Finance & Investment

Cost-to-serve & margin leakage by customer

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.

  • Finance & Investment
  • Traceable reasoning
  • Runs anywhere
Preview methodology

2–3 weeks ~40 minutes

For a full population, not a sample

No coding required

Input
Documents, exports or uploads you already hold
Output
A structured, review-ready deliverable
Runs in
Skillsize · ChatGPT · Claude · Copilot
Export
SKILL.md · MCP
Time saved
~2–3 weeks per run

— USE CASES

What people use Cost-to-serve & margin leakage by customer for

Repeatable client analysis

Run the same structured analysis for every client or business unit so quality no longer depends on who picked up the work.

Faster first drafts

Turn raw source material into a working draft in minutes and spend your time on judgement instead of assembly.

Comparable results over time

Produce the same shape of output each cycle so movement is measurable rather than re-argued.

What it works from

  • Documents, exports or uploads you already hold
  • Your own criteria, framework or house method

What you get back

  • A structured, review-ready deliverable
  • A traceable record of what informed each conclusion

— HOW IT BEHAVES

How Cost-to-serve & margin leakage by customer produces its result

The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.

Row-level table processing

Every row of your table is processed on the same basis, however long the table is.

Charted, not just stated

The pattern is visualised from the computed data, so the trend is legible at a glance.

Composed as work product

Findings are written up as a document that reads like professional output rather than raw model text.

Enriched row by row

Each row gains derived columns from the analysis, keeping the source data and the judgement side by side.

Roll-up alongside detail

Detail rows are summarised into the grouped view without losing the underlying lines.

Why this is expensive by hand

Every finance & investment team needs cost-to-serve & margin leakage by customer — and almost none of them do it the same way twice. In practice it shows up as repeatable client analysis: run the same structured analysis for every client or business unit so quality no longer depends on who picked up the work. 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.

How this Skill produces it

As a Skill, the work is already sequenced. You bring the evidence, and the run produces a structured, review-ready deliverable plus a traceable record of what informed each conclusion. 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.

Who it's for

  • Independent consultants codifying their own methodology
  • Strategy and transformation teams standardising delivery
  • Internal advisory functions under pressure to produce faster
  • Operators who need defensible output, not a one-off chat answer

Run it in Skillsize — or export it anywhere

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.

ChatGPTClaudeCopilotAI Products (MCP)

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