Customer profitability review
Shows which customers generate contribution and which make a loss after allocated costs. A ranked view helps focus management attention on relationships that erode profitability.
— Finance & Investment
Joins revenue to allocated cost per customer, derives true contribution margin, and names the loss-makers with the price rise each needs to reach your target margin.
2–3 weeks → ~40 minutes
For a full population, not a sample
No coding required
— USE CASES
Shows which customers generate contribution and which make a loss after allocated costs. A ranked view helps focus management attention on relationships that erode profitability.
Produces a shortlist of accounts for renegotiation, with the price increase each needs to reach the target margin at current volumes and allocated costs.
Examines contribution margin at customer-product level where the data supports it. Highlights likely leakage from pricing, product mix, discount creep or service intensity to support more focused commercial recommendations.
Makes the margin impact of allocated service costs visible across customer relationships. Helps distinguish accounts that need pricing attention from those that warrant a review of service demands.
— HOW IT BEHAVES
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Each row of your export is processed on the same basis, so no line item is skipped however long the table is.
Movement across the reporting period in scope is visualised from the computed data, so the trend is legible at a glance.
Findings on the reporting period in scope are written up as a document that reads like professional output, with each claim tied back to a line item.
Derived columns are added row by row, keeping your source data and the judgement about each line item side by side.
Detail rows are summarised into the grouped view of the reporting period in scope without losing the underlying line items.
Customer revenue can hide unprofitable relationships when discounts, product mix and service demands absorb the margin. In practice it shows up as customer profitability review: shows which customers generate contribution and which make a loss after allocated costs. A ranked view helps focus management attention on relationships that erode profitability. The value sits in the rigour, not the typing — yet the rigour is exactly what gets traded away when there is only 2–3 weeks of capacity for it.
As a Skill, the work is already sequenced. You bring the evidence, and the run produces contribution margin analysis by customer and, where available, by product plus ranked loss-making customer and product combinations. The criteria, ordering and review points that make the answer trustworthy are encoded in the Skill itself — which is the difference between a structured method and a prompt someone pastes in. Net effect: 2–3 weeks down to ~40 minutes, no drift between runs, and every conclusion traceable back to the evidence behind it.
Cost-to-serve & margin leakage by customer exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.
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