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====== Why CBSplit surfaces hidden funnel truths ======

===== The illusion of visibility =====

Most funnel dashboards look complete.

Conversions are tracked.
Revenue is displayed.
ROAS appears calculated.
Winners seem obvious.

Yet critical truths remain hidden.

CBSplit was built to expose what traditional tools cannot see.

===== Surface metrics hide lifecycle instability =====

Standard dashboards focus on:

  
  * Click-through rate
  * Conversion rate
  * Front-end revenue
  * Average order value

They do not fully reveal:

  
  * Refund-adjusted profitability
  * Subscription churn velocity
  * Rebill survival strength
  * Chargeback exposure
  * Processor risk patterns

Surface strength can mask structural weakness.

===== Blended averages conceal segment fragility =====

Aggregated reports combine:

  
  * Multiple traffic sources
  * Diverse geographies
  * Different buyer intents
  * Cohorts at different ages

Strong segments can hide weak ones.

Refund clusters may remain invisible inside blended data.

CBSplit preserves segmentation to expose variance.

===== Time hides truth =====

Early performance often looks strong.

Over time:

  
  * Refund windows close
  * Rebill cycles mature
  * Cohorts reveal churn patterns
  * Retry logic shows fragility

Short-term dashboards reward immediacy.

Lifecycle truth emerges later.

CBSplit evaluates performance across time horizons.

===== Backend leaks remain undetected =====

Funnels may appear profitable while:

  
  * Refund ratios drift upward
  * Retention declines gradually
  * Payment retries inflate apparent revenue
  * Processor scrutiny increases

These leaks compound silently.

Without lifecycle-aware tracking, erosion goes unnoticed.

===== Front-end wins can conceal backend failure =====

A funnel can:

  
  * Increase conversion rate
  * Raise EPC
  * Improve day-one ROAS

And simultaneously:

  
  * Increase churn
  * Raise refund probability
  * Lower net LTV
  * Reduce margin at scale

Classic analytics celebrate the lift.

CBSplit audits the lifecycle.

===== Traffic quality differences stay hidden =====

Two campaigns may look identical initially.

Over time, one produces:

  
  * Stable subscribers
  * Low refund ratios
  * Predictable LTV

The other produces:

  
  * Early cancellations
  * Refund spikes
  * Risk accumulation

Only lifecycle tracking reveals the divergence.

===== Hidden truth determines scalable profit =====

Sustainable growth depends on:

  
  * Refund-adjusted revenue
  * Rebill-adjusted LTV
  * Cohort durability
  * Risk-aware scaling thresholds

Without these signals, scaling decisions are speculative.

CBSplit transforms hidden signals into actionable clarity.