Purpose

Overall AOV: $305.16 (median $313.2) \u2014 The store's typical order value centers around $310, with relatively tight clustering (std dev $135.37)
AOV Growth: -19.8% \u2014 Significant declining trend from July 2024 ($323.46) to November 2024 ($285.90), indicating weakening order values over the analysis period
Multi-Item Orders: 65.9% \u2014 Two-thirds of orders contain multiple items; 3-item orders average $476.01 versus $153.03 for single-item orders
Vendor Performance: Hoka ($398.52 AOV) and Nike ($359.10 AOV) drive premium orders, while Lululemon ($193.70 AOV) underperforms despite 5 orders

This section documents the data transformation from raw Shopify export format to analysis-ready order-level data. The 51.2% retention rate reflects the aggregation of multi-row line-item records into 41 unique orders, which is essential for accurate Average Order Value (AOV) calculation and trend analysis.

Key Findings

Retention Rate (51.2%): Nearly half the initial rows were removed, but this is expected and appropriate—the raw export contained 80 line-item rows that consolidated into 41 unique orders, not data loss.
Rows Removed (39): These represent duplicate order entries across multiple line items per order, not quality issues or missing data.
No Train/Test Split: Analysis uses descriptive statistics across the full 41-order dataset rather than predictive modeling, aligning with the stated objective of trend analysis.

Interpretation

The preprocessing successfully transformed Shopify's line-item export format into order-level aggregates required for AOV analysis. The 51.2% reduction is a natural consequence of consolidating multi-item orders, not a data quality problem. This approach preserves all revenue and order information while enabling accurate calculation of metrics like overall AOV ($305.16) and vendor-level performance across the complete order population.

Context

The assumptions document confirms this transformation logic: "Total column populated only