This project evaluates whether ABG Motors, a Japanese automobile manufacturer, should enter the Indian automotive market. The analysis leverages data-driven modeling and predictive analytics to support a strategic market entry decision.
Using historical Japanese market data as the training base, a logistic regression classification model was developed to predict car purchase likelihood. The model was then applied to an Indian customer dataset to project potential sales and assess market viability.
- Sales Forecast Validation – Estimate potential car sales in India and compare with ABG Motors’ break-even threshold of 12,000 cars/year.
- Model Development – Build and validate a logistic regression model using Japanese customer data.
- Model Transferability – Test the model on Indian data to check if consumer behavior patterns align across the two markets.
- Strategic Recommendation – Provide evidence-based insights for the company’s market entry decision.
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Tools Used: Python, Microsoft Excel, Tableau
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Techniques: Logistic Regression, Exploratory Data Analysis (EDA), Data Visualization, Model Validation
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Datasets:
- Japanese Dataset: 40,000 customer records with purchase outcomes
- Indian Dataset: 70,000 potential customer records for projection
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Model Accuracy: 97.98%
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AUC Score: 0.74
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Projected Sales in India: 35,209 cars, exceeding the target of 12,000 cars by ~293%
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Top Predictors:
- Annual income (strongest positive impact)
- Age of current car (replacement cycle indicator)
- Customer age (negative correlation with purchase likelihood)
- Gender (males 26.7% more likely to buy)
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Indian and Japanese markets show similar demographic and behavioral trends, validating model transferability.
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Indian market characterized by:
- Balanced gender representation
- Strong middle-to-upper income segments
- Purchase readiness linked to maintenance cycles
The analysis strongly supports ABG Motors’ entry into the Indian market, with projected sales well above the break-even threshold. The logistic regression model effectively demonstrated cross-market applicability, providing quantitative backing for strategic decision-making.
Final Recommendation:
Proceed with market entry through a phased expansion strategy focused on major metropolitan areas, with continuous performance monitoring and model recalibration.