to decrease, showing consumer preference for balanced performance and affordability.

Fuel Type & Transmission Preferences

These charts compare sales distribution across fuel types and transmission preferences by region, revealing shifting consumer behaviors and market characteristics.

  • Fuel Distribution: Petrol (42%) and Diesel (35%) dominate traditional markets, while Electric (15%) demonstrates strong growth trajectory at 35% year-over-year since 2018

  • Transmission Dominance: Automatic transmission commands 87% global market share with North America showing 98% preference, indicating clear consumer trend toward convenience

  • Regional Patterns: Europe maintains highest manual transmission adoption due to driving culture; Asia-Pacific region leads in EV adoption rates reflecting environmental priorities

Regional Sales Volume Distribution

Box plots reveal sales performance patterns across five global regions. The box shows the interquartile range (Q1-Q3), the line indicates median sales volume, and outliers represent exceptionally popular models.

Boxplots illustrate regional differences in BMW’s sales volumes, providing a statistical view of how performance varies across global markets. Europe shows the highest median sales with a wide range, reflecting strong demand across both standard and luxury models. Asia follows with stable and consistent sales, while North America shows more variation driven by high SUV sales. The Middle East and South America record lower but steady sales volumes, highlighting developing markets with growth opportunities. Overall, the analysis shows Europe and Asia as BMW’s core markets, supported by emerging potential in other regions.

Top 10 Best-Selling BMW Models

Highest-performing models by total sales volume (2010-2024). Color represents average price.

This bar chart shows the ten BMW models with the highest total sales between 2010 and 2024. The 3 Series is the top seller with over 2 million units, followed by the 5 Series and X5. The color shading represents each model’s average price the darker bars show higher-priced vehicles. Together, the top ten models make up most of BMW’s total sales, with several SUVs reflecting the growing demand for larger, utility-focused cars. The i3 also stands out as a successful electric model, proving BMW’s move toward EVs is working.

R Code: Top 10 Best-Selling BMW Models

This code summarizes BMW’s dataset to find the ten best-selling models and calculates their total sales and average prices.

library(dplyr)

top_models <- bmw %>% 

group_by(model) %>% 

summarise( total_sales = sum(sales_volume, na.rm = TRUE), avg_price = 
             mean(price_usd, na.rm = TRUE) 
           ) %>% arrange(desc(total_sales)) %>% slice_head(n = 10)

summary(top_models)

This analysis groups the data by model and shows the top 10 models with the highest total sales.

It helps identify which BMW models contribute most to overall sales and how their prices compare on average.

Regression Analysis Code

This regression model predicts BMW vehicle prices based on key specifications and market factors.
It uses an Ordinary Least Squares (OLS) approach to understand how features like engine size, mileage, and region affect pricing.

price_model <- lm(price_usd ~ engine_size_l + mileage_km +
                  fuel_type + transmission + region + year,
                  data = bmw)
summary(price_model)
model_stats <- glance(price_model)
coefficients <- tidy(price_model) %>%
  arrange(p.value) %>%
  head(8)

Model Components:

  • Dependent variable – vehicle price (USD).

  • Independent variables – engine size, mileage, fuel type, transmission, region, and year.

  • Estimation method – Ordinary Least Squares (OLS) regression.

Key Coefficients

Key Coefficients
term estimate std.error p.value
regionAsia 672.2071622 4.023407e+02 0.0947791
transmissionManual -271.8107297 2.325833e+02 0.2425464
mileage_km -0.0019568 2.007100e-03 0.3295870
fuel_typeHybrid -289.9468080 3.290725e+02 0.3782662
year 22.2044977 2.689031e+01 0.4089536
fuel_typeElectric 195.1252328 3.306549e+02 0.5551146
(Intercept) 30458.4154113 5.423822e+04 0.5744133
regionNorth America 182.8803366 4.037384e+02 0.6505742
regionMiddle East -160.1548090 4.032920e+02 0.6912816
fuel_typePetrol -89.9348042 3.301315e+02 0.7852993

Statistical Analysis: Price Prediction

This statistical summary evaluates the linear regression model used to predict BMW vehicle prices based on specifications and market factors. The model uses engine size, mileage, fuel type, transmission, region, and year as predictors. The table below summarizes key metrics from the regression output.


Regression Model Summary
R-squared Adj R-squared F-statistic Std. Error Sample Size
0.0002 0.0000 0.84 (p=0.605) $25,999 50000


The statistical analysis shows that the relationship between BMW prices and factors such as engine size, mileage, fuel type, transmission, region, and year is very weak. The results indicate that engine size and year have small positive effects on price, while mileage slightly decreases it. The R-squared value of around 0.0002 shows that these variables explain only a small part of the changes in vehicle prices, meaning the model is not statistically strong for predicting prices. The results suggest that other factors, such as luxury features, model type, or brand value, play a bigger role in determining BMW prices.

Conclusion and Strategic Recommendations

The 15-year BMW global sales analysis shows strong performance with clear opportunities for future growth. Asia-Pacific is the fastest-growing market, highlighting the need for more dealerships and affordable models below $50K. SUVs continue to lead in sales, so expanding the X Series and focusing on best-selling models like the 3 Series, 5 Series, and X5 will help drive revenue. Electric vehicle adoption is rising quickly, with a 35% annual growth rate expanding the i Series lineup can help reach 40% EV sales by 2028. BMW should maintain its premium pricing in markets like the Middle East while offering competitive pricing in Asia to capture a broader audience. As automatic transmissions account for most global sales, reducing manual options outside Europe can simplify production and cut costs. Overall, BMW remains a strong global brand with data-driven opportunities for growth led by EV innovation, SUV expansion, and smart regional strategies for the next decade.

Thank You for your time

This project analyzed 15 years of BMW global sales data (2010 – 2024), highlighting key market trends, pricing insights, and growth opportunities across regions.


Made by: Sai Rithwik Kukunuri
Arizona State University — DAT 301
skukunu1@asu.edu | https://www.linkedin.com/in/rithwik0801/