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🏋️‍♂️ Aerofit — Descriptive Statistics & Probability Analysis

Python Status Dataset License


📘 About Aerofit

Aerofit is a leading brand in the fitness equipment industry, offering a wide range of products including treadmills, exercise bikes, gym equipment, and fitness accessories.
The brand’s mission is to help people of all fitness levels achieve their health goals efficiently and comfortably.


🎯 Business Objective

The Aerofit Market Research Team aims to identify target audience characteristics for each treadmill model.
The objective is to recommend the most suitable treadmill to new customers based on their demographics, income, fitness level, and usage behavior.

Key Tasks:

  • Perform Descriptive Analytics to develop customer profiles for each treadmill.
  • Create Contingency Tables to compute marginal and conditional probabilities.
  • Derive insights and recommendations to support business decision-making.

🧾 Dataset Overview

📂 Dataset Link: Aerofit Treadmill Data

Feature Description

Feature Description
Product Purchased Type of treadmill: KP281, KP481, or KP781
Age Customer’s age (in years)
Gender Male / Female
Education Years of education completed
MaritalStatus Single / Partnered
Usage Average number of times the treadmill is used per week
Income Annual income (in USD)
Fitness Self-rated fitness level (1 = Poor, 5 = Excellent)
Miles Expected miles to walk/run per week

🏷️ Product Portfolio

Product Segment Price (USD) Description
KP281 Entry-Level $1,500 Basic treadmill for light users
KP481 Mid-Range $1,750 Ideal for regular runners
KP781 Premium $2,500 Advanced treadmill with high-end features

💡 Business Insights

📊 Key Findings:

  • 🔹 Most preferred product: KP281 (≈ 44.4% of total sales)
  • 🔹 Least sold product: KP781 (≈ 22.2%)
  • 🔹 Customer Characteristics:
    • KP781: Popular among high-income, high-fitness users with frequent usage (>4/week).
    • KP281: Favored by partnered customers with moderate income and lower usage (<4/week).
    • KP481: Customer profile similar to KP281, but with slightly higher income and fitness levels.
    • Education:
      • KP281 & KP481 buyers → typically education < 16 years
      • KP781 buyers → often education > 16 years
    • Gender Distribution:
      • Males: 55.8%
      • Females: 42.2%
    • Marital Status:
      • Partnered: 59.4%
      • Single: 40.6%
    • Usage Frequency:
      • Average = 3 times per week
    • Income Bracket (75th Percentile):
      • KP281 & KP481 → ≤ $53,000
      • KP781 → ≤ $90,000

📈 Probability Insights

Scenario Probability
Male & Single buying KP281 44.19%
Male & Partnered buying KP281 or KP481 34.43%
Female & Single buying KP281 43.33%
Female & Partnered buying KP281 58.7%

💬 Recommendations

1. Boost Awareness for Low-Reach Products
Increase promotional efforts for KP481 and KP781, which have lower market share.

2. Highlight KP481’s Value Proposition
Since KP281 and KP481 attract similar customers, market KP481 as a feature-upgraded version of KP281 to increase conversions.

3. Target Young Consumers
Introduce features like:

  • Music connectivity 🎵
  • Motion sensors 🏃‍♂️
  • Body temperature tracking 🌡️
  • Interactive virtual routes 🎮

4. Focus KP781 Marketing on High-End Users
Promote KP781 among high-income, male, and frequent treadmill users who value advanced performance features.

5. Strengthen Digital Presence
Leverage social media marketing and e-commerce platforms to reach a wider audience and enhance brand visibility.


🧠 Summary

This project uses Descriptive Statistics and Probability Analysis to uncover customer behavior patterns and preferences across Aerofit treadmill models.
These insights enable data-driven marketing strategies and help Aerofit align product recommendations with customer needs effectively.


🛠️ Tools & Technologies

Tool Purpose
Python (Pandas, NumPy, Matplotlib, Seaborn) Data cleaning, analysis & visualization
Excel Data summarization & cross-tabulation
Jupyter Notebook Exploratory Data Analysis
Probability Concepts Conditional & Marginal probability calculations

📚 Author

Ankit Verma
Data Analyst | SQL • Python • Power BI • Machine Learning
🔗 LinkedInGitHub


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About

Aerofit is a leading brand in the field of fitness equipment it provides products such as treadmills, exercise bikes, gym equipment. Aim is to identify customer characteristics for each type of treadmill to provide better recommendations for new customers.

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