THE RESULT
What the data shows
The largest computed metric is 0.146 for (0.0, 1.0]; the smallest is 0.0393 for (10.0, inf]. Metric: rate (Subscription share).
Campaign includes the recorded contact. This association cannot estimate the effect of placing one more call.
| contact band | events | n | rate | wilson lower | wilson upper |
|---|---|---|---|---|---|
| (0.0, 1.0] | 2,561 | 17,544 | 0.146 | 0.1408 | 0.1513 |
| (1.0, 2.0] | 1,401 | 12,505 | 0.112 | 0.1066 | 0.1177 |
| (10.0, inf] | 47 | 1,196 | 0.0393 | 0.02968 | 0.05187 |
| (2.0, 3.0] | 618 | 5,521 | 0.1119 | 0.1039 | 0.1205 |
| (3.0, 5.0] | 456 | 5,286 | 0.08627 | 0.07899 | 0.09414 |
| (5.0, 10.0] | 206 | 3,159 | 0.06521 | 0.05712 | 0.07436 |
THE METHOD
From source to answer
Bounded contact-count bands and binomial rate intervals.
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
Investigate diminishing response while considering that difficult-to-convert clients may receive more calls.
Where the conclusion stops
Observational marketing records do not identify campaign uplift. Month and row order are not precise timestamps; repeated-client identifiers are unavailable. Models are research diagnostics, not financial eligibility or automated contact decisions.
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.