Premium Portfolio Strategy

A Data-Driven Approach to Premium Assortment Planning

The business question: How should a wine store balance its red and white wine assortment to maximise the availability of higher-quality wines and meet customer expectations?

1. Business challenge:

A wine retailer wants to understand whether red or white wines offer a stronger representation in the higher-quality segment, and whether the two categories should receive different levels of shelf space.

Analytical approach:

• Compared quality-rating distributions across red and white wines.
• Tested whether the differences in quality distributions were statistically significant.
• Investigated chemical characteristics associated with higher-rated wines.
• Used correlation analysis, regression and principal component analysis (PCA) to identify quality-related patterns.

2. Findings:

Commercial recommendation:

• White wines: approximately 22% of observations fall into quality classes 7–9 top quality.

• Mean difference in top quality is 8,07% which is statistically significant.

• The most common rating is 6 for white wines (45%) and 5 for red wines (43%).

• Alcohol content is positively associated with quality for both wine types, while density tends to decrease as quality increases.

• The quality-rating distributions differ by wine colour, confirmed by Chi-squared test.

These findings suggest that white wines have a stronger representation in the higher-rated segment in this dataset.

3. Recommendation to the wine store

• Give white wines greater consideration when expanding the premium-quality range.
• Maintain a differentiated red wine selection, with particular attention to the characteristics associated with higher ratings.
• Use quality ratings to support product selection, alongside commercial indicators such as customer preferences, gross margin and price point.
• Review the assortment by quality tier rather than treating red and white wines as interchangeable products.