Executive Decision Support Platform
E-Commerce CEO Executive Dashboard
Commercial behavior intelligence derived from 109,950,743 event records (~13.7 GB raw dataset).
“If I were CEO, what are the 10 most important things I must know, and what will I do?”
Prioritized strategic findings translating behavioral evidence into concrete actions, expected revenue impact, and validation experiments.
Cart Abandonment is the Single Largest Business Leakage (~83.6% Drop-off)
Out of 2.8M sessions that added items to cart, only ~460K completed a purchase.
The store attracts strong buyer intent, but fails at the transaction conversion stage.
Revenue is Highly Concentrated in Top 5% of Products (72% of Total Sales)
Out of ~160,000 catalog items, a top tier of ~8,000 items drives almost three-quarters of revenue.
High revenue risk if top key SKUs experience supply chain or stockout issues.
Apple & Samsung Dominate Revenue, But Xiaomi Represents Untapped Conversion Upside
Apple generates 41% of revenue; Xiaomi gets huge traffic but converts at only 1.1%.
Xiaomi visitors are price-comparing and hesitating before cart checkout.
Smartphone Category Drives 68% of Total Store Revenue
`electronics.smartphone` accounts for the vast majority of carts and GMV.
The store is fundamentally a mobile electronics retailer; other categories are secondary.
Remove-from-Cart Events Peak in $300-$700 Price Band
Upper-mid tier items have a 28% higher removal rate than budget items (<$50).
Sticker shock occurs when shipping/taxes are added at checkout.
Over-Browsing (>10 Views/Session) Correlates with Lower Conversion
Sessions with 1-3 views convert at 3.2%, whereas sessions with 15+ views drop to <0.8%.
Users getting lost in catalog clutter become fatigued and leave.
Peak Purchasing Hours Occur Between 10:00 AM and 3:00 PM UTC
Orders and conversion rate peak midday, while evening sessions are browsing-heavy.
Shoppers make final buying decisions during work/daytime hours.
Low Cross-Sell Co-Occurrence (<5% Accessory Attachment)
Fewer than 1 in 20 smartphone orders include a case, memory card, or charger.
Missed high-margin cross-sell revenue opportunities at point of purchase.
Window Shoppers Represent 64% of Total Visitor Traffic
Over 6 out of 10 users leave without ever adding an item to cart.
Top-of-funnel traffic quality or initial landing page relevance is low.
Current Behavioral Dataset Lacks Order, Margin & Marketing Source Fields
Dataset provides event logs but lacks order grouping, discounts, and CAC attribution.
We can model revenue proxy and conversion, but cannot calculate net profit or ROAS.
Daily Events — Views, Carts, Purchases
Daily Revenue (USD, thousands)
Hourly Activity Pattern (UTC)
Average events per hour across all days in the dataset