====== Why backend leaks compound silently ======

===== The slow erosion problem =====

Backend leaks rarely explode overnight.

They drip.

A small refund increase.
A slight drop in rebill survival.
A minor rise in churn.

Individually, they seem manageable.

Over time, they compound.

CBSplit was built to detect this silent erosion before it becomes structural damage.

===== Leaks begin as small percentages =====

Backend leaks often appear as:

  
  * 2–3% higher refund ratio
  * 5% lower first rebill survival
  * Slight increase in payment failures
  * Gradual rise in cancellations

At low scale, these numbers look insignificant.

At higher volume, they multiply into meaningful revenue loss.

===== Refund drift reduces net margin quietly =====

A small refund increase:

  
  * Reduces net revenue
  * Raises chargeback exposure
  * Weakens processor trust
  * Compresses margin

Because revenue initially appears strong, the leak remains unnoticed.

CBSplit recalculates performance after refund reconciliation.

===== Churn velocity compounds over billing cycles =====

In subscription funnels:

  
  * Small churn increases shorten LTV
  * Shorter LTV shifts breakeven thresholds
  * Lower retention weakens scaling capacity

These effects compound across cohorts.

Front-end dashboards do not capture this compounding decline.

===== Retry dependence masks instability =====

Payment retries can:

  
  * Temporarily recover failed transactions
  * Delay visible churn
  * Inflate apparent retention

If revenue depends heavily on retries, stability is fragile.

When retry performance changes, revenue drops quickly.

CBSplit distinguishes durable rebills from recovery-driven revenue.

===== Scaling amplifies silent leaks =====

At low volume, backend leaks may appear harmless.

When scaled:

  
  * Refund counts increase dramatically
  * Churn impact multiplies
  * Net revenue erodes faster
  * Risk thresholds approach

Silent leaks become visible only after expansion.

CBSplit identifies structural weakness before scaling magnifies it.

===== Aggregated reporting hides gradual decline =====

Blended dashboards average:

  
  * Strong cohorts
  * Weak cohorts
  * High-quality traffic
  * Fragile segments

Gradual backend decline can hide inside stable averages.

Segmentation is required to detect drift.

===== Compounding works in reverse =====

Compounding can grow profit.

It can also amplify loss.

Small backend weaknesses:

  
  * Reduce LTV
  * Increase acquisition pressure
  * Lower allowable CPA
  * Force campaign contraction

The erosion is slow but persistent.

CBSplit tracks lifecycle performance across time horizons.