Four audits, each ending in a recommendation. All four use public or synthetic datasets, not client data, and every figure is marked as observed in the data or modeled from it.
8 products carry 84.5% of profit in a $35.2M catalogue
The Profit Leak Diagnostic. Public dataset from Kaggle: 180,519 transactions, $35.2M in sales.
What the audit concludedRevenue is not the issue. Mistaking revenue for business health is. Profit here depends on 8 products, and the 28 weak ones should be sorted by cause before any are cut.
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Share of profit earned by 8 of 118 productsObserved in the data
84.5%
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Products with weak margins and high delivery failure, together only 2.2% of salesObserved in the data
28
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Profit at risk if the top 8 products lost 20% of margin, nearly 17% of total profitModeled scenario, not an actual loss
$643,000
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Slide deck (PDF)
Dashboard walkthrough (video)
Discounting costs $13.8M: a standing practice, not a targeted tool
Retail Discount Profitability Audit. Synthetic dataset (Microsoft Contoso), 223K+ transactions.
- Transactions sold at a discountObserved in the data61%
- Total discount cost6.3% of revenue, 11.3% of profit$13.8M
What the audit concludedDo not change pricing policy yet. Put a budget, an owner, and reason codes on discounts, then test a lower discount cap on the 10% to 20% tier.
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Late deliveries hurt reviews, and over 96% of customers never ordered again
Olist churn root-cause investigation. Public dataset from Kaggle: 113K+ Brazilian orders.
- Customers who never placed a second orderObserved in the data96.9%
- Average review score for on-time vs late ordersObserved in the data4.2 vs 2.5
What the audit concludedTreat late delivery and repeat purchase as two separate problems. Fix fulfilment to protect reviews, and test a second-purchase offer to win customers back.
Full case study
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Dashboard layout (PDF)
Top customers were worth 3.2x the average, and up to 40x an at-risk customer
UK retail customer lifetime value and segment analysis. Public dataset from UCI: 1M+ transactions, £17M+ revenue.
- Champion customer value against the average customerObserved in the data3.2x
- Extra revenue if customers moved up a segmentModeled opportunity, not realised revenue£390K+
What the audit concludedA Champion customer averaged £8,767 against £220 for an At-Risk one. A gap that size makes moving existing customers up a segment the first place to look.
Full case study
Watch the 3-minute walkthrough (video)