THE RESULT
What the data shows
The largest computed metric is 1 for 1.0; the smallest is 0.06391 for 0.01. Metric: spend_share (Share of annual spending).
No margin or exposure data are supplied; customer concentration is not the same as credit risk.
| top customer fraction | customers | spend share |
|---|---|---|
| 0.01 | 5 | 0.06391 |
| 0.05 | 22 | 0.1776 |
| 0.1 | 44 | 0.276 |
| 0.2 | 88 | 0.429 |
| 0.5 | 220 | 0.7442 |
| 1 | 440 | 1 |
THE METHOD
From source to answer
Rank customers by total observed spending and compute concentration at fixed top fractions.
The Python source exposes this study’s transformations. The complete project download includes shared preparation and evaluation routines.
THE NEXT DECISION
What follows from the finding
Consider account-service concentration while avoiding assumptions about profitability.
Where the conclusion stops
Annual customer spending uses source monetary units, not an assumed currency. There are no margins, transactions or dates. Customer segments are descriptive and do not establish promotion response.
Related studies may reuse observations or holdouts. These are historical analyses; associations and backtests do not demonstrate commercial impact. Further model tuning needs new, untouched evaluation data.