Churn Reason Summary
Normalize and count supplied churn-reason labels.
Description
Churn-reason summaries group supplied exit labels into frequencies.
Churn-reason summaries group supplied exit labels into frequencies. Normalization merges spelling that differs only in surrounding whitespace or letter case.1
Normalize and count supplied churn-reason labels.
When to use Churn Reason Summary
Use this tool to normalize and count supplied churn-reason labels.
Prepare the text, recorded observations, aligned figures or editorial criteria requested. Confirm what each label, count, timestamp or supplied flag represents before interpreting the result.
How to use Churn Reason Summary and understand its results
- Prepare the text, recorded observations, aligned figures or editorial criteria requested. Confirm what each label, count, timestamp or supplied flag represents before interpreting the result.
- Enter reasons using the field table and calculation rules, then run the tool.
- Read reasonCounts, mostCommonReason, uniqueReasonCount. The explanation below defines the units, signs, ordering and any flags or placeholder values.
- If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.
| Input field | Meaning | Value type; see rules below | Requirement |
|---|---|---|---|
| reasons | Churn reasons | list of string | Required |
Enter reason strings; trim/lowercase with en-US rules and reject blank entries. Aggregate counts, sort ties alphabetically with localeCompare and return summaries, most common label and unique count. Empty input returns empty summaries, mostCommon=none and zero unique reasons.
summary=reason: count; order=count descending, then localeCompare Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| reasonCounts | Normalized reason counts | list of string |
| mostCommonReason | Most common reason | string |
| uniqueReasonCount | Unique reason count | integer; minimum: 0 |
{
"input": {
"reasons": [
"price",
"coverage",
"Price",
"price"
]
},
"output": {
"reasonCounts": [
"price: 3",
"coverage: 1"
],
"mostCommonReason": "price",
"uniqueReasonCount": 2
}
}Limitations and assumptions
No subscriber behavior or causal explanation is inferred; labels are supplied observations.
Numeric inputs must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Lists are limited to 100,000 entries; the rules above may require smaller limits. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.
Alternative or Complementary methods
Use Subscriber Sunset: Measure subscriber access sunset timing against a supplied allowance. For a complementary task, use Play-by-Play Code Count: Count selected play-by-play codes and identify absent tracked codes.
References
-
Churn Reason Summary — tool.io
Similar or alternative tools
- Subscriber Sunset
Measure subscriber access sunset timing against a supplied allowance.
- Play-by-Play Code Count
Count selected play-by-play codes and identify absent tracked codes.